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content/en/case-studies/OWNERS
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# Owned by Kubernetes blog reviewers.
options:
no_parent_owners: true
# reviewers: // List any reviewers here
approvers:
- alexcontini
- kbarnard10
- sarahkconway
- zacharysarah
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---
title: Case Studies
bigheader: Kubernetes User Case Studies
abstract: A collection of users running Kubernetes in production.
layout: basic
class: gridPage
cid: caseStudies
---
<section id="mainContent">
<main>
<div class="content">
<div class="case-studies">
<div class="case-study">
<img src="/images/case_studies/squarespace_feature.png" alt="squarespace">
<p class="quote">"Once you prove that Kubernetes solves one problem, everyone immediately starts solving other problems without you even having to evangelize it."</p>
<!--<p class="attrib">— Kevin Lynch, Staff Engineer on the Site Reliability team at Squarespace</p>-->
<a href="/case-studies/squarespace/">Read about Squarespace</a>
</div>
<div class="case-study">
<img src="/images/case_studies/crowdfire_feature.png" alt="Crowdfire">
<p class="quote">"In the 15 months that we’ve been using Kubernetes, it has been amazing for us. It enabled us to iterate quickly, increase development speed, and continuously deliver new features and bug fixes to our users, while keeping our operational costs and infrastructure management overhead under control."</p>
<!--<p class="attrib">—Amanpreet Singh, Software Engineer at Crowdfire</p>-->
<a href="/case-studies/crowdfire/">Read about Crowdfire</a>
</div>
<div class="case-study">
<img src="/images/case_studies/zalando_feature.png" alt="Zalando">
<p class="quote">"We envision all Zalando delivery teams running their containerized applications on a state-of-the-art, reliable and scalable cluster infrastructure provided by Kubernetes."</p>
<!--<p class="attrib">—Henning Jacobs, Head of Developer Productivity at Zalando</p>-->
<a href="/case-studies/zalando/">Read about Zalando</a>
</div>
<div class="case-study">
<img src="/images/case_studies/amadeus_feature.png" alt="amadeus">
<p class="quote">"We didn’t think that we could achieve them with our existing system. We need new automation, things that Kubernetes and OpenShift bring."</p>
<!--<p class="attrib">— Eric Mountain, Senior Expert, Distributed Systems at Amadeus IT Group</p>-->
<a href="/case-studies/amadeus/">Read about Amadeus</a>
</div>
</div>
</div>
</main>
</section>
<section id="video">
<main>
<!--<div><button onclick="kub.showVideo()"><img src="/images/case_studies/video_thumb.jpg" alt="Zulily video"><h6>Kubernetes at zulily</h6></button></div>-->
<div>
<!--<h3>Box</h3>-->
<h4><i>"Kubernetes has the opportunity to be the new cloud platform. The amount of innovation that's going to come from being able to standardize on Kubernetes as a platform is incredibly exciting - more exciting than anything I've seen in the last 10 years of working on the cloud."</i></h4>
<img src="/images/case_studies/box-small.png" id="boxlogo" alt="Box">
</div>
<div style= "padding-left: 40px;"><button onclick="kub.showVideo()"><img src="/images/case_studies/Video-Clip-Box.png" alt="Box video"><h6>Kubernetes at Box</h6></button></div>
</main>
</section>
<section id="users">
<main>
<h3>Kubernetes Users</h3>
<div id="usersGrid">
<a target="_blank" href="/case-studies/squarespace/"><img src="/images/case_studies/squarespace_feature.png" alt="Squarespace"></a>
<a target="_blank" href="/case-studies/crowdfire/"><img src="/images/case_studies/crowdfire_feature.png" alt="Crowdfire"></a>
<a target="_blank" href="/case-studies/zalando/"><img src="/images/case_studies/zalando_feature.png" alt="Zalando"></a>
<a target="_blank" href="/case-studies/amadeus/"><img src="/images/case_studies/amadeus.png" alt="Amadeus"></a>
<a target="_blank" href="/case-studies/ancestry/"><img src="/images/case_studies/ancestry.png" alt="Ancestry.com"></a>
<a target="_blank" href="/case-studies/blablacar/"><img src="/images/case_studies/blablacar.png" alt="BlaBlaCar"></a>
<a target="_blank" href="/case-studies/blackrock/"><img src="/images/case_studies/blackrock2.png" alt="BlackRock"></a>
<a target="_blank" href="/case-studies/box/"><img src="/images/case_studies/box_logo.png" alt="box"></a>
<a target="_blank" href="/case-studies/buffer/"><img src="/images/case_studies/buffer_logo.png" alt="Buffer"></a>
<a target="_blank" href="https://cloud.google.com/customers/ccp-games/"><img src="/images/case_studies/ccp.png" alt="CCP Games"></a>
<a target="_blank" href="https://youtu.be/lmeFkH-rHII"><img src="/images/case_studies/comcast_logo.png" alt="Comcast"></a>
<a target="_blank" href="http://searchitoperations.techtarget.com/news/450297178/Tech-firms-roll-out-Kubernetes-in-production"><img src="/images/case_studies/concur.png" alt="Concur"></a>
<a target="_blank" href="http://www.nextplatform.com/2015/11/12/inside-ebays-shift-to-kubernetes-and-containers-atop-openstack/"><img src="/images/case_studies/ebay_logo.png" alt="Ebay"></a>
<a target="_blank" href="http://blogs.wsj.com/cio/2016/02/24/big-changes-in-goldmans-software-emerge-from-small-containers/"><img src="/images/case_studies/gs.png" alt="Goldman Sachs"></a>
<a target="_blank" href="/case-studies/golfnow/"><img src="/images/case_studies/golfnow_logo.png" alt="GolfNow"></a>
<a target="_blank" href="/case-studies/haufegroup/"><img src="/images/case_studies/haufegroup_logo.png" alt="Haufe Group"></a>
<a target="_blank" href="/case-studies/huawei/"><img src="/images/case_studies/huawei.png" alt="Huawei"></a>
<a target="_blank" href="http://blog.kubernetes.io/2017/02/inside-jd-com-shift-to-kubernetes-from-openstack.html"><img src="/images/case_studies/jd.png" alt="JD.COM"></a>
<a target="_blank" href="https://www.openstack.org/videos/video/running-kubernetes-on-openstack-at-liveperson"><img src="/images/case_studies/liveperson.png" alt="LivePerson"></a>
<a target="_blank" href="https://youtu.be/YkOY7DgXKyw"><img src="/images/case_studies/monzo_logo.png" alt="monzo"></a>
<a target="_blank" href="https://www.youtube.com/watch?v=P5qfyv_zGcU"><img src="/images/case_studies/nyt.png" alt="New York Times"></a>
<a target="_blank" href="https://openai.com/blog/infrastructure-for-deep-learning"><img src="/images/case_studies/openai.png" alt="OpenAI"></a>
<a target="_blank" href="/case-studies/peardeck/"><img src="/images/case_studies/peardeck_logo.png" alt="peardeck"></a>
<a href="/case-studies/pearson/"><img src="/images/case_studies/pearson_logo.png" alt="Pearson"></a>
<a target="_blank" href="https://cloud.google.com/customers/philips/"><img src="/images/case_studies/philips_logo.png" alt="Philips"></a>
<a target="_blank" href="https://cloudplatform.googleblog.com/2016/09/bringing-Pokemon-GO-to-life-on-Google-Cloud.html"><img src="/images/case_studies/pokemon_go_logo.png" alt="Pokemon GO"></a>
<a target="_blank" href="http://www.nextplatform.com/2016/05/24/samsung-experts-put-kubernetes-paces/"><img src="/images/case_studies/sds.png" alt="Samsung SDS"></a>
<a target="_blank" href="https://youtu.be/4gyeixJLabo"><img src="/images/case_studies/sap.png" alt="SAP"></a>
<a target="_blank" href="https://www.youtube.com/watch?v=5378N5iLb2Q"><img src="/images/case_studies/soundcloud.png" alt="SoundCloud"></a>
<a target="_blank" href="https://www.youtube.com/watch?v=F3iMkz_NSvU"><img src="/images/case_studies/homeoffice.png" alt="UK Home Office"></a>
<a target="_blank" href="http://thenewstack.io/wepay-kubernetes-changed-business/"><img src="/images/case_studies/wepay.png" alt="WePay"></a>
<a target="_blank" href="/case-studies/wink/"><img src="/images/case_studies/wink.png" alt="Wink"></a>
<a href="/case-studies/wikimedia/"><img src="/images/case_studies/wikimedia_logo.png" alt="Wikimedia"></a>
<a target="_blank" href="http://blog.kubernetes.io/2016/10/kubernetes-and-openstack-at-yahoo-japan.html"><img src="/images/case_studies/yahooJapan_logo.png" alt="Yahoo! Japan"></a>
<a target="_blank" href="#" onclick="event.preventDefault(); kub.showVideo()"><img src="/images/case_studies/zulily_logo.png" alt="zulily"></a>
<a target="_blank" href="https://docs.google.com/a/google.com/forms/d/e/1FAIpQLScuI7Ye3VQHQTwBASrgkjQDSS5TP0g3AXfFhwSM9YpHgxRKFA/viewform" class="tell-your-story"><img src="/images/case_studies/story.png" alt="Tell your story"></a>
</div>
</main>
</section>
<div id="videoPlayer">
<!--<iframe data-url="https://www.youtube.com/watch?v=of45hYbkIZs" frameborder="0" allowfullscreen></iframe>-->
<iframe data-url="https://www.youtube.com/embed/of45hYbkIZs?autoplay=1" frameborder="0" allowfullscreen="true"></iframe>
<button id="closeButton"></button>
</div>
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---
title: Amadeus Case Study
case_study_styles: true
cid: caseStudies
css: /css/style_amadeus.css
---
<div class="banner1">
<h1> CASE STUDY:<img src="/images/amadeus_logo.png" class="header_logo"><br> <div class="subhead">Another Technical Evolution for a 30-Year-Old Company
</div></h1>
</div>
<div class="details">
Company &nbsp;<b>Amadeus IT Group</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Madrid, Spain</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Travel Technology</b>
</div>
<hr>
<section class="section1">
<div class="cols">
<div class="col1">
<h2>Challenge</h2>
In the past few years, Amadeus, which provides IT solutions to the travel industry around the world, found itself in need of a new platform for the 5,000 services supported by its service-oriented architecture. The 30-year-old company operates its own data center in Germany, and there were growing demands internally and externally for solutions that needed to be geographically dispersed. And more generally, "we had objectives of being even more highly available," says Eric Mountain, Senior Expert, Distributed Systems at Amadeus. Among the company’s goals: to increase automation in managing its infrastructure, optimize the distribution of workloads, use data center resources more efficiently, and adopt new technologies more easily.
</div>
<div class="col2">
<h2>Solution</h2>
Mountain has been overseeing the company’s migration to <a href="http://kubernetes.io/">Kubernetes</a>, using <a href="https://www.openshift.org/">OpenShift</a> Container Platform, <a href="https://www.redhat.com/en">Red Hat</a>’s enterprise container platform.
<br><br>
<h2>Impact</h2>
One of the first projects the team deployed in Kubernetes was the Amadeus Airline Cloud Availability solution, which helps manage ever-increasing flight-search volume. "It’s now handling in production several thousand transactions per second, and it’s deployed in multiple data centers throughout the world," says Mountain. "It’s not a migration of an existing workload; it’s a whole new workload that we couldn’t have done otherwise. [This platform] gives us access to market opportunities that we didn’t have before."
</div>
</div>
</section>
<div class="banner2">
<div class="banner2text">
"We want multi-data center capabilities, and we want them for our mainstream system as well. We didn’t think that we could achieve them with our existing system. We need new automation, things that Kubernetes and OpenShift bring."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Eric Mountain, Senior Expert, Distributed Systems at Amadeus IT Group</span>
</div>
</div>
<section class="section2">
<div class="fullcol">
<h2>In his two decades at Amadeus, Eric Mountain has been the migrations guy. </h2>
Back in the day, he worked on the company’s move from Unix to Linux, and now he’s overseeing the journey to cloud native. "Technology just keeps changing, and we embrace it," he says. "We are celebrating our 30 years this year, and we continue evolving and innovating to stay cost-efficient and enhance everyone’s travel experience, without interrupting workflows for the customers who depend on our technology."<br><br>
That was the challenge that Amadeus—which provides IT solutions to the travel industry around the world, from flight searches to hotel bookings to customer feedback—faced in 2014. The technology team realized it was in need of a new platform for the 5,000 services supported by its service-oriented architecture.<br><br>
The tipping point occurred when they began receiving many requests, internally and externally, for solutions that needed to be geographically outside the company’s main data center in Germany. "Some requests were for running our applications on customer premises," Mountain says. "There were also new services we were looking to offer that required response time to the order of a few hundred milliseconds, which we couldn’t achieve with transatlantic traffic. Or at least, not without eating into a considerable portion of the time available to our applications for them to process individual queries."<br><br>
More generally, the company was interested in leveling up on high availability, increasing automation in managing infrastructure, optimizing the distribution of workloads and using data center resources more efficiently. "We have thousands and thousands of servers," says Mountain. "These servers are assigned roles, so even if the setup is highly automated, the machine still has a given role. It’s wasteful on many levels. For instance, an application doesn’t necessarily use the machine very optimally. Virtualization can help a bit, but it’s not a silver bullet. If that machine breaks, you still want to repair it because it has that role and you can’t simply say, ‘Well, I’ll bring in another machine and give it that role.’ It’s not fast. It’s not efficient. So we wanted the next level of automation."<br><br>
</div>
</section>
<div class="banner3">
<div class="banner3text">
"We hope that if we build on what others have built, what we do might actually be upstream-able. As Kubernetes and OpenShift progress, we see that we are indeed able to remove some of the additional layers we implemented to compensate for gaps we perceived earlier."
</div>
</div>
<section class="section3">
<div class="fullcol">
While mainly a C++ and Java shop, Amadeus also wanted to be able to adopt new technologies more easily. Some of its developers had started using languages like <a href="https://www.python.org/">Python</a> and databases like <a href="https://www.couchbase.com/">Couchbase</a>, but Mountain wanted still more options, he says, "in order to better adapt our technical solutions to the products we offer, and open up entirely new possibilities to our developers." Working with recent technologies and cool new things would also make it easier to attract new talent.
<br><br>
All of those needs led Mountain and his team on a search for a new platform. "We did a set of studies and proofs of concept over a fairly short period, and we considered many technologies," he says. "In the end, we were left with three choices: build everything on premise, build on top of <a href="http://kubernetes.io/">Kubernetes</a> whatever happens to be missing from our point of view, or go with <a href="https://www.openshift.com/">OpenShift</a> and build whatever remains there."
<br><br>
The team decided against building everything themselves—though they’d done that sort of thing in the past—because "people were already inventing things that looked good," says Mountain.
<br><br>
Ultimately, they went with OpenShift Container Platform, <a href="https://www.redhat.com/en">Red Hat</a>’s Kubernetes-based enterprise offering, instead of building on top of Kubernetes because "there was a lot of synergy between what we wanted and the way Red Hat was anticipating going with OpenShift," says Mountain. "They were clearly developing Kubernetes, and developing certain things ahead of time in OpenShift, which were important to us, such as more security."
<br><br>
The hope was that those particular features would eventually be built into Kubernetes, and, in the case of security, Mountain feels that has happened. "We realize that there’s always a certain amount of automation that we will probably have to develop ourselves to compensate for certain gaps," says Mountain. "The less we do that, the better for us. We hope that if we build on what others have built, what we do might actually be upstream-able. As Kubernetes and OpenShift progress, we see that we are indeed able to remove some of the additional layers we implemented to compensate for gaps we perceived earlier."
</div>
</section>
<div class="banner4">
<div class="banner4text">
"It’s not a migration of an existing workload; it’s a whole new workload that we couldn’t have done otherwise. [This platform] gives us access to market opportunities that we didn’t have before."
</div>
</div>
<section class="section4">
<div class="fullcol">
The first project the team tackled was one that they knew had to run outside the data center in Germany. Because of the project’s needs, "We couldn’t rely only on the built-in Kubernetes service discovery; we had to layer on top of that an extra service discovery level that allows us to load balance at the operation level within our system," says Mountain. They also built a stream dedicated to monitoring, which at the time wasn’t offered in the Kubernetes or OpenShift ecosystem. Now that <a href="https://www.prometheus.io/">Prometheus</a> and other products are available, Mountain says the company will likely re-evaluate their monitoring system: "We obviously always like to leverage what Kubernetes and OpenShift can offer."
<br><br>
The second project ended up going into production first: the Amadeus Airline Cloud Availability solution, which helps manage ever-increasing flight-search volume and was deployed in public cloud. Launched in early 2016, it is "now handling in production several thousand transactions per second, and it’s deployed in multiple data centers throughout the world," says Mountain. "It’s not a migration of an existing workload; it’s a whole new workload that we couldn’t have done otherwise. [This platform] gives us access to market opportunities that we didn’t have before."
<br><br>
Having been through this kind of technical evolution more than once, Mountain has advice on how to handle the cultural changes. "That’s one aspect that we can tackle progressively," he says. "We have to go on supplying our customers with new features on our pre-existing products, and we have to keep existing products working. So we can’t simply do absolutely everything from one day to the next. And we mustn’t sell it that way."
<br><br>
The first order of business, then, is to pick one or two applications to demonstrate that the technology works. Rather than choosing a high-impact, high-risk project, Mountain’s team selected a smaller application that was representative of all the company’s other applications in its complexity: "We just made sure we picked something that’s complex enough, and we showed that it can be done."
</div>
</section>
<div class="banner5">
<div class="banner5text">
"The bottom line is we want these multi-data center capabilities, and we want them as well for our mainstream system," he says. "And we don’t think that we can implement them with our previous system. We need the new automation, homogeneity, and scale that Kubernetes and OpenShift bring."
</div>
</div>
<section class="section5">
<div class="fullcol">
Next comes convincing people. "On the operations side and on the R&D side, there will be people who say quite rightly, ‘There is a system, and it works, so why change?’" Mountain says. "The only thing that really convinces people is showing them the value." For Amadeus, people realized that the Airline Cloud Availability product could not have been made available on the public cloud with the company’s existing system. The question then became, he says, "Do we go into a full-blown migration? Is that something that is justified?"
<br><br>
"The bottom line is we want these multi-data center capabilities, and we want them as well for our mainstream system," he says. "And we don’t think that we can implement them with our previous system. We need the new automation, homogeneity, and scale that Kubernetes and OpenShift bring."
<br><br>
So how do you get everyone on board? "Make sure you have good links between your R&D and your operations," he says. "Also make sure you’re going to talk early on to the investors and stakeholders. Figure out what it is that they will be expecting from you, that will convince them or not, that this is the right way for your company."
<br><br>
His other advice is simply to make the technology available for people to try it. "Kubernetes and OpenShift Origin are open source software, so there’s no complicated license key for the evaluation period and you’re not limited to 30 days," he points out. "Just go and get it running." Along with that, he adds, "You’ve got to be prepared to rethink how you do things. Of course making your applications as cloud native as possible is how you’ll reap the most benefits: 12 factors, CI/CD, which is continuous integration, continuous delivery, but also continuous deployment."
<br><br>
And while they explore that aspect of the technology, Mountain and his team will likely be practicing what he preaches to others taking the cloud native journey. "See what happens when you break it, because it’s important to understand the limits of the system," he says. Or rather, he notes, the advantages of it. "Breaking things on Kube is actually one of the nice things about it—it recovers. It’s the only real way that you’ll see that you might be able to do things."
</div>
</section>
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---
title: Ancestry Case Study
case_study_styles: true
cid: caseStudies
css: /css/style_ancestry.css
---
<div class="banner1">
<h1> CASE STUDY:<img src="http://c.mfcreative.com/i/logo/ancestry-on-dark.svg" width="22%" style="margin-bottom:-12px;margin-left:3px;"><br> <div class="subhead">Digging Into the Past With New Technology</div></h1>
</div>
<div class="details">
Company &nbsp;<b>Ancestry</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Lehi, Utah</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Internet Company, Online Services</b>
</div>
<hr>
<section class="section1">
<div class="cols">
<div class="col1">
<h2>Challenge</h2>
Ancestry, the global leader in family history and consumer genomics, uses sophisticated engineering and technology to help everyone, everywhere discover the story of what led to them. The company has spent more than 30 years innovating and building products and technologies that at their core, result in real and emotional human responses. <a href="https://www.ancestry.com">Ancestry</a> currently serves more than 2.6 million paying subscribers, holds 20 billion historical records, 90 million family trees and more than four million people are in its AncestryDNA network, making it the largest consumer genomics DNA network in the world. The company's popular website, <a href="https://www.ancestry.com">ancestry.com</a>, has been working with big data long before the term was popularized. The site was built on hundreds of services, technologies and a traditional deployment methodology. "It's worked well for us in the past," says Paul MacKay, software engineer and architect at Ancestry, "but had become quite cumbersome in its processing and is time-consuming. As a primarily online service, we are constantly looking for ways to accelerate to be more agile in delivering our solutions and our&nbsp;products."
<br>
</div>
<div class="col2">
<h2>Solution</h2>
The company is transitioning to cloud native infrastructure, using <a href="https://www.docker.com">Docker</a> containerization, <a href="https://kubernetes.io">Kubernetes</a> orchestration and <a href="https://prometheus.io">Prometheus</a> for cluster monitoring.<br>
<br>
<h2>Impact</h2>
"Every single product, every decision we make at Ancestry, focuses on delighting our customers with intimate, sometimes life-changing discoveries about themselves and their families," says MacKay. "As the company continues to grow, the increased productivity gains from using Kubernetes has helped Ancestry make customer discoveries faster. With the move to Dockerization for example, instead of taking between 20 to 50 minutes to deploy a new piece of code, we can now deploy in under a minute for much of our code. We’ve truly experienced significant time savings in addition to the various features and benefits from cloud native and Kubernetes-type technologies."
</div>
</div>
</section>
<div class="banner2">
<div class="banner2text">
"At a certain point, you have to step back if you're going to push a new technology and get key thought leaders with engineers within the organization to become your champions for new technology adoption. At training sessions, the development teams were always the ones that were saying, 'Kubernetes saved our time tremendously; it's an enabler. It really is incredible.'"<br><br><span style="font-size:16px">- PAUL MACKAY, SOFTWARE ENGINEER AND ARCHITECT AT ANCESTRY</span>
</div>
</div>
<section class="section2">
<div class="fullcol">
<h2>It started with a Shaky Leaf.</h2>
Since its introduction a decade ago, the Shaky Leaf icon has become one of Ancestry's signature features, which signals to users that there's a helpful hint you can use to find out more about your family tree.<br><br>
So when the company decided to begin moving its infrastructure to cloud native technology, the first service that was launched on <a href="https://kubernetes.io">Kubernetes</a>, the open source platform for managing application containers across clusters of hosts, was this hint system. Think of it as Amazon's recommended products, but instead of recommending products the company recommends records, stories, or familial connections. "It was a very important part of the site," says Ancestry software engineer and architect Paul MacKay, "but also small enough for a pilot project that we knew we could handle in a very appropriate, secure way."<br><br>
And when it went live smoothly in early 2016, "our deployment time for this service literally was cut down from 50 minutes to 2 or 5 minutes," MacKay adds. "The development team was just thrilled because we're focused on supplying a great experience for our customers. And that means features, it means stability, it means all those things that we need for a first-in-class type operation."<br><br>
The stability of that Shaky Leaf was a signal for MacKay and his team that their decision to embrace cloud native technologies was the right one for the company. With a private data center, Ancestry built its website (which launched in 1996) on hundreds of services and technologies and a traditional deployment methodology. "It worked well for us in the past, but the sum of the legacy systems became quite cumbersome in its processing and was time-consuming," says MacKay. "We were looking for other ways to accelerate, to be more agile in delivering our solutions and our products."
</div>
</section>
<div class="banner3">
<div class="banner3text">
"And when it [Kubernetes] went live smoothly in early 2016, 'our deployment time for this service literally was cut down from 50 minutes to 2 or 5 minutes,' MacKay adds. 'The development team was just thrilled because we're focused on supplying a great experience for our customers. And that means features, it means stability, it means all those things that we need for a first-in-class type operation.'"
</div>
</div>
<section class="section3">
<div class="fullcol">
That need led them in 2015 to explore containerization. Ancestry engineers had already been using technology like <a href="https://www.java.com/en/">Java</a> and <a href="https://www.python.org">Python</a> on Linux, so part of the decision was about making the infrastructure more Linux-friendly. They quickly decided that they wanted to go with Docker for containerization, "but it always comes down to the orchestration part of it to make it really work," says MacKay.<br><br>
His team looked at orchestration platforms offered by <a href="https://docs.docker.com/compose/">Docker Compose</a>, <a href="http://mesos.apache.org">Mesos</a> and <a href="https://www.openstack.org/software/">OpenStack</a>, and even started to prototype some homegrown solutions. And then they started hearing rumblings of the imminent release of Kubernetes v1.0. "At the forefront, we were looking at the secret store, so we didn't have to manage that all ourselves, the config maps, the methodology of seamless deployment strategy," he says. "We found that how Kubernetes had done their resources, their types, their labels and just their interface was so much further advanced than the other things we had seen. It was a feature fit."<br><br>
<div class="quote">
Plus, MacKay says, "I just believed in the confidence that comes with the history that Google has with containerization. So we started out right on the leading edge of it. And we haven't looked back since."</div><br>
Which is not to say that adopting a new technology hasn't come with some challenges. "Change is hard," says MacKay. "Not because the technology is hard or that the technology is not good. It's just that people like to do things like they had done [before]. You have the early adopters and you have those who are coming in later. It was a learning experience on both sides."<br><br>
Figuring out the best deployment operations for Ancestry was a big part of the work it took to adopt cloud native infrastructure. "We want to make sure the process is easy and also controlled in the manner that allows us the highest degree of security that we demand and our customers demand," says MacKay. "With Kubernetes and other products, there are some good solutions, but a little bit of glue is needed to bring it into corporate processes and governances. It's like having a set of gloves that are generic, but when you really do want to grab something you have to make it so it's customized to you. That's what we had to do."<br><br>
Their best practices include allowing their developers to deploy into development stage and production, but then controlling the aspects that need governance and auditing, such as secrets. They found that having one namespace per service is useful for achieving that containment of secrets and config maps. And for their needs, having one container per pod makes it easier to manage and to have a smaller unit of deployment.
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"The success of Ancestry's first deployment of the hint system on Kubernetes helped create momentum for greater adoption of the technology."
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With that process established, the time spent on deployment was cut down to under a minute for some services. "As programmers, we have what's called REPL: read, evaluate, print, and loop, but with Kubernetes, we have CDEL: compile, deploy, execute, and loop," says MacKay. "It's a very quick loop back and a great benefit to understand that when our services are deployed in production, they're the same as what we tested in the pre-production environments. The approach of cloud native for Ancestry provides us a better ability to scale and to accommodate the business needs as work loads occur."<br><br>
The success of Ancestry's first deployment of the hint system on Kubernetes helped create momentum for greater adoption of the technology. "Engineers like to code, they like to do features, they don't like to sit around waiting for things to be deployed and worrying about scaling up and out and down," says MacKay. "After a while the engineers became our champions. At training sessions, the development teams were always the ones saying, 'Kubernetes saved our time tremendously; it's an enabler; it really is incredible.' Over time, we were able to convince our management that this was a transition that the industry is making and that we needed to be a part of it."<br><br>
A year later, Ancestry has transitioned a good number of applications to Kubernetes. "We have many different services that make up the rich environment that [the website] has from both the DNA side and the family history side," says MacKay. "We have front-end stacks, back-end stacks and back-end processing type stacks that are in the cluster."<br><br>
The company continues to weigh which services it will move forward to Kubernetes, which ones will be kept as is, and which will be replaced in the future and thus don't have to be moved over. MacKay estimates that the company is "approaching halfway on those features that are going forward. We don't have to do a lot of convincing anymore. It's more of an issue of timing with getting product management and engineering staff the knowledge and information that they need."
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"... 'I believe in Kubernetes. I believe in containerization. I think
if we can get there and establish ourselves in that world, we will be further along and far better off being agile and all the things we talk about,
and it'll&nbsp;go&nbsp;forward.'"
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Looking ahead, MacKay sees Ancestry maximizing the benefits of Kubernetes in 2017. "We're very close to having everything that should be or could be in a Linux-friendly world in Kubernetes by the end of the year," he says, adding that he's looking forward to features such as federation and horizontal pod autoscaling that are currently in the works. "Kubernetes has been very wonderful for us and we continue to ride the wave."<br><br>
That wave, he points out, has everything to do with the vibrant Kubernetes community, which has grown by leaps and bounds since Ancestry joined it as an early adopter. "This is just a very rough way of judging it, but on Slack in June 2015, there were maybe 500 on there," MacKay says. "The last time I looked there were maybe 8,500 just on the Slack channel. There are so many major companies and different kinds of companies involved now. It's the variety of contributors, the number of contributors, the incredibly competent and friendly community."<br><br>
As much as he and his team at Ancestry have benefited from what he calls "the goodness and the technical abilities of many" in the community, they've also contributed information about best practices, logged bug issues and participated in the open source conversation. And they've been active in attending <a href="https://www.meetup.com/Utah-Kubernetes-Meetup/">meetups</a> to help educate and give back to the local tech community in Utah. Says MacKay: "We're trying to give back as far as our experience goes, rather than just code."
<br><br>When he meets with companies considering adopting cloud native infrastructure, the best advice he has to give from Ancestry's Kubernetes journey is this: "Start small, but with hard problems," he says. And "you need a patron who understands the vision of containerization, to help you tackle the political as well as other technical roadblocks that can occur when change is needed."<br><br>
With the changes that MacKay's team has led over the past year and a half, cloud native will be part of Ancestry's technological genealogy for years to come. MacKay has been such a champion of the technology that he says people have jokingly accused him of having a Kubernetes tattoo.<br><br>
"I really don't," he says with a laugh. "But I'm passionate. I'm not exclusive to any technology; I use whatever I need that's out there that makes us great. If it's something else, I'll use it. But right now I believe in Kubernetes. I believe in containerization. I think if we can get there and establish ourselves in that world, we will be further along and far better off being agile and all the things we talk about, and it'll go forward."<br><br>
He pauses. "So, yeah, I guess you can say I'm an evangelist for Kubernetes," he says. "But I'm not getting a tattoo!"
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<h1> CASE STUDY:<img src="/images/blablacar_logo.png" class="header_logo"><br> <div class="subhead">Turning to Containerization to Support Millions of Rideshares</div></h1>
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Company &nbsp;<b>BlaBlaCar</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Paris, France</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Ridesharing Company</b>
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<h2>Challenge</h2>
The world’s largest long-distance carpooling community, <a href="https://www.blablacar.com/">BlaBlaCar</a>, connects 40 million members across 22 countries. The company has been experiencing exponential growth since 2012 and needed its infrastructure to keep up. "When you’re thinking about doubling the number of servers, you start thinking, ‘What should I do to be more efficient?’" says Simon Lallemand, Infrastructure Engineer at BlaBlaCar. "The answer is not to hire more and more people just to deal with the servers and installation." The team knew they had to scale the platform, but wanted to stay on their own bare metal servers.
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<br>
<h2>Solution</h2>
Opting not to shift to cloud virtualization or use a private cloud on their own servers, the BlaBlaCar team became early adopters of containerization, using the CoreOs runtime <a href="https://coreos.com/rkt">rkt</a>, initially deployed using <a href="https://coreos.com/fleet/docs/latest/launching-containers-fleet.html">fleet</a> cluster manager. Last year, the company switched to <a href="http://kubernetes.io/">Kubernetes</a> orchestration, and now also uses <a href="https://prometheus.io/">Prometheus</a> for monitoring.
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<h2>Impact</h2>
"Before using containers, it would take sometimes a day, sometimes two, just to create a new service," says Lallemand. "With all the tooling that we made around the containers, copying a new service now is a matter of minutes. It’s really a huge gain. We are better at capacity planning in our data center because we have fewer constraints due to this abstraction between the services and the hardware we run on. For the developers, it also means they can focus only on the features that they’re developing, and not on the infrastructure."
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"When you’re switching to this cloud-native model and running everything in containers, you have to make sure that at any moment you can reboot without any downtime and without losing traffic. [With Kubernetes] our infrastructure is much more resilient and we have better availability than before."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Simon Lallemand, Infrastructure Engineer at BlaBlaCar</span>
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<h2>For the 40 million users of <a href="https://www.blablacar.com/">BlaBlaCar</a>, it’s easy to find strangers headed in the same direction to share rides and costs. You can even choose how much "bla bla" chatter you want from a long-distance ride mate.</h2>
Behind the scenes, though, the infrastructure was falling woefully behind the rider community’s exponential growth. Founded in 2006, the company hit its current stride around 2012. "Our infrastructure was very traditional," says Infrastructure Engineer Simon Lallemand, who began working at the company in 2014. "In the beginning, it was a bit chaotic because we had to [grow] fast. But then comes the time when you have to design things to make it manageable."<br><br>
By 2015, the company had about 50 bare metal servers. The team was using a <a href="https://www.mysql.com/">MySQL</a> database and <a href="http://php.net/">PHP</a>, but, Lallemand says, "it was a very static way." They also utilized the configuration management system, <a href="https://www.chef.io/chef/">Chef</a>, but had little automation in its process. "When you’re thinking about doubling the number of servers, you start thinking, ‘What should I do to be more efficient?’" says Lallemand. "The answer is not to hire more and more people just to deal with the servers and installation."<br><br>
Instead, BlaBlaCar began its cloud-native journey but wasn’t sure which route to take. "We could either decide to go into cloud virtualization or even use a private cloud on our own servers," says Lallemand. "But going into the cloud meant we had to make a lot of changes in our application work, and we were just not ready to make the switch from on premise to the cloud." They wanted to keep the great performance they got on bare metal, so they didn’t want to go to virtualization on premise.<br><br>
The solution: containerization. This was early 2015 and containers were still relatively new. "It was a bold move at the time," says Lallemand. "We decided that the next servers that we would buy in the new data center would all be the same model, so we could outsource the maintenance of the servers. And we decided to go with containers and with <a href="https://coreos.com/">CoreOS</a> Container Linux as an abstraction for this hardware. It seemed future-proof to go with containers because we could see what companies were already doing with containers."
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"With all the tooling that we made around the containers, copying a new service is a matter of minutes. It’s a huge gain. For the developers, it means they can focus only on the features that they’re developing and not on the infrastructure or the hour they would test their code, or the hour that it would get deployed."
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Next, they needed to choose a runtime for the containers, but "there were very few deployments in production at that time," says Lallemand. They experimented with <a href="https://www.docker.com/">Docker</a> but decided to go with <a href="https://coreos.com/rkt">rkt</a>. Lallemand explains that for BlaBlaCar, it was "much simpler to integrate things that are on rkt." At the time, the project was still pre-v1.0, so "we could speak with the developers of rkt and give them feedback. It was an advantage." Plus, he notes, rkt was very stable, even at this early stage.<br><br>
Once those decisions were made that summer, the company came up with a plan for implementation. First, they formed a task force to create a workflow that would be tested by three of the 10 members on Lallemand’s team. But they took care to run regular workshops with all 10 members to make sure everyone was on board. "When you’re focused on your product sometimes you forget if it’s really user friendly, whether other people can manage to create containers too," Lallemand says. "So we did a lot of iterations to find a good workflow."<br><br>
After establishing the workflow, Lallemand says with a smile that "we had this strange idea that we should try the most difficult thing first. Because if it works, it will work for everything." So the first project the team decided to containerize was the database. "Nobody did that at the time, and there were really no existing tools for what we wanted to do, including building container images," he says. So the team created their own tools, such as <a href="https://github.com/blablacar/dgr">dgr</a>, which builds container images so that the whole team has a common framework to build on the same images with the same standards. They also revamped the service-discovery tools <a href="https://github.com/airbnb/nerve">Nerve</a> and <a href="http://airbnb.io/projects/synapse/">Synapse</a>; their versions, <a href="https://github.com/blablacar/go-nerve">Go-Nerve</a> and <a href="https://github.com/blablacar/go-synapse">Go-Synapse</a>, were written in Go and built to be more efficient and include new features. All of these tools were open-sourced.<br><br>
At the same time, the company was working to migrate its entire platform to containers with a deadline set for Christmas 2015. With all the work being done in parallel, BlaBlaCar was able to get about 80 percent of its production into containers by its deadline with live traffic running on containers during December. (It’s now at 100 percent.) "It’s a really busy time for traffic," says Lallemand. "We knew that by using those new servers with containers, it would help us handle the traffic."<br><br>
In the middle of that peak season for carpooling, everything worked well. "The biggest impact that we had was for the deployment of new services," says Lallemand. "Before using containers, we had to first deploy a new server and create configurations with Chef. It would take sometimes a day, sometimes two, just to create a new service. And with all the tooling that we made around the containers, copying a new service is a matter of minutes. So it’s really a huge gain. For the developers, it means they can focus only on the features that they’re developing and not on the infrastructure or the hour they would test their code, or the hour that it would get deployed."
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"We realized that there was a really strong community around it [Kubernetes], which meant we would not have to maintain a lot of tools of our own," says Lallemand. "It was better if we could contribute to some bigger project like Kubernetes."
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In order to meet their self-imposed deadline, one of the decisions they made was to not do any "orchestration magic" for containers in the first production alignment. Instead, they used the basic <a href="https://coreos.com/fleet/docs/latest/launching-containers-fleet.html">fleet</a> tool from CoreOS to deploy their containers. (They did build a tool called <a href="https://github.com/blablacar/ggn">GGN</a>, which they’ve open-sourced, to make it more manageable for their system engineers to use.)<br><br>
Still, the team knew that they’d want more orchestration. "Our tool was doing a pretty good job, but at some point you want to give more autonomy to the developer team," Lallemand says. "We also realized that we don’t want to be the single point of contact for developers when they want to launch new services." By the summer of 2016, they found their answer in <a href="http://kubernetes.io/">Kubernetes</a>, which had just begun supporting rkt implementation.<br><br>
After discussing their needs with their contacts at CoreOS and Google, they were convinced that Kubernetes would work for BlaBlaCar. "We realized that there was a really strong community around it, which meant we would not have to maintain a lot of tools of our own," says Lallemand. "It was better if we could contribute to some bigger project like Kubernetes." They also started using <a href="https://prometheus.io/">Prometheus</a>, as they were looking for "service-oriented monitoring that could be updated nightly." Production on Kubernetes began in December 2016. "We like to do crazy stuff around Christmas," he adds with a laugh.<br><br>
BlaBlaCar now has about 3,000 pods, with 1200 of them running on Kubernetes. Lallemand leads a "foundations team" of 25 members who take care of the networks, databases and systems for about 100 developers. There have been some challenges getting to this point. "The rkt implementation is still not 100 percent finished," Lallemand points out. "It’s really good, but there are some features still missing. We have questions about how we do things with stateful services, like databases. We know how we will be migrating some of the services; some of the others are a bit more complicated to deal with. But the Kubernetes community is making a lot of progress on that part."<br><br>
The team is particularly happy that they’re now able to plan capacity better in the company’s data center. "We have fewer constraints since we have this abstraction between the services and the hardware we run on," says Lallemand. "If we lose a server because there’s a hardware problem on it, we just move the containers onto another server. It’s much more efficient. We do that by just changing a line in the configuration file. And with Kubernetes, it should be automatic, so we would have nothing to do."
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"If we lose a server because there’s a hardware problem on it, we just move the containers onto another server. It’s much more efficient. We do that by just changing a line in the configuration file. With Kubernetes, it should be automatic, so we would have nothing to do."
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And these advances ultimately trickle down to BlaBlaCar’s users. "We have improved availability overall on our website," says Lallemand. "When you’re switching to this cloud-native model with running everything in containers, you have to make sure that you can at any moment reboot a server or a data container without any downtime, without losing traffic. So now our infrastructure is much more resilient and we have better availability than before."<br><br>
Within BlaBlaCar’s technology department, the cloud-native journey has created some profound changes. Lallemand thinks that the regular meetings during the conception stage and the training sessions during implementation helped. "After that everybody took part in the migration process," he says. "Then we split the organization into different ‘tribes’—teams that gather developers, product managers, data analysts, all the different jobs, to work on a specific part of the product. Before, they were organized by function. The idea is to give all these tribes access to the infrastructure directly in a self-service way without having to ask. These people are really autonomous. They have responsibility of that part of the product, and they can make decisions faster." <br><br>
This DevOps transformation turned out to be a positive one for the company’s staffers. "The team was very excited about the DevOps transformation because it was new, and we were working to make things more reliable, more future-proof," says Lallemand. "We like doing things that very few people are doing, other than the internet giants." <br><br>
With these changes already making an impact, BlaBlaCar is looking to split up more and more of its application into services. "I don’t say microservices because they’re not so micro," Lallemand says. "If we can split the responsibilities between the development teams, it would be easier to manage and more reliable, because we can easily add and remove services if one fails. You can handle it easily, instead of adding a big monolith that we still have." <br><br>
When Lallemand speaks to other European companies curious about what BlaBlaCar has done with its infrastructure, he tells them to come along for the ride. "I tell them that it’s such a pleasure to deal with the infrastructure that we have today compared to what we had before," he says. "They just need to keep in mind their real motive, whether it’s flexibility in development or reliability or so on, and then go step by step towards reaching those objectives. That’s what we’ve done. It’s important not to do technology for the sake of technology. Do it for a purpose. Our focus was on helping the developers."
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<h1> CASE STUDY: <img src="/images/blackrock_logo.png" class="header_logo"><br>
<div class="subhead">Rolling Out Kubernetes in Production in 100 Days</div>
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Company &nbsp;<b>BlackRock</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>New York, NY</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Financial Services</b>
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<h2>Challenge</h2>
The world’s largest asset manager, <a href="https://www.blackrock.com/investing">BlackRock</a> operates a very controlled static deployment scheme, which has allowed for scalability over the years. But in their data science division, there was a need for more dynamic access to resources. "We want to be able to give every investor access to data science, meaning <a href="https://www.python.org">Python</a> notebooks, or even something much more advanced, like a MapReduce engine based on <a href="https://spark.apache.org">Spark</a>," says Michael Francis, a Managing Director in BlackRock’s Product Group, which runs the company’s investment management platform. "Managing complex Python installations on users’ desktops is really hard because everyone ends up with slightly different environments. We have existing environments that do these things, but we needed to make it real, expansive and scalable. Being able to spin that up on demand, tear it down, make that much more dynamic, became a critical thought process for us. It’s not so much that we had to solve our main core production problem, it’s how do we extend that? How do we evolve?"
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<h2>Solution</h2>
Drawing from what they learned during a pilot done last year using <a href="https://www.docker.com">Docker</a> environments, Francis put together a cross-sectional team of 20 to build an investor research web app using <a href="https://kubernetes.io">Kubernetes</a> with the goal of getting it into production within one quarter.
<br><br>
<h2>Impact</h2>
"Our goal was: How do you give people tools rapidly without having to install them on their desktop?" says Francis. And the team hit the goal within 100 days. Francis is pleased with the results and says, "We’re going to use this infrastructure for lots of other application workloads as time goes on. It’s not just data science; it’s this style of application that needs the dynamism. But I think we’re 6-12 months away from making a [large scale] decision. We need to gain experience of running the system in production, we need to understand failure modes and how best to manage operational issues. What’s interesting is that just having this technology there is changing the way our developers are starting to think about their future development."
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"My message to other enterprises like us is you can actually integrate Kubernetes into an existing, well-orchestrated machinery. You don’t have to throw out everything you do. And using Kubernetes made a complex problem significantly easier."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Michael Francis, Managing Director, BlackRock</span>
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One of the management objectives for BlackRock’s Product Group employees in 2017 was to "build cool stuff." Led by Managing Director Michael Francis, a cross-sectional group of 20 did just that: They rolled out a full production Kubernetes environment and released a new investor research web app on it. In 100 days.<br><br>
For a company that’s the world’s largest asset manager, "just equipment procurement can take 100 days sometimes, let alone from inception to delivery," says Karl Wieman, a Senior System Administrator. "It was an aggressive schedule. But it moved the dial."
In fact, the project achieved two goals: It solved a business problem (creating the needed web app) as well as provided real-world, in-production experience with Kubernetes, a cloud-native technology that the company was eager to explore. "It’s not so much that we had to solve our main core production problem, it’s how do we extend that? How do we evolve?" says Francis. The ultimate success of this project, beyond delivering the app, lies in the fact that "we’ve managed to integrate a radically new thought process into a controlled infrastructure that we didn’t want to change."<br><br>
After all, in its three decades of existence, BlackRock has "a very well-established environment for managing our compute resources," says Francis. "We manage large cluster processes on machines, so we do a lot of orchestration and management for our main production processes in a way that’s very cloudish in concept. We’re able to manage them in a very controlled, static deployment scheme, and that has given us a huge amount of scalability."<br><br>
Though that works well for the core production, the company has found that some data science workloads require more dynamic access to resources. "It’s a very bursty process," says Francis, who is head of data for the company’s Aladdin investment management platform division.<br><br>
Aladdin, which connects the people, information and technology needed for money management in real time, is used internally and is also sold as a platform to other asset managers and insurance companies. "We want to be able to give every investor access to data science, meaning <a href="https://www.python.org">Python</a> notebooks, or even something much more advanced, like a MapReduce engine based on <a href="https://spark.apache.org">Spark</a>," says Francis. But "managing complex Python installations on users’ desktops is really hard because everyone ends up with slightly different environments. Docker allows us to flatten that environment."
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"We manage large cluster processes on machines, so we do a lot of orchestration and management for our main production processes in a way that’s very cloudish in concept. We’re able to manage them in a very controlled, static deployment scheme, and that has given us a huge amount of scalability."
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Still, challenges remain. "If you have a shared cluster, you get this storming herd problem where everyone wants to do the same thing at the same time," says Francis. "You could put limits on it, but you’d have to build an infrastructure to define limits for our processes, and the Python notebooks weren’t really designed for that. We have existing environments that do these things, but we needed to make it real, expansive, and scalable. Being able to spin that up on demand, tear it down, and make that much more dynamic, became a critical thought process for us."<br><br>
Made up of managers from technology, infrastructure, production operations, development and information security, Francis’s team was able to look at the problem holistically and come up with a solution that made sense for BlackRock. "Our initial straw man was that we were going to build everything using <a href="https://www.ansible.com">Ansible</a> and run it all using some completely different distributed environment," says Francis. "That would have been absolutely the wrong thing to do. Had we gone off on our own as the dev team and developed this solution, it would have been a very different product. And it would have been very expensive. We would not have gone down the route of running under our existing orchestration system. Because we don’t understand it. These guys [in operations and infrastructure] understand it. Having the multidisciplinary team allowed us to get to the right solutions and that actually meant we didn’t build anywhere near the amount we thought we were going to end up building."<br><br>
In search of a solution in which they could manage usage on a user-by-user level, Francis’s team gravitated to Red Hat’s <a href="https://www.openshift.com">OpenShift</a> Kubernetes offering. The company had already experimented with other cloud-native environments, but the team liked that Kubernetes was open source, and "we felt the winds were blowing in the direction of Kubernetes long term," says Francis. "Typically we make technology choices that we believe are going to be here in 5-10 years’ time, in some form. And right now, in this space, Kubernetes feels like the one that’s going to be there." Adds Uri Morris, Vice President of Production Operations: "When you see that the non-Google committers to Kubernetes overtook the Google committers, that’s an indicator of the momentum."<br><br>
Once that decision was made, the major challenge was figuring out how to make Kubernetes work within BlackRock’s existing framework. "It’s about understanding how we can operate, manage and support a platform like this, in addition to tacking it onto our existing technology platform," says Project Manager Michael Maskallis. "All the controls we have in place, the change management process, the software development lifecycle, onboarding processes we go through—how can we do all these things?"<br><br>
The first (anticipated) speed bump was working around issues behind BlackRock’s corporate firewalls. "One of our challenges is there are no firewalls in most open source software," says Francis. "So almost all install scripts fail in some bizarre way, and pulling down packages doesn’t necessarily work." The team ran into these types of problems using <a href="https://kubernetes.io/docs/getting-started-guides/minikube/">Minikube</a> and did a few small pushes back to the open source project.
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"Typically we make technology choices that we believe are going to be here in 5-10 years’ time, in some form. And right now, in this space, Kubernetes feels like the one that’s going to be there."
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There were also questions about service discovery. "You can think of Aladdin as a cloud of services with APIs between them that allows us to build applications rapidly," says Francis. "It’s all on a proprietary message bus, which gives us all sorts of advantages but at the same time, how does that play in a third party [platform]?"<br><br>
Another issue they had to navigate was that in BlackRock’s existing system, the messaging protocol has different instances in the different development, test and production environments. While Kubernetes enables a more DevOps-style model, it didn’t make sense for BlackRock. "I think what we are very proud of is that the ability for us to push into production is still incredibly rapid in this [new] infrastructure, but we have the control points in place, and we didn’t have to disrupt everything," says Francis. "A lot of the cost of this development was thinking how best to leverage our internal tools. So it was less costly than we actually thought it was going to be."<br><br>
The project leveraged tools associated with the messaging bus, for example. "The way that the Kubernetes cluster will talk to our internal messaging platform is through a gateway program, and this gateway program already has built-in checks and throttles," says Morris. "We can use them to control and potentially throttle the requests coming in from Kubernetes’s very elastic infrastructure to the production infrastructure. We’ll continue to go in that direction. It enables us to scale as we need to from the operational perspective."<br><br>
The solution also had to be complementary with BlackRock’s centralized operational support team structure. "The core infrastructure components of Kubernetes are hooked into our existing orchestration framework, which means that anyone in our support team has both control and visibility to the cluster using the existing operational tools," Morris explains. "That means that I don’t need to hire more people."<br><br>
With those points established, the team created a procedure for the project: "We rolled this out first to a development environment, then moved on to a testing environment and then eventually to two production environments, in that sequential order," says Maskallis. "That drove a lot of our learning curve. We have all these moving parts, the software components on the infrastructure side, the software components with Kubernetes directly, the interconnectivity with the rest of the environment that we operate here at BlackRock, and how we connect all these pieces. If we came across issues, we fixed them, and then moved on to the different environments to replicate that until we eventually ended up in our production environment where this particular cluster is supposed to live."<br><br>
The team had weekly one-hour working sessions with all the members (who are located around the world) participating, and smaller breakout or deep-dive meetings focusing on specific technical details. Possible solutions would be reported back to the group and debated the following week. "I think what made it a successful experiment was people had to work to learn, and they shared their experiences with others," says Vice President and Software Developer Fouad Semaan. Then, Francis says, "We gave our engineers the space to do what they’re good at. This hasn’t been top-down."
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"The core infrastructure components of Kubernetes are hooked into our existing orchestration framework, which means that anyone in our support team has both control and visibility to the cluster using the existing operational tools. That means that I don’t need to hire more people."
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They were led by one key axiom: To stay focused and avoid scope creep. This meant that they wouldn’t use features that weren’t in the core of Kubernetes and Docker. But if there was a real need, they’d build the features themselves. Luckily, Francis says, "Because of the rapidity of the development, a lot of things we thought we would have to build ourselves have been rolled into the core product. [The package manager<a href="https://helm.sh"> Helm</a> is one example]. People have similar problems."<br><br>
By the end of the 100 days, the app was up and running for internal BlackRock users. The initial capacity of 30 users was hit within hours, and quickly increased to 150. "People were immediately all over it," says Francis. In the next phase of this project, they are planning to scale up the cluster to have more capacity.<br><br>
Even more importantly, they now have in-production experience with Kubernetes that they can continue to build on—and a complete framework for rolling out new applications. "We’re going to use this infrastructure for lots of other application workloads as time goes on. It’s not just data science; it’s this style of application that needs the dynamism," says Francis. "Is it the right place to move our core production processes onto? It might be. We’re not at a point where we can say yes or no, but we felt that having real production experience with something like Kubernetes at some form and scale would allow us to understand that. I think we’re 6-12 months away from making a [large scale] decision. We need to gain experience of running the system in production, we need to understand failure modes and how best to manage operational issues."<br><br>
For other big companies considering a project like this, Francis says commitment and dedication are key: "We got the signoff from [senior management] from day one, with the commitment that we were able to get the right people. If I had to isolate what makes something complex like this succeed, I would say senior hands-on people who can actually drive it make a huge difference." With that in place, he adds, "My message to other enterprises like us is you can actually integrate Kubernetes into an existing, well-orchestrated machinery. You don’t have to throw out everything you do. And using Kubernetes made a complex problem significantly easier."
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<h1>CASE STUDY: <img src="/images/box_logo.png" width="10%" style="margin-bottom:-6px"><br>
<div class="subhead">An Early Adopter Envisions
a New Cloud Platform</div>
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Company &nbsp;<b>Box</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Redwood City, California</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Technology</b>
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<h2>Challenge</h2>
Founded in 2005, the enterprise content management company allows its more than 50 million users to manage content in the cloud. <a href="https://www.box.com/home">Box</a> was built primarily with bare metal inside the company’s own data centers, with a monolithic PHP code base. As the company was expanding globally, it needed to focus on "how we run our workload across many different cloud infrastructures from bare metal to public cloud," says Sam Ghods, Cofounder and Services Architect of Box. "It’s been a huge challenge because of different clouds, especially bare metal, have very different interfaces."
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<h2>Solution</h2>
Over the past couple of years, Box has been decomposing its infrastructure into microservices, and became an early adopter of, as well as contributor to, <a href="http://kubernetes.io/">Kubernetes</a> container orchestration. Kubernetes, Ghods says, has allowed Box’s developers to "target a universal set of concepts that are portable across all clouds."<br><br>
<h2>Impact</h2>
"Before Kubernetes," Ghods says, "our infrastructure was so antiquated it was taking us more than six months to deploy a new microservice. Today, a new microservice takes less than five days to deploy. And we’re working on getting it to an hour."
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"We looked at a lot of different options, but Kubernetes really stood out....the fact that on day one it was designed to run on bare metal just as well as Google Cloud meant that we could actually migrate to it inside of our data centers, and then use those same tools and concepts to run across public cloud providers as&nbsp;well."<br><br><span style="font-size:15px;letter-spacing:0.08em">- SAM GHOUDS, CO-FOUNDER AND SERVICES ARCHITECT OF BOX</span>
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<h2>In the summer of 2014, Box was feeling the pain of a decade’s worth of hardware and software infrastructure that wasn’t keeping up with the company’s needs.</h2>
A platform that allows its more than 50 million users (including governments and big businesses like <a href="https://www.ge.com/">General Electric</a>) to manage and share content in the cloud, Box was originally a <a href="http://php.net/">PHP</a> monolith of millions of lines of code built exclusively with bare metal inside of its own data centers. It had already begun to slowly chip away at the monolith, decomposing it into microservices. And "as we’ve been expanding into regions around the globe, and as the public cloud wars have been heating up, we’ve been focusing a lot more on figuring out how we run our workload across many different environments and many different cloud infrastructure providers," says Box Cofounder and Services Architect Sam Ghods. "It’s been a huge challenge thus far because of all these different providers, especially bare metal, have very different interfaces and ways in which you work with them."<br><br>
Box’s cloud native journey accelerated that June, when Ghods attended <a href="https://www.docker.com/events/dockercon">DockerCon</a>. The company had come to the realization that it could no longer run its applications only off bare metal, and was researching containerizing with Docker, virtualizing with OpenStack, and supporting public cloud.<br><br>
At that conference, Google announced the release of its Kubernetes container management system, and Ghods was won over. "We looked at a lot of different options, but Kubernetes really stood out, especially because of the incredibly strong team of <a href="https://research.google.com/pubs/pub43438.html">Borg</a> veterans and the vision of having a completely infrastructure-agnostic way of being able to run cloud software," he says, referencing Google’s internal container orchestrator Borg. "The fact that on day one it was designed to run on bare metal just as well as <a href="https://cloud.google.com/">Google Cloud</a> meant that we could actually migrate to it inside of our data centers, and then use those same tools and concepts to run across public cloud providers as well."<br><br>
Another plus: Ghods liked that <a href="https://kubernetes.io/">Kubernetes</a> has a universal set of API objects like pod, service, replica set and deployment object, which created a consistent surface to build tooling against. "Even PaaS layers like <a href="https://www.openshift.com/">OpenShift</a> or <a href="http://deis.io/">Deis</a> that build on top of Kubernetes still treat those objects as first-class principles," he says. "We were excited about having these abstractions shared across the entire ecosystem, which would result in a lot more momentum than we saw in other potential solutions."<br><br>
Box deployed Kubernetes in a cluster in a production data center just six months later. Kubernetes was then still pre-beta, on version 0.11. They started small: The very first thing Ghods’s team ran on Kubernetes was a Box API checker that confirms Box is up. "That was just to write and deploy some software to get the whole pipeline functioning," he says. Next came some daemons that process jobs, which was "nice and safe because if they experienced any interruptions, we wouldn’t fail synchronous incoming requests from customers."
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"As we’ve been expanding into regions around the globe, and as the public cloud wars have been heating up, we’ve been focusing a lot more on figuring out how we [can have Kubernetes help] run our workload across many different environments and many different cloud infrastructure providers."
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The first live service, which the team could route to and ask for information, was launched a few months later. At that point, Ghods says, "We were comfortable with the stability of the Kubernetes cluster. We started to port some services over, then we would increase the cluster size and port a few more, and that’s ended up to about 100 servers in each data center that are dedicated purely to Kubernetes. And that’s going to be expanding a lot over the next 12 months, probably too many hundreds if not thousands."<br><br>
While observing teams who began to use Kubernetes for their microservices, "we immediately saw an uptick in the number of microservices being released," Ghods&nbsp;notes. "There was clearly a pent-up demand for a better way of building software through microservices, and the increase in agility helped our developers be more productive and make better architectural choices."
<br><br><div class="quote">"There was clearly a pent-up demand for a better way of building software through microservices, and the increase in agility helped our developers be more productive and make better architectural choices."</div><br>
Ghods reflects that as early adopters, Box had a different journey from what companies experience now. "We were definitely lock step with waiting for certain things to stabilize or features to get released," he says. "In the early days we were doing a lot of contributions [to components such as kubectl apply] and waiting for Kubernetes to release each of them, and then we’d upgrade, contribute more, and go back and forth several times. The entire project took about 18 months from our first real deployment on Kubernetes to having general availability. If we did that exact same thing today, it would probably be no more than six."<br><br>
In any case, Box didn’t have to make too many modifications to Kubernetes for it to work for the company. "The vast majority of the work our team has done to implement Kubernetes at Box has been making it work inside of our existing (and often legacy) infrastructure," says Ghods, "such as upgrading our base operating system from RHEL6 to RHEL7 or integrating it into <a href="https://www.nagios.org/">Nagios</a>, our monitoring infrastructure. But overall Kubernetes has been remarkably flexible with fitting into many of our constraints, and we’ve been running it very successfully on our bare metal infrastructure."<br><br>
Perhaps the bigger challenge for Box was a cultural one. "Kubernetes, and cloud native in general, represents a pretty big paradigm shift, and it’s not very incremental," Ghods says. "We’re essentially making this pitch that Kubernetes is going to solve everything because it does things the right way and everything is just suddenly better. But it’s important to keep in mind that it’s not nearly as proven as many other solutions out there. You can’t say how long this or that company took to do it because there just aren’t that many yet. Our team had to really fight for resources because our project was a bit of a moonshot."
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"The vast majority of the work our team has done to implement Kubernetes at Box has been making it work inside of our existing [and often legacy] infrastructure....overall Kubernetes has been remarkably flexible with fitting into many of our constraints, and we’ve been running it very successfully on our bare metal infrastructure."
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Having learned from experience, Ghods offers these two pieces of advice for companies going through similar challenges:
<h2>1. Deliver early and often.</h2> Service discovery was a huge problem for Box, and the team had to decide whether to build an interim solution or wait for Kubernetes to natively satisfy Box’s unique requirements. After much debate, "we just started focusing on delivering something that works, and then dealing with potentially migrating to a more native solution later," Ghods says. "The above-all-else target for the team should always be to serve real production use cases on the infrastructure, no matter how trivial. This helps keep the momentum going both for the team itself and for the organizational perception of the project." </br></br>
<h2>2. Keep an open mind about what your company has to abstract away from developers and what it&nbsp;doesn’t.</h2> Early on, the team built an abstraction on top of Docker files to help ensure that images had the right security updates.
This turned out to be superfluous work, since container images are considered immutable and you can easily scan them post-build to ensure they do not contain vulnerabilities. Because managing infrastructure through containerization is such a discontinuous leap, it’s better to start by interacting directly with the native tools and learning their unique advantages and caveats. An abstraction should be built only after a practical need for it arises.</br></br>
In the end, the impact has been powerful. "Before Kubernetes," Ghods says, "our infrastructure was so antiquated it was taking us more than six months to deploy a new microservice. Now a new microservice takes less than five days to deploy. And we’re working on getting it to an hour. Granted, much of that six months was due to how broken our systems were, but bare metal is intrinsically a difficult platform to support unless you have a system like Kubernetes to help manage&nbsp;it."</br></br>
By Ghods’s estimate, Box is still several years away from his goal of being a 90-plus percent Kubernetes shop. "We’re very far along on having a mission-critical, stable Kubernetes deployment that provides a lot of value," he says. "Right now about five percent of all of our compute runs on Kubernetes, and I think in the next six months we’ll likely be between 20 to 50 percent. We’re working hard on enabling all stateless service use cases, and shift our focus to stateful services after&nbsp;that."
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"Ghods predicts that Kubernetes has the opportunity to be the new cloud platform. '...because it’s a never-before-seen level of automation and intelligence surrounding infrastructure that is portable and agnostic to every way you can run your infrastructure.'"
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In fact, that’s what he envisions across the industry: Ghods predicts that Kubernetes has the opportunity to be the new cloud platform. Kubernetes provides an API consistent across different cloud platforms including bare metal, and "I don’t think people have seen the full potential of what’s possible when you can program against one single interface," he says. "The same way <a href="https://aws.amazon.com/">AWS</a> changed infrastructure so that you don’t have to think about servers or cabinets or networking equipment anymore, Kubernetes enables you to focus exclusively on the containers that you’re running, which is pretty exciting. That’s the vision."</br></br>
Ghods points to projects that are already in development or recently released for Kubernetes as a cloud platform: cluster federation, the Dashboard UI, and <a href="https://coreos.com/">CoreOS</a>’s etcd operator. "I honestly believe it’s the most exciting thing I’ve seen in cloud infrastructure," he says, "because it’s a never-before-seen level of automation and intelligence surrounding infrastructure that is portable and agnostic to every way you can run your infrastructure."</br></br>
Box, with its early decision to use bare metal, embarked on its Kubernetes journey out of necessity. But Ghods says that even if companies don’t have to be agnostic about cloud providers today, Kubernetes may soon become the industry standard, as more and more tooling and extensions are built around the API.</br></br>
"The same way it doesn’t make sense to deviate from Linux because it’s such a standard," Ghods says, "I think Kubernetes is going down the same path. It is still early days—the documentation still needs work and the user experience for writing and publishing specs to the Kubernetes clusters is still rough. When you’re on the cutting edge you can expect to bleed a little. But the bottom line is, this is where the industry is going. Three to five years from now it’s really going to be shocking if you run your infrastructure any other way."
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<h1>CASE STUDY: <img src="/images/buffer.png" width="18%" style="margin-bottom:-5px;margin-left:10px;"><br>
<div class="subhead">Making Deployments Easy for a Small, Distributed Team</div>
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Company&nbsp;<b>Buffer</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Around the World</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Social Media Technology</b>
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<h2>Challenge</h2>
With a small but fully distributed team of 80 working across almost a dozen time zones, Buffer—which offers social media management to agencies and marketers—was looking to solve its "classic monolithic code base problem," says Architect Dan Farrelly. "We wanted to have the kind of liquid infrastructure where a developer could create an app and deploy it and scale it horizontally as&nbsp;necessary."
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<h2>Solution</h2>
Embracing containerization, Buffer moved its infrastructure from Amazon Web Services’ Elastic Beanstalk to Docker on AWS, orchestrated with&nbsp;Kubernetes.
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<h2>Impact</h2>
The new system "leveled up our ability with deployment and rolling out new changes," says Farrelly. "Building something on your computer and knowing that it’s going to work has shortened things up a lot. Our feedback cycles are a lot faster now&nbsp;too."
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"It’s amazing that we can use the Kubernetes solution off the shelf with our team. And it just keeps getting better. Before we even know that we need something, it’s there in the next release or it’s coming in the next few months."<br><br><span style="font-size:16px;letter-spacing:2px;">- DAN FARRELLY, BUFFER ARCHITECT</span>
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<h2>Dan Farrelly uses a carpentry analogy to explain the problem his company, <a href="https://buffer.com">Buffer</a>, began having as its team of developers grew over the past few years.</h2>
"If you’re building a table by yourself, it’s fine," the company’s architect says. "If you bring in a second person to work on the table, maybe that person can start sanding the legs while you’re sanding the top. But when you bring a third or fourth person in, someone should probably work on a different table." Needing to work on more and more different tables led Buffer on a path toward microservices and containerization made possible by Kubernetes.<br><br>
Since around 2012, Buffer had already been using <a href="https://aws.amazon.com/elasticbeanstalk/">Elastic Beanstalk</a>, the orchestration service for deploying infrastructure offered by <a href="https://aws.amazon.com">Amazon Web Services</a>. "We were deploying a single monolithic <a href="http://php.net/manual/en/intro-whatis.php">PHP</a> application, and it was the same application across five or six environments," says Farrelly. "We were very much a product-driven company. It was all about shipping new features quickly and getting things out the door, and if something was not broken, we didn’t spend too much time on it. If things were getting a little bit slow, we’d maybe use a faster server or just scale up one instance, and it would be good enough. We’d move on."<br><br>
But things came to a head in 2016. With the growing number of committers on staff, Farrelly and Buffer’s then-CTO, Sunil Sadasivan, decided it was time to re-architect and rethink their infrastructure. "It was a classic monolithic code base problem," says Farrelly.<br><br>Some of the company’s team was already successfully using <a href="https://www.docker.com">Docker</a> in their development environment, but the only application running on Docker in production was a marketing website that didn’t see real user traffic. They wanted to go further with Docker, and the next step was looking at options for&nbsp;orchestration.
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And all the things Kubernetes did well suited Buffer’s needs. "We wanted to have the kind of liquid infrastructure where a developer could create an app and deploy it and scale it horizontally as necessary," says Farrelly. "We quickly used some scripts to set up a couple of test clusters, we built some small proof-of-concept applications in containers, and we deployed things within an hour. We had very little experience in running containers in production. It was amazing how quickly we could get a handle on it&nbsp;[Kubernetes]."
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First they considered <a href="https://mesosphere.com">Mesosphere</a>, <a href="https://dcos.io">DC/OS</a> and <a href="https://aws.amazon.com/ecs/">Amazon Elastic Container Service</a> (which their data systems team was already using for some data pipeline jobs). While they were impressed by these offerings, they ultimately went with Kubernetes. "We run on AWS still, so spinning up, creating services and creating load balancers on demand for us without having to configure them manually was a great way for our team to get into this," says Farrelly. "We didn’t need to figure out how to configure this or that, especially coming from a former Elastic Beanstalk environment that gave us an automatically-configured load balancer. I really liked Kubernetes’ controls of the command line. It just took care of ports. It was a lot more flexible. Kubernetes was designed for doing what it does, so it does it very well."<br><br>
And all the things Kubernetes did well suited Buffer’s needs. "We wanted to have the kind of liquid infrastructure where a developer could create an app and deploy it and scale it horizontally as necessary," says Farrelly. "We quickly used some scripts to set up a couple of test clusters, we built some small proof-of-concept applications in containers, and we deployed things within an hour. We had very little experience in running containers in production. It was amazing how quickly we could get a handle on it [Kubernetes]."<br><br>
Above all, it provided a powerful solution for one of the company’s most distinguishing characteristics: their remote team that’s spread across a dozen different time zones. "The people with deep knowledge of our infrastructure live in time zones different from our peak traffic time zones, and most of our product engineers live in other places," says Farrelly. "So we really wanted something where anybody could get a grasp of the system early on and utilize it, and not have to worry that the deploy engineer is asleep. Otherwise people would sit around for 12 to 24 hours for something. It’s been really cool to see people moving much faster."
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With a relatively small engineering team—just 25 people, and only a handful working on infrastructure, with the majority front-end developers—Buffer needed "something robust for them to deploy whatever they wanted," says Farrelly. Before, "it was only a couple of people who knew how to set up everything in the old way. With this system, it was easy to review documentation and get something out extremely quickly. It lowers the bar for us to get everything in production. We don't have the big team to build all these tools or manage the infrastructure like other larger companies&nbsp;might."
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"In our old way of working, the feedback loop was a lot longer, and it was delicate because if you deployed something, the risk was high to potentially break something else," Farrelly says. "With the kind of deploys that we built around Kubernetes, we were able to detect bugs and fix them, and get them deployed super fast. The second someone is fixing [a bug], it’s out the&nbsp;door."
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To help with this, Buffer developers wrote a deploy bot that wraps the Kubernetes deploy process and can be used by every team. "Before, our data analysts would update, say, a <a href="https://www.python.org">Python</a> analysis script and have to wait for the lead on that team to click the button and deploy it," Farrelly explains. "Now our data analysts can make a change, enter a <a href="https://slack.com">Slack</a> command, ‘/deploy,’ and it goes out instantly. They don’t need to wait on these slow turnaround times. They don’t even know where it’s running; it doesn’t matter."
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One of the first applications the team built from scratch using Kubernetes was a new image resizing service. As a social media management tool that allows marketing teams to collaborate on posts and send updates across multiple social media profiles and networks, Buffer has to be able to resize photographs as needed to meet the varying limitations of size and format posed by different social networks. "We always had these hacked together solutions," says Farrelly.
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To create this new service, one of the senior product engineers was assigned to learn Docker and Kubernetes, then build the service, test it, deploy it and monitor it—which he was able to do relatively quickly. "In our old way of working, the feedback loop was a lot longer, and it was delicate because if you deployed something, the risk was high to potentially break something else," Farrelly says. "With the kind of deploys that we built around Kubernetes, we were able to detect bugs and fix them, and get them deployed super fast. The second someone is fixing [a bug], it’s out the door."
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Plus, unlike with their old system, they could scale things horizontally with one command. "As we rolled it out," Farrelly says, "we could anticipate and just click a button. This allowed us to deal with the demand that our users were placing on the system and easily scale it to handle it."
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Another thing they weren’t able to do before was a canary deploy. This new capability "made us so much more confident in deploying big changes," says Farrelly. "Before, it took a lot of testing, which is still good, but it was also a lot of ‘fingers crossed.’ And this is something that gets run 800,000 times a day, the core of our business. If it doesn’t work, our business doesn’t work. In a Kubernetes world, I can do a canary deploy to test it for 1 percent and I can shut it down very quickly if it isn’t working. This has leveled up our ability to deploy and roll out new changes quickly while reducing&nbsp;risk."
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"If you want to run containers in production, with nearly the power that Google uses internally, this [Kubernetes] is a great way to do that," Farrelly says. "We’re a relatively small team that’s actually running Kubernetes, and we’ve never run anything like it before. So it’s more approachable than you might think. That’s the one big thing that I tell people who are experimenting with it. Pick a couple of things, roll it out, kick the tires on this for a couple of months and see how much it can handle. You start learning a lot this&nbsp;way."
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By October 2016, 54 percent of Buffer’s traffic was going through their Kubernetes cluster. "There’s a lot of our legacy functionality that still runs alright, and those parts might move to Kubernetes or stay in our old setup forever," says Farrelly. But the company made the commitment at that time that going forward, "all new development, all new features, will be running on Kubernetes."
<br><br>
The plan for 2017 is to move all the legacy applications to a new Kubernetes cluster, and run everything they’ve pulled out of their old infrastructure, plus the new services they’re developing in Kubernetes, on another cluster. "I want to bring all the benefits that we’ve seen on our early services to everyone on the team," says Farrelly.
<br><br>
<h2>For Buffer’s engineers, it’s an exciting process. "Every time we’re deploying a new service, we need to figure out: OK, what’s the architecture? How do these services communicate? What’s the best way to build this service?" Farrelly says. "And then we use the different features that Kubernetes has to glue all the pieces together. It’s enabling us to experiment as we’re learning how to design a service-oriented architecture. Before, we just wouldn’t have been able to do it. This is actually giving us a blank white board so we can do whatever we want on it."
</h2>
Part of that blank slate is the flexibility that Kubernetes offers should the time come when Buffer may want or need to change its cloud. "It’s cloud agnostic so maybe one day we could switch to Google or somewhere else," Farrelly says. "We’re very deep in Amazon but it’s nice to know we could move away if we need to."
<br><br>
At this point, the team at Buffer can’t imagine running their infrastructure any other way—and they’re happy to spread the word. "If you want to run containers in production, with nearly the power that Google uses internally, this [Kubernetes] is a great way to do that," Farrelly says. "We’re a relatively small team that’s actually running Kubernetes, and we’ve never run anything like it before. So it’s more approachable than you might think. That’s the one big thing that I tell people who are experimenting with it. Pick a couple of things, roll it out, kick the tires on this for a couple of months and see how much it can handle. You start learning a lot this&nbsp;way."
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<h1> CASE STUDY:<img src="/images/crowdfire_logo.png" class="header_logo"><br> <div class="subhead">How to Keep Iterating a Fast-Growing App With a Cloud-Native Approach</div></h1>
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<div class="details">
Company &nbsp;<b>Crowdfire</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Mumbai, India</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Social Media Software</b>
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<h2>Challenge</h2>
<a href="https://www.crowdfireapp.com/">Crowdfire</a> helps content creators create their content anywhere on the Internet and publish it everywhere else in the right format. Since its launch in 2010, it has grown to 16 million users. The product began as a monolith app running on <a href="https://cloud.google.com/appengine/">Google App Engine</a>, and in 2015, the company began a transformation to microservices running on Amazon Web Services <a href="https://aws.amazon.com/elasticbeanstalk/">Elastic Beanstalk</a>. "It was okay for our use cases initially, but as the number of services, development teams and scale increased, the deploy times, self-healing capabilities and resource utilization started to become problems for us," says Software Engineer Amanpreet Singh, who leads the infrastructure team for Crowdfire.<br>
<h2>Solution</h2>
"We realized that we needed a more cloud-native approach to deal with these issues," says Singh. The team decided to implement a custom setup of Kubernetes based on <a href="https://www.terraform.io/">Terraform</a> and <a href="https://www.ansible.com/">Ansible</a>.
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<h2>Impact</h2>
"Kubernetes has helped us reduce the deployment time from 15 minutes to less than a minute," says Singh. "Due to Kubernetes’s self-healing nature, the operations team doesn’t need to do any manual intervention in case of a node or pod failure." Plus, he says, "Dev-Prod parity has improved since developers can experiment with options in dev/staging clusters, and when it’s finalized, they just commit the config changes in the respective code repositories. These changes automatically get replicated on the production cluster via CI/CD pipelines."
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"In the 15 months that we’ve been using Kubernetes, it has been amazing for us. It enabled us to iterate quickly, increase development speed, and continuously deliver new features and bug fixes to our users, while keeping our operational costs and infrastructure management overhead under control."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Amanpreet Singh, Software Engineer at Crowdfire</span>
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<h2>"If you build it, they will come."</h2>
For most content creators, only half of that movie quote may ring true. Sure, platforms like Wordpress, YouTube and Shopify have made it simple for almost anyone to start publishing new content online, but attracting an audience isn’t as easy. Crowdfire "helps users publish their content to all possible places where their audience exists," says Amanpreet Singh, a Software Engineer at the company based in Mumbai, India. Crowdfire has gained more than 16 million users—from bloggers and artists to makers and small businesses—since its launch in 2010.<br><br>
With that kind of growth—and a high demand from users for new features and continuous improvements—the Crowdfire team struggled to keep up behind the scenes. In 2015, they moved their monolith Java application to Amazon Web Services <a href="https://aws.amazon.com/elasticbeanstalk/">Elastic Beanstalk</a> and started breaking it down into microservices.<br><br>
It was a good first step, but the team soon realized they needed to go further down the cloud-native path, which would lead them to Kubernetes. "It was okay for our use cases initially, but as the number of services and development teams increased and we scaled further, deploy times, self-healing capabilities and resource utilization started to become problematic," says Singh, who leads the infrastructure team at Crowdfire. "We realized that we needed a more cloud-native approach to deal with these issues."<br><br>
As he looked around for solutions, Singh had a checklist of what Crowdfire needed. "We wanted to keep some things separate so they could be shipped independent of other things; this would help remove blockers and let different teams work at their own pace," he says. "We also make a lot of data-driven decisions, so shipping a feature and its iterations quickly was a must."<br><br>
Kubernetes checked all the boxes and then some. "One of the best things was the built-in service discovery," he says. "When you have a bunch of microservices that need to call each other, having internal DNS readily available and service IPs and ports automatically set as environment variables help a lot." Plus, he adds, "Kubernetes’s opinionated approach made it easier to get started."
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"We realized that we needed a more cloud-native approach to deal with these issues," says Singh. The team decided to implement a custom setup of Kubernetes based on Terraform and Ansible."
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There was another compelling business reason for the cloud-native approach. "In today’s world of ever-changing business requirements, using cloud native technology provides a variety of options to choose from—even the ability to run services in a hybrid cloud environment," says Singh. "Businesses can keep services in a region closest to the users, and thus benefit from high-availability and resiliency."<br><br>
So in February 2016, Singh set up a test Kubernetes cluster using the kube-up scripts provided. "I explored the features and was able to deploy an application pretty easily," he says. "However, it seemed like a black box since I didn’t understand the components completely, and had no idea what the kube-up script did under the hood. So when it broke, it was hard to find the issue and fix it." <br><br>
To get a better understanding, Singh dove into the internals of Kubernetes, reading the docs and even some of the code. And he looked to the Kubernetes community for more insight. "I used to stay up a little late every night (a lot of users were active only when it’s night here in India) and would try to answer questions on the Kubernetes community Slack from users who were getting started," he says. "I would also follow other conversations closely. I must admit I was able to avoid a lot of issues in our setup because I knew others had faced the same issues."<br><br>
Based on the knowledge he gained, Singh decided to implement a custom setup of Kubernetes based on <a href="https://www.terraform.io/">Terraform</a> and <a href="https://www.ansible.com/">Ansible</a>. "I wrote Terraform to launch Kubernetes master and nodes (Auto Scaling Groups) and an Ansible playbook to install the required components," he says. (The company recently switched to using prebaked <a href="http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html">AMIs</a> to make the node bringup faster, and is planning to change its networking layer.) <br><br>
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"Kubernetes helped us reduce the deployment time from 15 minutes to less than a minute. Due to Kubernetes’s self-healing nature, the operations team doesn’t need to do any manual intervention in case of a node or pod failure."
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First, the team migrated a few staging services from Elastic Beanstalk to the new Kubernetes staging cluster, and then set up a production cluster a month later to deploy some services. The results were convincing. "By the end of March 2016, we established that all the new services must be deployed on Kubernetes," says Singh. "Kubernetes helped us reduce the deployment time from 15 minutes to less than a minute. Due to Kubernetes’s self-healing nature, the operations team doesn’t need to do any manual intervention in case of a node or pod failure." On top of that, he says, "Dev-Prod parity has improved since developers can experiment with options in dev/staging clusters, and when it’s finalized, they just commit the config changes in the respective code repositories. These changes automatically get replicated on the production cluster via CI/CD pipelines. This brings more visibility into the changes being made, and keeping an audit trail."<br><br>
Over the next six months, the team worked on migrating all the services from Elastic Beanstalk to Kubernetes, except for the few that were deprecated and would soon be terminated anyway. The services were moved one at a time, and their performance was monitored for two to three days each. Today, "We’re completely migrated and we run all new services on Kubernetes," says Singh. <br><br>
The impact has been considerable: With Kubernetes, the company has experienced a 90% cost savings on Elastic Load Balancer, which is now only used for their public, user-facing services. Their EC2 operating expenses have been decreased by as much as 50%.<br><br>
All 30 engineers at Crowdfire were onboarded at once. "I gave an internal talk where I shared the basic components and demoed the usage of kubectl," says Singh. "Everyone was excited and happy about using Kubernetes. Developers have more control and visibility into their applications running in production now. Most of all, they’re happy with the low deploy times and self-healing services." <br><br>
And they’re much more productive, too. "Where we used to do about 5 deployments per day," says Singh, "now we’re doing 30+ production and 50+ staging deployments almost every day."
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The impact has been considerable: With Kubernetes, the company has experienced a 90% cost savings on Elastic Load Balancer, which is now only used for their public, user-facing services. Their EC2 operating expenses have been decreased by as much as 50%.
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Singh notes that almost all of the engineers interact with the staging cluster on a daily basis, and that has created a cultural change at Crowdfire. "Developers are more aware of the cloud infrastructure now," he says. "They’ve started following cloud best practices like better health checks, structured logs to stdout [standard output], and config via files or environment variables."<br><br>
With Crowdfire’s commitment to Kubernetes, Singh is looking to expand the company’s cloud-native stack. The team already uses <a href="https://prometheus.io/">Prometheus</a> for monitoring, and he says he is evaluating <a href="https://linkerd.io/">Linkerd</a> and <a href="https://envoyproxy.github.io/">Envoy Proxy</a> as a way to "get more metrics about request latencies and failures, and handle them better." Other CNCF projects, including <a href="http://opentracing.io/">OpenTracing</a> and <a href="https://grpc.io/">gRPC</a> are also on his radar.<br><br>
Singh has found that the cloud-native community is growing in India, too, particularly in Bangalore. "A lot of startups and new companies are starting to run their infrastructure on Kubernetes," he says. <br><br>
And when people ask him about Crowdfire’s experience, he has this advice to offer: "Kubernetes is a great piece of technology, but it might not be right for you, especially if you have just one or two services or your app isn’t easy to run in a containerized environment," he says. "Assess your situation and the value that Kubernetes provides before going all in. If you do decide to use Kubernetes, make sure you understand the components that run under the hood and what role they play in smoothly running the cluster. Another thing to consider is if your apps are ‘Kubernetes-ready,’ meaning if they have proper health checks and handle termination signals to shut down gracefully."<br><br>
And if your company fits that profile, go for it. Crowdfire clearly did—and is now reaping the benefits. "In the 15 months that we’ve been using Kubernetes, it has been amazing for us," says Singh. "It enabled us to iterate quickly, increase development speed and continuously deliver new features and bug fixes to our users, while keeping our operational costs and infrastructure management overhead under control."
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<h1>CASE STUDY: <img src="/images/golfnow_logo.png" width="20%" style="margin-bottom:-6px"><br>
<div class="subhead">Saving Time and Money with Cloud Native Infrastructure</div>
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Company&nbsp;<b>GolfNow</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location&nbsp;<b>Orlando, Florida</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry&nbsp;<b>Golf Industry Technology and Services Provider</b>
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<h2>Challenge</h2>
A member of the <a href="http://www.nbcunicareers.com/our-businesses/nbc-sports-group">NBC Sports Group</a>, <a href="https://www.golfnow.com/">GolfNow</a> is the golf industry’s technology and services leader, managing 10 different products, as well as the largest e-commerce tee time marketplace in the world. As its business began expanding rapidly and globally, GolfNow’s monolithic application became problematic. "We kept growing our infrastructure vertically rather than horizontally, and the cost of doing business became problematic," says Sheriff Mohamed, GolfNow’s Director, Architecture. "We wanted the ability to more easily expand globally."
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<h2>Solution</h2>
Turning to microservices and containerization, GolfNow began moving its applications and databases from third-party services to its own clusters running on <a href="https://www.docker.com/">Docker</a> and <a href="http://kubernetes.io/">Kubernetes.</a><br><br>
<h2>Impact</h2>
The results were immediate. While maintaining the same capacity—and beyond, during peak periods—GolfNow saw its infrastructure costs for the first application virtually cut in half.
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"With our growth we obviously needed to expand our infrastructure, and we kept growing vertically rather than horizontally. We were basically wasting money and doubling the cost of our infrastructure."<br><br><span style="font-size:15px;letter-spacing:0.08em">- SHERIFF MOHAMED, DIRECTOR, ARCHITECTURE AT GOLFNOW</span>
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<h2>It’s not every day that you can say you’ve slashed an operating expense by half.</h2>
But Sheriff Mohamed and Josh Chandler did just that when they helped lead their company, <a href="https://www.golfnow.com/">GolfNow</a>, on a journey from a monolithic to a containerized, cloud native infrastructure managed by Kubernetes.
<br> <br>
A top-performing business within the NBC Sports Group, GolfNow is a technology and services company with the largest tee time marketplace in the world. GolfNow serves 5 million active golfers across 10 different products. In recent years, the business had grown so fast that the infrastructure supporting their giant monolithic application (written in C#.NET and backed by SQL Server database management system) could not keep up. "With our growth we obviously needed to expand our infrastructure, and we kept growing vertically rather than horizontally," says Sheriff, GolfNow’s Director, Architecture. "Our costs were growing exponentially. And on top of that, we had to build a Disaster Recovery (DR) environment, which then meant we’d have to copy exactly what we had in our original data center to another data center that was just the standby. We were basically wasting money and doubling the cost of our infrastructure."
<br> <br>
In moving just the first of GolfNow’s important applications—a booking engine for golf courses and B2B marketing platform—from third-party services to their own Kubernetes environment, "our bill went down drastically," says Sheriff.
<br> <br>
The path to those stellar results began in late 2014. In order to support GolfNow’s global growth, the team decided that the company needed to have multiple data centers and the ability to quickly and easily re-route traffic as needed. "From there we knew that we needed to go in a direction of breaking things apart, microservices, and containerization," says Sheriff. "At the time we were trying to get away from <a href="https://www.microsoft.com/net">C#.NET</a> and <a href="https://www.microsoft.com/en-cy/sql-server/sql-server-2016">SQL Server</a> since it didn’t run very well on Linux, where everything container was running smoothly."
<br> <br>
To that end, the team shifted to working with <a href="https://nodejs.org/">Node.js</a>, the open-source, cross-platform JavaScript runtime environment for developing tools and applications, and <a href="https://www.mongodb.com/">MongoDB</a>, the open-source database program. At the time, <a href="https://www.docker.com/">Docker</a>, the platform for deploying applications in containers, was still new. But once the team began experimenting with it, Sheriff says, "we realized that was the way we wanted to go, especially since that’s the way the industry is heading."
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"The team migrated the rest of the application into their Kubernetes cluster. And the impact was immediate: On top of cutting monthly costs by a large percentage, says Sheriff, 'Running at the same capacity and during our peak time, we were able to horizontally grow. Since we were using our VMs more efficiently with containers, we didn’t have to pay extra money at all.'"
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GolfNow’s dev team ran an "internal, low-key" proof of concept and were won over. "We really liked how easy it was to be able to pass containers around to each other and have them up and running in no time, exactly the way it was running on my machine," says Sheriff. "Because that is always the biggest gripe that Ops has with developers, right? ‘It worked on my machine!’ But then we started getting to the point of, ‘How do we make sure that these things stay up and running?’" <br><br>
That led the team on a quest to find the right orchestration system for the company’s needs. Sheriff says the first few options they tried were either too heavy or "didn’t feel quite right." In late summer 2015, they discovered the just-released <a href="http://kubernetes.io/">Kubernetes</a>, which Sheriff immediately liked for its ease of use. "We did another proof of concept," he says, "and Kubernetes won because of the fact that the community backing was there, built on top of what Google had already done."
<br><br>
But before they could go with Kubernetes, <a href="http://www.nbc.com/">NBC</a>, GolfNow’s parent company, also asked them to comparison shop with another company. Sheriff and his team liked the competing company’s platform user interface, but didn’t like that its platform would not allow containers to run natively on Docker. With no clear decision in sight, Sheriff’s VP at GolfNow, Steve McElwee, set up a three-month trial during which a GolfNow team (consisting of Sheriff and Josh, who’s now Lead Architect, Open Platforms) would build out a Kubernetes environment, and a large NBC team would build out one with the other company’s platform.
<br><br>
"We spun up the cluster and we tried to get everything to run the way we wanted it to run," Sheriff says. "The biggest thing that we took away from it is that not only did we want our applications to run within Kubernetes and Docker, we also wanted our databases to run there. We literally wanted our entire infrastructure to run within Kubernetes."
<br><br>
At the time there was nothing in the community to help them get Kafka and MongoDB clusters running within a Kubernetes and Docker environment, so Sheriff and Josh figured it out on their own, taking a full month to get it right. "Everything started rolling from there," Sheriff says. "We were able to get all our applications connected, and we finished our side of the proof of concept a month in advance. My VP was like, ‘Alright, it’s over. Kubernetes wins.’"
<br><br>
The next step, beginning in January 2016, was getting everything working in production. The team focused first on one application that was already written in Node.js and MongoDB. A booking engine for golf courses and B2B marketing platform, the application was already going in the microservice direction but wasn’t quite finished yet. At the time, it was running in <a href="https://devcenter.heroku.com/articles/mongohq">Heroku Compose</a> and other third-party services—resulting in a large monthly bill.
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"'The time I spent actually moving the applications was under 30 seconds! We can move data centers in just incredible amounts of time. If you haven’t come from the Kubernetes world you wouldn’t believe me.' Sheriff puts it in these terms: 'Before Kubernetes I wasn’t sleeping at night, literally. I was woken up all the time, because things were down. After Kubernetes, I’ve been sleeping at night.'"
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"The goal was to take all of that out and put it within this new platform we’ve created with Kubernetes on <a href="https://cloud.google.com/compute/">Google Compute Engine (GCE)</a>," says Sheriff. "So we ended up building piece by piece, in parallel, what was out in Heroku and Compose, in our Kubernetes cluster. Then, literally, just switched configs in the background. So in Heroku we had the app running hitting a Compose database. We’d take the config, change it and make it hit the database that was running in our cluster."
<br><br>
Using this procedure, they were able to migrate piecemeal, without any downtime. The first migration was done during off hours, but to test the limits, the team migrated the second database in the middle of the day, when lots of users were running the application. "We did it," Sheriff says, "and again it was successful. Nobody noticed."
<br><br>
After three weeks of monitoring to make sure everything was running stable, the team migrated the rest of the application into their Kubernetes cluster. And the impact was immediate: On top of cutting monthly costs by a large percentage, says Sheriff, "Running at the same capacity and during our peak time, we were able to horizontally grow. Since we were using our VMs more efficiently with containers, we didn’t have to pay extra money at all."
<br><br>
Not only were they saving money, but they were also saving time. "I had a meeting this morning about migrating some applications from one cluster to another," says Josh. "I spent about 2 hours explaining the process. The time I spent actually moving the applications was under 30 seconds! We can move data centers in just incredible amounts of time. If you haven’t come from the Kubernetes world you wouldn’t believe me." Sheriff puts it in these terms: "Before Kubernetes I wasn’t sleeping at night, literally. I was woken up all the time, because things were down. After Kubernetes, I’ve been sleeping at night."
<br><br>
A small percentage of the applications on GolfNow have been migrated over to the Kubernetes environment. "Our Core Team is rewriting a lot of the .NET applications into <a href="https://www.microsoft.com/net/core">.NET Core</a> [which is compatible with Linux and Docker] so that we can run them within containers," says Sheriff.
<br><br>
Looking ahead, Sheriff and his team want to spend 2017 continuing to build a whole platform around Kubernetes with <a href="https://github.com/drone/drone">Drone</a>, an open-source continuous delivery platform, to make it more developer-centric. "Now they’re able to manage configuration, they’re able to manage their deployments and things like that, making all these subteams that are now creating all these microservices, be self sufficient," he says. "So it can pull us away from applications and allow us to just make sure the cluster is running and healthy, and then actually migrate that over to our Ops team."
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"Having gone from complete newbies to production-ready in three months, the GolfNow team is eager to encourage other companies to follow their lead. 'This is The Six Million Dollar Man of the cloud right now,' adds Josh. 'Just try it out, watch it happen. I feel like the proof is in the pudding when you look at these kinds of application stacks. They’re faster, they’re more resilient.'"
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And long-term, Sheriff has an even bigger goal for getting more people into the Kubernetes fold. "We’re actually trying to make this platform generic enough so that any of our sister companies can use it if they wish," he says. "Most definitely I think it can be used as a model. I think the way we migrated into it, the way we built it out, are all ways that I think other companies can learn from, and should not be afraid of."
<br><br>
The GolfNow team is also giving back to the Kubernetes community by open-sourcing a bot framework that Josh built. "We noticed that the dashboard user interface is actually moving a lot faster than when we started," says Sheriff. "However we realized what we needed was something that’s more of a bot that really helps us administer Kubernetes as a whole through Slack." Josh explains: "With the Kubernetes-Slack integration, you can essentially hook into a cluster and the issue commands and edit configurations. We’ve tried to simplify the security configuration as much as possible. We hope this will be our major thank you to Kubernetes, for everything you’ve given us."
<br><br>
Having gone from complete newbies to production-ready in three months, the GolfNow team is eager to encourage other companies to follow their lead. The lessons they’ve learned: "You’ve got to have buy-in from your boss," says Sheriff. "Another big deal is having two to three people dedicated to this type of endeavor. You can’t have people who are half in, half out." And if you don’t have buy-in from the get go, proving it out will get you there.
<br><br>
"This is The Six Million Dollar Man of the cloud right now," adds Josh. "Just try it out, watch it happen. I feel like the proof is in the pudding when you look at these kinds of application stacks. They’re faster, they’re more resilient."
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<h1> CASE STUDY:<img src="/images/haufegroup_logo.png" class="header_logo"><br> <div class="subhead">Paving the Way for Cloud Native for Midsize Companies</div></h1>
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<div class="details">
Company &nbsp;<b>Haufe Group</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Freiburg, Germany</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Media and Software</b>
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<h2>Challenge</h2>
Founded in 1930 as a traditional publisher, Haufe Group has grown into a media and software company with 95 percent of its sales from digital products. Over the years, the company has gone from having "hardware in the basement" to outsourcing its infrastructure operations and IT. More recently, the development of new products, from Internet portals for tax experts to personnel training software, has created demands for increased speed, reliability and scalability. "We need to be able to move faster," says Solution Architect Martin Danielsson. "Adapting workloads is something that we really want to be able to do."
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<h2>Solution</h2>
Haufe Group began its cloud-native journey when <a href="https://azure.microsoft.com/">Microsoft Azure</a> became available in Europe; the company needed cloud deployments for its desktop apps with bandwidth-heavy download services. "After that, it has been different projects trying out different things," says Danielsson. Two years ago, Holger Reinhardt joined Haufe Group as CTO and rapidly re-oriented the traditional host provider-based approach toward a cloud and API-first strategy.
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A core part of this strategy was a strong mandate to embrace infrastructure-as-code across the entire software deployment lifecycle via Docker. The company is now getting ready to go live with two services in production using <a href="https://kubernetes.io/">Kubernetes</a> orchestration on <a href="https://azure.microsoft.com/">Microsoft Azure</a> and <a href="https://aws.amazon.com/">Amazon Web Services</a>. The team is also working on breaking up one of their core Java Enterprise desktop products into microservices to allow for better evolvability and dynamic scaling in the cloud.
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<h2>Impact</h2>
With the ability to adapt workloads, Danielsson says, teams "will be able to scale down to around half the capacity at night, saving 30 percent of the hardware cost." Plus, shorter release times have had a major impact. "Before, we had to announce at least a week in advance when we wanted to do a release because there was a huge checklist of things that you had to do," he says. "By going cloud native, we have the infrastructure in place to be able to automate all of these things. Now we can get a new release done in half an hour instead of days."
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"Over the next couple of years, people won’t even think that much about it when they want to run containers. Kubernetes is going to be the go-to solution."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Martin Danielsson, Solution Architect, Haufe Group</span>
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<h2>More than 80 years ago, Haufe Group was founded as a traditional publishing company, printing books and commentary on paper.</h2> By the 1990s, though, the company’s leaders recognized that the future was digital, and to their credit, were able to transform Haufe Group into a media and software business that now gets 95 percent of its sales from digital products. "Among the German companies doing this, we were one of the early adopters," says Martin Danielsson, Solution Architect for Haufe Group.<br><br>
And now they’re leading the way for midsize companies embracing cloud-native technology like Kubernetes. "The really big companies like Ticketmaster and Google get it right, and the startups get it right because they’re faster," says Danielsson. "We’re in this big lump of companies in the middle with a lot of legacy, a lot of structure, a lot of culture that does not easily fit the cloud technologies. We’re just 1,500 people, but we have hundreds of customer-facing applications. So we’re doing things that will be relevant for many companies of our size or even smaller."<br><br>
Many of those legacy challenges stemmed from simply following the technology trends of the times. "We used to do full DevOps," he says. In the 1990s and 2000s, "that meant that you had your hardware in the basement. And then 10 years ago, the hype of the moment was to outsource application operations, outsource everything, and strip down your IT department to take away the distraction of all these hardware things. That’s not our area of expertise. We didn’t want to be an infrastructure provider. And now comes the backlash of that."<br><br>
Haufe Group began feeling the pain as they were developing more new products, from Internet portals for tax experts to personnel training software, that have created demands for increased speed, reliability and scalability. "Right now, we have this break in workflows, where we go from writing concepts to developing, handing it over to production and then handing that over to your host provider," he says. "And then when things go bad we have no clue what went wrong. We definitely want to take back control, and we want to move a lot faster. Adapting workloads is something that we really want to be able to do."<br><br>
Those needs led them to explore cloud-native technology. Their first foray into the cloud was doing deployments in <a href="https://azure.microsoft.com/">Microsoft Azure</a>, once it became available in Europe, for desktop products that had built-in download services. Hosting expenses for such bandwidth-heavy services were too high, so the company turned to the cloud. "After that, it has been different projects trying out different things," says Danielsson.
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"We have been doing containers for the last two years, and we really got the hang of how they work," says Danielsson. "But it was always for development and test, never in production, because we didn’t fully understand how that would work. And to me, Kubernetes was definitely the technology that solved that."
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Two years ago, Holger Reinhardt joined Haufe Group as CTO and rapidly re-oriented the traditional host provider-based approach toward a cloud and API-first strategy. A core part of this strategy was a strong mandate to embrace infrastructure-as-code across the entire software deployment lifecycle via Docker.
Some experiments went further than others; German regulations about sensitive data proved to be a road block in moving some workloads to Azure and Amazon Web Services. "Due to our history, Germany is really strict with things like personally identifiable data," Danielsson says.<br><br>
These experiments took on new life with the arrival of the Azure Sovereign Cloud for Germany (an Azure clone run by the German T-Systems provider). With the availability of Azure.de—which conforms to Germany’s privacy regulations—teams started to seriously consider deploying production loads in Docker into the cloud. "We have been doing containers for the last two years, and we really got the hang of how they work," says Danielsson. "But it was always for development and test, never in production, because we didn’t fully understand how that would work. And to me, Kubernetes was definitely the technology that solved that."<br><br>
In parallel, Danielsson had built an API management system with the aim of supporting CI/CD scenarios, aspects of which were missing in off-the-shelf API management products. With a foundation based on <a href="https://getkong.org/">Mashape’s Kong</a> gateway, it is open-sourced as <a href="http://wicked.haufe.io/">wicked.haufe.io</a>. He put wicked.haufe.io to use with his product team.<br><br> Otherwise, Danielsson says his philosophy was "don’t try to reinvent the wheel all the time. Go for what’s there and 99 percent of the time it will be enough. And if you think you really need something custom or additional, think perhaps once or twice again. One of the things that I find so amazing with this cloud-native framework is that everything ties in."<br><br>
Currently, Haufe Group is working on two projects using Kubernetes in production. One is a new mobile application for researching legislation and tax laws. "We needed a way to take out functionality from a legacy core and put an application on top of that with an API gateway—a lot of moving parts that screams containers," says Danielsson. So the team moved the build pipeline away from "deploying to some old, huge machine that you could deploy anything to" and onto a Kubernetes cluster where there would be automatic CI/CD "with feature branches and all these things that were a bit tedious in the past."
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"Before, we had to announce at least a week in advance when we wanted to do a release because there was a huge checklist of things that you had to do," says Danielsson. "By going cloud native, we have the infrastructure in place to be able to automate all of these things. Now we can get a new release done in half an hour instead of days."
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It was a proof of concept effort, and the proof was in the pudding. "Everyone was really impressed at what we accomplished in a week," says Danielsson. "We did these kinds of integrations just to make sure that we got a handle on how Kubernetes works. If you can create optimism and buzz around something, it’s half won. And if the developers and project managers know this is working, you’re more or less done." Adds Reinhardt: "You need to create some very visible, quick wins in order to overcome the status quo."<br><br>
The impact on the speed of deployment was clear: "Before, we had to announce at least a week in advance when we wanted to do a release because there was a huge checklist of things that you had to do," says Danielsson. "By going cloud native, we have the infrastructure in place to be able to automate all of these things. Now we can get a new release done in half an hour instead of days." <br><br>
The potential impact on cost was another bonus. "Hosting applications is quite expensive, so moving to the cloud is something that we really want to be able to do," says Danielsson. With the ability to adapt workloads, teams "will be able to scale down to around half the capacity at night, saving 30 percent of the hardware cost." <br><br>
Just as importantly, Danielsson says, there’s added flexibility: "When we try to move or rework applications that are really crucial, it’s often tricky to validate whether the path we want to take is going to work out well. In order to validate that, we would need to reproduce the environment and really do testing, and that’s prohibitively expensive and simply not doable with traditional host providers. Cloud native gives us the ability to do risky changes and validate them in a cost-effective way."<br><br>
As word of the two successful test projects spread throughout the company, interest in Kubernetes has grown. "We want to be able to support our developers in running Kubernetes clusters but we’re not there yet, so we allow them to do it as long as they’re aware that they are on their own," says Danielsson. "So that’s why we are also looking at things like [the managed Kubernetes platform] <a href="https://coreos.com/tectonic/">CoreOS Tectonic</a>, <a href="https://azure.microsoft.com/en-us/services/container-service/">Azure Container Service</a>, <a href="https://aws.amazon.com/ecs/">ECS</a>, etc. These kinds of services will be a lot more relevant to midsize companies that want to leverage cloud native but don’t have the IT departments or the structure around that."<br><br>
In the next year and a half, Danielsson says the company will be working on moving one of their legacy desktop products, a web app for researching legislation and tax laws originally built in Java Enterprise, onto cloud-native technology. "We’re doing a microservice split out right now so that we can independently deploy the different parts," he says. The main website, which provides free content for customers, is also moving to cloud native.
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"the execution of a strategy requires alignment of culture, structure and technology. Only if those three dimensions are aligned can you successfully execute a transformation into microservices and cloud-native architectures. And it is only then that the Cloud will pay the dividends in much faster speeds in product innovation and much lower operational costs."
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But with these goals, Danielsson believes there are bigger cultural challenges that need to be constantly addressed. The move to new technology, not to mention a shift toward DevOps, means a lot of change for employees. "The roles were rather fixed in the past," he says. "You had developers, you had project leads, you had testers. And now you get into these really, really important things like test automation. Testers aren’t actually doing click testing anymore, and they have to write automated testing. And if you really want to go full-blown CI/CD, all these little pieces have to work together so that you get the confidence to do a check in, and know this check in is going to land in production, because if I messed up, some test is going to break. This is a really powerful thing because whatever you do, whenever you merge something into the trunk or to the master, this is going live. And that’s where you either get the people or they run away screaming."
Danielsson understands that it may take some people much longer to get used to the new ways.<br><br>
"Culture is nothing that you can force on people," he says. "You have to live it for yourself. You have to evangelize. You have to show the advantages time and time again: This is how you can do it, this is what you get from it." To that end, his team has scheduled daylong workshops for the staff, bringing in outside experts to talk about everything from API to Devops to cloud. <br><br>
For every person who runs away screaming, many others get drawn in. "Get that foot in the door and make them really interested in this stuff," says Danielsson. "Usually it catches on. We have people you never would have expected chanting, ‘Docker Docker Docker’ now. It’s cool to see them realize that there is a world outside of their Python libraries. It’s awesome to see them really work with Kubernetes."<br><br>
Ultimately, Reinhardt says, "the execution of a strategy requires alignment of culture, structure and technology. Only if those three dimensions are aligned can you successfully execute a transformation into microservices and cloud-native architectures. And it is only then that the Cloud will pay the dividends in much faster speeds in product innovation and much lower operational costs."
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<h1> CASE STUDY:<img src="/images/huawei_logo.png" class="header_logo"><br> <div class="subhead">Embracing Cloud Native as a User – and a Vendor</div></h1>
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Company &nbsp;<b>Huawei</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Shenzhen, China</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Telecommunications Equipment</b>
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<h2>Challenge</h2>
A multinational company that’s the largest telecommunications equipment manufacturer in the world, Huawei has more than 180,000 employees. In order to support its fast business development around the globe, <a href="http://www.huawei.com/">Huawei</a> has eight data centers for its internal I.T. department, which have been running 800+ applications in 100K+ VMs to serve these 180,000 users. With the rapid increase of new applications, the cost and efficiency of management and deployment of VM-based apps all became critical challenges for business agility. "It’s very much a distributed system so we found that managing all of the tasks in a more consistent way is always a challenge," says Peixin Hou, the company’s Chief Software Architect and Community Director for Open Source. "We wanted to move into a more agile and decent practice."
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<h2>Solution</h2>
After deciding to use container technology, Huawei began moving the internal I.T. department’s applications to run on <a href="http://kubernetes.io/">Kubernetes</a>. So far, about 30 percent of these applications have been transferred to cloud native.
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<h2>Impact</h2>
"By the end of 2016, Huawei’s internal I.T. department managed more than 4,000 nodes with tens of thousands containers using a Kubernetes-based Platform as a Service (PaaS) solution," says Hou. "The global deployment cycles decreased from a week to minutes, and the efficiency of application delivery has been improved 10 fold." For the bottom line, he says, "We also see significant operating expense spending cut, in some circumstances 20-30 percent, which we think is very helpful for our business." Given the results Huawei has had internally – and the demand it is seeing externally – the company has also built the technologies into <a href="http://developer.huawei.com/ict/en/site-paas">FusionStage™</a>, the PaaS solution it offers its customers.
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"If you’re a vendor, in order to convince your customer, you should use it yourself. Luckily because Huawei has a lot of employees, we can demonstrate the scale of cloud we can build using this technology."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Peixin Hou, chief software architect and community director for open source</span>
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Huawei’s Kubernetes journey began with one developer.
Over two years ago, one of the engineers employed by the networking and telecommunications giant became interested in <a href="http://kubernetes.io/">Kubernetes</a>, the technology for managing application containers across clusters of hosts, and started contributing to its open source community. As the technology developed and the community grew, he kept telling his managers about it.<br><br>
And as fate would have it, at the same time, Huawei was looking for a better orchestration system for its internal enterprise I.T. department, which supports every business flow processing. "We have more than 180,000 employees worldwide, and a complicated internal procedure, so probably every week this department needs to develop some new applications," says Peixin Hou, Huawei’s Chief Software Architect and Community Director for Open Source. "Very often our I.T. departments need to launch tens of thousands of containers, with tasks running across thousands of nodes across the world. It’s very much a distributed system, so we found that managing all of the tasks in a more consistent way is always a challenge."<br><br>
In the past, Huawei had used virtual machines to encapsulate applications, but "every time when we start a VM," Hou says, "whether because it’s a new service or because it was a service that was shut down because of some abnormal node functioning, it takes a lot of time." Huawei turned to containerization, so the timing was right to try Kubernetes. It took a year to adopt that engineer’s suggestion – the process "is not overnight," says Hou – but once in use, he says, "Kubernetes basically solved most of our problems. Before, the time of deployment took about a week, now it only takes minutes. The developers are happy. That department is also quite happy."<br><br>
Hou sees great benefits to the company that come with using this technology: "Kubernetes brings agility, scale-out capability, and DevOps practice to the cloud-based applications," he says. "It provides us with the ability to customize the scheduling architecture, which makes possible the affinity between container tasks that gives greater efficiency. It supports multiple container formats. It has extensive support for various container networking solutions and container storage."
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"Kubernetes basically solved most of our problems. Before, the time of deployment took about a week, now it only takes minutes. The developers are happy. That department is also quite happy."
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And not least of all, there’s an impact on the bottom line. Says Hou: "We also see significant operating expense spending cut in some circumstances 20-30 percent, which is very helpful for our business."<br><br>
Pleased with those initial results, and seeing a demand for cloud native technologies from its customers, Huawei doubled down on Kubernetes. In the spring of 2016, the company became not only a user but also a vendor.<br><br>
"We built the Kubernetes technologies into our solutions," says Hou, referring to Huawei’s <a href="http://developer.huawei.com/ict/en/site-paas">FusionStage™</a> PaaS offering. "Our customers, from very big telecommunications operators to banks, love the idea of cloud native. They like Kubernetes technology. But they need to spend a lot of time to decompose their applications to turn them into microservice architecture, and as a solution provider, we help them. We’ve started to work with some Chinese banks, and we see a lot of interest from our customers like <a href="http://www.chinamobileltd.com/">China Mobile</a> and <a href="https://www.telekom.com/en">Deutsche Telekom</a>."<br><br>
"If you’re just a user, you’re just a user," adds Hou. "But if you’re a vendor, in order to even convince your customers, you should use it yourself. Luckily because Huawei has a lot of employees, we can demonstrate the scale of cloud we can build using this technology. We provide customer wisdom." While Huawei has its own private cloud, many of its customers run cross-cloud applications using Huawei’s solutions. It’s a big selling point that most of the public cloud providers now support Kubernetes. "This makes the cross-cloud transition much easier than with other solutions," says Hou.<br><br>
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"Our customers, from very big telecommunications operators to banks, love the idea of cloud native. They like Kubernetes technology. But they need to spend a lot of time to decompose their applications to turn them into microservice architecture, and as a solution provider, we help them."
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Within Huawei itself, once his team completes the transition of the internal business procedure department to Kubernetes, Hou is looking to convince more departments to move over to the cloud native development cycle and practice. "We have a lot of software developers, so we will provide them with our platform as a service solution, our own product," he says. "We would like to see significant cuts in their iteration cycle."<br><br>
Having overseen the initial move to Kubernetes at Huawei, Hou has advice for other companies considering the technology: "When you start to design the architecture of your application, think about cloud native, think about microservice architecture from the beginning," he says. "I think you will benefit from that."<br><br>
But if you already have legacy applications, "start from some microservice-friendly part of those applications first, parts that are relatively easy to be decomposed into simpler pieces and are relatively lightweight," Hou says. "Don’t think from day one that within how many days I want to move the whole architecture, or move everything into microservices. Don’t put that as a kind of target. You should do it in a gradual manner. And I would say for legacy applications, not every piece would be suitable for microservice architecture. No need to force it."<br><br>
After all, as enthusiastic as Hou is about Kubernetes at Huawei, he estimates that "in the next 10 years, maybe 80 percent of the workload can be distributed, can be run on the cloud native environments. There’s still 20 percent that’s not, but it’s fine. If we can make 80 percent of our workload really be cloud native, to have agility, it’s a much better world at the end of the day."
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"In the next 10 years, maybe 80 percent of the workload can be distributed, can be run on the cloud native environments. There’s still 20 percent that’s not, but it’s fine. If we can make 80 percent of our workload really be cloud native, to have agility, it’s a much better world at the end of the day."
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In the nearer future, Hou is looking forward to new features that are being developed around Kubernetes, not least of all the ones that Huawei is contributing to. Huawei engineers have worked on the federation feature (which puts multiple Kubernetes clusters in a single framework to be managed seamlessly), scheduling, container networking and storage, and a just-announced technology called <a href="http://containerops.org/">Container Ops</a>, which is a DevOps pipeline engine. "This will put every DevOps job into a container," he explains. "And then this container mechanism is running using Kubernetes, but is also used to test Kubernetes. With that mechanism, we can make the containerized DevOps jobs be created, shared and managed much more easily than before."<br><br>
Still, Hou sees this technology as only halfway to its full potential. First and foremost, he’d like to expand the scale it can orchestrate, which is important for supersized companies like Huawei – as well as some of its customers.<br><br>
Hou proudly notes that two years after that first Huawei engineer became a contributor to and evangelist for Kubernetes, Huawei is now a top contributor to the community. "We’ve learned that the more you contribute to the community," he says, "the more you get back."
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<h1> CASE STUDY:<img src="/images/peardeck_logo.png" width="22%" style="margin-bottom:-0px"><br> <div class="subhead">Infrastructure for a Growing EdTech Startup</div></h1>
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Company &nbsp;<b>Pear Deck</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Iowa City, Iowa</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Educational Software</b>
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<h2>Challenge</h2>
The three-year-old startup provides a web app for teachers to interact with their students in the classroom. The JavaScript app was built on Google’s web app development platform <a href="https://firebase.google.com/">Firebase</a>, using <a href="https://www.heroku.com/">Heroku</a>. As the user base steadily grew, so did the development team. "We outgrew Heroku when we started wanting to have multiple services, and the deploying story got pretty horrendous. We were frustrated that we couldn’t have the developers quickly stage a version," says CEO Riley Eynon-Lynch. "Tracing and monitoring became basically impossible." On top of that, many of Pear Deck’s customers are behind government firewalls and connect through Firebase, not Pear Deck’s servers, making troubleshooting even more difficult.
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<h2>Solution</h2>
In 2016, the company began moving their code from Heroku to <a href="https://www.docker.com/">Docker</a> containers running on <a href="https://cloud.google.com/kubernetes-engine/">Google Kubernetes Engine</a>, orchestrated by <a href="http://kubernetes.io/">Kubernetes</a> and monitored with <a href="https://prometheus.io/">Prometheus</a>.
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<h2>Impact</h2>
The new cloud native stack immediately improved the development workflow, speeding up deployments. Prometheus gave Pear Deck "a lot of confidence, knowing that people are still logging into the app and using it all the time," says Eynon-Lynch. "The biggest impact is being able to work as a team on the configuration in git in a pull request, and the biggest confidence comes from the solidity of the abstractions and the trust that we have in Kubernetes actually making our yaml files a reality."
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"We didn’t even realize how stressed out we were about our lack of insight into what was happening with the app. I’m really excited and have more and more confidence in the actual state of our application for our actual users, and not just what the CPU graphs are saying, because of Prometheus and Kubernetes."<br><br><span style="font-size:16px;letter-spacing:2px;">– RILEY EYNON-LYNCH, CEO OF PEAR DECK</span>
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<h2>With the speed befitting a startup, Pear Deck delivered its first prototype to customers within three months of incorporating.</h2>
As a former high school math teacher, CEO Riley Eynon-Lynch felt an urgency to provide a tech solution to classes where instructors struggle to interact with every student in a short amount of time. "Pear Deck is an app that students can use to interact with the teacher all at once," he says. "When the teacher asks a question, instead of just the kid at the front of the room answering again, everybody can answer every single question. It’s a huge fundamental shift in the messaging to the students about how much we care about them and how much they are a part of the classroom."<br><br>
Eynon-Lynch and his partners quickly built a JavaScript web app on Google’s web app development platform <a href="https://firebase.google.com/">Firebase</a>, and launched the minimum viable product [MVP] on <a href="https://www.heroku.com/">Heroku</a> "because it was fast and easy," he says. "We made everything as easy as we could."
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But once it launched, the user base began growing steadily at a rate of 30 percent a month. "Our Heroku bill was getting totally insane," Eynon-Lynch says. But even more crucially, as the company hired more developers to keep pace, "we outgrew Heroku. We wanted to have multiple services and the deploying story got pretty horrendous. We were frustrated that we couldn’t have the developers quickly stage a version. Tracing and monitoring became basically impossible."
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On top of that, many of Pear Deck’s customers are behind government firewalls and connect through Firebase, not Pear Deck’s servers, making troubleshooting even more difficult.
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The team began looking around for another solution, and finally decided in early 2016 to start moving the app from Heroku to <a href="https://www.docker.com/">Docker</a> containers running on <a href="https://cloud.google.com/kubernetes-engine/">Google Kubernetes Engine</a>, orchestrated by <a href="http://kubernetes.io/">Kubernetes</a> and monitored with <a href="https://prometheus.io/">Prometheus</a>.
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"When it became clear that Google Kubernetes Engine was going to have a lot of support from Google and be a fully-managed Kubernetes platform, it seemed very obvious to us that was the way to go," says Eynon-Lynch.
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They had considered other options like Google’s App Engine (which they were already using for one service) and Amazon’s <a href="https://aws.amazon.com/ec2/">Elastic Compute Cloud</a> (EC2), while experimenting with running one small service that wasn’t accessible to the Internet in Kubernetes. "When it became clear that Google Kubernetes Engine was going to have a lot of support from Google and be a fully-managed Kubernetes platform, it seemed very obvious to us that was the way to go," says Eynon-Lynch. "We didn’t really consider Terraform and the other competitors because the abstractions offered by Kubernetes just jumped off the page to us."<br><br>
Once the team started porting its Heroku apps into Kubernetes, which was "super easy," he says, the impact was immediate. "Before, to make a new version of the app meant going to Heroku and reconfiguring 10 new services, so basically no one was willing to do it, and we never staged things," he says. "Now we can deploy our exact same configuration in lots of different clusters in 30 seconds. We have a full set up that’s always running, and then any of our developers or designers can stage new versions with one command, including their recent changes. We stage all the time now, and everyone stopped talking about how cool it is because it’s become invisible how great it is."
<br><br>
Along with Kubernetes came Prometheus. "Until pretty recently we didn’t have any kind of visibility into aggregate server metrics or performance," says Eynon-Lynch. The team had tried to use Google Kubernetes Engine’s <a href="https://cloud.google.com/stackdriver/">Stackdriver</a> monitoring, but had problems making it work, and considered <a href="https://newrelic.com/">New Relic</a>. When they started looking at Prometheus in the fall of 2016, "the fit between the abstractions in Prometheus and the way we think about how our system works, was so clear and obvious," he says.<br><br>
The integration with Kubernetes made set-up easy. Once Helm installed Prometheus, "We started getting a graph of the health of all our Kubernetes nodes and pods immediately. I think we were pretty hooked at that point," Eynon-Lynch says. "Then we got our own custom instrumentation working in 15 minutes, and had an actively updated count of requests that we could do, rate on and get a sense of how many users are connected at a given point. And then it was another hour before we had alarms automatically showing up in our Slack channel. All that was in one afternoon. And it was an afternoon of gasping with delight, basically!"
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"We started getting a graph of the health of all our Kubernetes nodes and pods immediately. I think we were pretty hooked at that point," Eynon-Lynch says. "Then we got our own custom instrumentation working in 15 minutes, and had an actively updated count of requests that we could do, rate on and get a sense of how many users are connected at a given point. And then it was another hour before we had alarms automatically showing up in our Slack channel. All that was in one afternoon. And it was an afternoon of gasping with delight, basically!"
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With Pear Deck’s specific challenges—traffic through Firebase as well as government firewalls—Prometheus was a game-changer. "We didn’t even realize how stressed out we were about our lack of insight into what was happening with the app," Eynon-Lynch says. Before, when a customer would report that the app wasn’t working, the team had to manually investigate the problem without knowing whether customers were affected all over the world, or whether Firebase was down, and where.<br><br>
To help solve that problem, the team wrote a script that pings Firebase from several different geographical locations, and then reports the responses to Prometheus in a histogram. "A huge impact that Prometheus had on us was just an amazing sigh of relief, of feeling like we knew what was happening," he says. "It took 45 minutes to implement [the Firebase alarm] because we knew that we had this trustworthy metrics platform in Prometheus. We weren’t going to have to figure out, ‘Where do we send these metrics? How do we aggregate the metrics? How do we understand them?’"<br><br>
Plus, Prometheus has allowed Pear Deck to build alarms for business goals. One measures the rate of successful app loads and goes off if the day’s loads are less than 90 percent of the loads from seven days before. "We run a JavaScript app behind ridiculous firewalls and all kinds of crazy browser extensions messing with it—Chrome will push a feature that breaks some CSS that we’re using," Eynon-Lynch says. "So that gives us a lot of confidence, and we at least know that people are still logging into the app and using it all the time."<br><br>
Now, when a customer complains, and none of the alarms have gone off, the team can feel confident that it’s not a widespread problem. "Just to be sure, we can go and double check the graphs and say, ‘Yep, there’s currently 10,000 people connected to that Firebase node. It’s definitely working. Let’s investigate your network settings, customer,’" he says. "And we can pass that back off to our support reps instead of the whole development team freaking out that Firebase is down."<br><br>
Pear Deck is also giving back to the community, building and open-sourcing a <a href="https://github.com/peardeck/prometheus-user-metrics">metrics aggregator</a> that enables end-user monitoring in Prometheus. "We can measure, for example, the time to interactive-dom on the web clients," he says. "The users all report that to our aggregator, then the aggregator reports to Prometheus. So we can set an alarm for some client side errors."<br><br>
Most of Pear Deck’s services have now been moved onto Kubernetes. And all of the team’s new code is going on Kubernetes. "Kubernetes lets us experiment with service configurations and stage them on a staging cluster all at once, and test different scenarios and talk about them as a development team looking at code, not just talking about the steps we would eventually take as humans," says Eynon-Lynch.
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"A huge impact that Prometheus had on us was just an amazing sigh of relief, of feeling like we knew what was happening. It took 45 minutes to implement [the Firebase alarm] because we knew that we had this trustworthy metrics platform in Prometheus...in terms of the cloud, Kubernetes and Prometheus have so much to offer," he says.
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Looking ahead, the team is planning to explore autoscaling on Kubernetes. With users all over the world but mostly in the United States, there are peaks and valleys in the traffic. One service that’s still on App Engine can get as many as 10,000 requests a second during the day but far less at night. "We pay for the same servers at night, so I understand there’s autoscaling that we can be taking advantage of," he says. "Implementing it is a big worry, exposing the rest of our Kubernetes cluster to us and maybe messing that up. But it’s definitely our intention to move everything over, because now none of the developers want to work on that app anymore because it’s such a pain to deploy it."
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They’re also eager to explore the work that Kubernetes is doing with stateful sets. "Right now all of the services we run in Kubernetes are stateless, and Google basically runs our databases for us and manages backups," Eynon-Lynch says. "But we’re interested in building our own web-socket solution that doesn’t have to be super stateful but will have maybe an hour’s worth of state on it."
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That project will also involve Prometheus, for a dark launch of web socket connections. "We don’t know how reliable web socket connections behind all these horrible firewalls will be to our servers," he says. "We don’t know what work Firebase has done to make them more reliable. So I’m really looking forward to trying to get persistent connections with web sockets to our clients and have optional tools to understand if it’s working. That’s our next new adventure, into stateful servers."
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As for Prometheus, Eynon-Lynch thinks the company has only gotten started. "We haven’t instrumented all our important features, especially those that depend on third parties," he says. "We have to wait for those third parties to tell us they’re down, which sometimes they don’t do for a long time. So I’m really excited and have more and more confidence in the actual state of our application for our actual users, and not just what the CPU graphs are saying, because of Prometheus and Kubernetes."
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For a spry startup that’s continuing to grow rapidly—and yes, they’re <a href="https://www.peardeck.com/careers/">hiring</a>!—Pear Deck is notably satisfied with how its infrastructure has evolved in the cloud native ecosystem. "Usually I have some angsty thing where I want to get to the new, better technology," says Eynon-Lynch, "but in terms of the cloud, Kubernetes and Prometheus have so much to offer."
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<h1> Pearson Case Study</h1>
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<h3 id="caseStudyTitle">Using Kubernetes to reinvent the world's largest educational company</h3>
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Pearson, the world's education company, serving 75 million learners worldwide, set a goal to more than double that number to 200 million by 2025. A key part of this growth is in digital learning experiences, and that requires an infrastructure platform that is able to scale quickly and deliver products to market faster. So Pearson's Cloud Technology team chose Kubernetes to help build a platform to meet the business requirements. </p>
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"To transform our infrastructure, we had to think beyond simply enabling automated provisioning, we realized we had to build a platform that would allow Pearson developers to build manage and deploy applications in a completely different way. We chose Kubernetes because of its flexibility, ease of management and the way it would improve our engineers' productivity." </p>
<p class="attrib">— Chris Jackson, Director for Cloud Product Engineering, Pearson</p>
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<h4>Challenges:</h4>
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<li>Pearson had difficulty in scaling and adapting to the growing online audience. They wanted to build and deliver content primarily over the web.</li>
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<h4>Why Kubernetes:</h4>
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<li>Kubernetes will allow Pearson's teams to develop their apps in a consistent manner, saving time and minimizing complexity.</li>
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<h4>Approach:</h4>
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<li>Build a centralized platform for use across the entire enterprise</li>
<li>Use container technology as the core of the platform</li>
<li>Deploy Kubernetes to manage the platform</li>
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<h4>Results:</h4>
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<li>Pearson is building an enterprise-wide platform for delivering innovative, web-based educational content. They expect engineers' productivity to increase by up to 20 percent.</li>
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<h4>Kubernetes powers a comprehensive developer experience</h4>
<p>Pearson wanted to use as much open source technology as possible for the platform given that it provides both technical and commercial benefits over the duration of the project. Jackson says, "Building an infrastructure platform based on open source technology in Pearson was a no-brainer, the sharing of technical challenges and advanced use cases in a community of people with talent far beyond what we could hire independently allows us to innovate at a level we could not reach on our own. Our engineers enjoy returning code to the community and participating in talks, blogs and meetings, it's a great way for us to allow our team to express themselves and share the pride they have in their work."</p>
<p>It also wanted to use a container-focused platform. Pearson has 400 development groups and diverse brands with varying business and technical needs. With containers, each brand could experiment with building new types of content using their preferred technologies, and then deliver it using containers. Pearson chose Kubernetes because it believes that is the best technology for managing containers, has the widest community support and offers the most flexible and powerful tools."</p>
<p>Kubernetes is at the core of the platform we've built for developers. After we get our big spike in back-to-school in traffic, much of Pearson's traffic will interact with Kubernetes. It is proving to be as effective as we had hoped," Jackson says.</p>
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<h4>Encouraging experimentation, saving engineers time</h4>
<p>With the new platform, Pearson will increase stability and performance, and to bring products to market more quickly. The company says its engineers will also get a productivity boost because they won't spend time managing infrastructure. Jackson estimates 15 to 20 percent in productivity savings.</p>
<p>Beyond that, Pearson says the platform will encourage innovation because of the ease with which new applications can be developed, and because applications will be deployed far more quickly than in the past. It expects that will help the company meet its goal of reaching 200 million learners within the next 10 years.</p>
<p>"We're already seeing tremendous benefits with Kubernetes — improved engineering productivity, faster delivery of applications and a simplified infrastructure. But this is just the beginning. Kubernetes will help transform the way that educational content is delivered online," says Jackson.</p>
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<h1> CASE STUDY:<img src="/images/squarespace_logo.png" class="header_logo"><br> <div class="subhead">Squarespace: Gaining Productivity and Resilience with Kubernetes
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Company &nbsp;<b>Squarespace</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>New York, N.Y.</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Software as a Service, Website-Building Platform</b>
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<h2>Challenge</h2>
Moving from a monolith to microservices in 2014 "solved a problem on the development side, but it pushed that problem to the infrastructure team," says Kevin Lynch, Staff Engineer on the Site Reliability team at Squarespace. "The infrastructure deployment process on our 5,000 VM hosts was slowing everyone down."
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<h2>Solution</h2>
The team experimented with container orchestration platforms, and found that Kubernetes "answered all the questions that we had," says Lynch. The company began running Kubernetes in its data centers in&nbsp;2016.
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<h2>Impact</h2>
Since Squarespace moved to Kubernetes, in conjunction with modernizing its networking stack, deployment time has been reduced by almost 85%. Before, their VM deployment would take half an hour; now, says Lynch, "someone can generate a templated application, deploy it within five minutes, and have actual instances containerized, running in our staging environment at that point." Because of that, "productivity time is the big cost saver," he adds. "When we started the Kubernetes project, we had probably a dozen microservices. Today there are twice that in the pipeline being actively worked on." Resilience has also been improved with Kubernetes: "If a node goes down, it’s rescheduled immediately and there’s no performance&nbsp;impact."
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"Once you prove that Kubernetes solves one problem, everyone immediately starts solving other problems without you even having to evangelize it."
<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>— Kevin Lynch, Staff Engineer on the Site Reliability team at Squarespace</span>
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<h2>Since it was started in a dorm room in 2003, Squarespace has made it simple for millions of people to create their own websites.</h2> Behind the scenes, though, the company’s monolithic Java application was making things not so simple for its developers to keep improving the platform. So in 2014, the company decided to "go down the microservices path," says Kevin Lynch, staff engineer on Squarespace’s Site Reliability team. "But we were always deploying our applications in vCenter VMware VMs [in our own data centers]. Microservices solved a problem on the development side, but it pushed that problem to the Infrastructure team. The infrastructure deployment process on our 5,000 VM hosts was slowing everyone down."<br><br>
After experimenting with another container orchestration platform and "breaking it in very painful ways," Lynch says, the team began experimenting with Kubernetes in mid-2016 and found that it "answered all the questions that we had." Deploying it in the data center rather than the public cloud was their biggest challenge, and at the time, not a lot of other companies were doing that. "We had to figure out how to deploy this in our infrastructure for ourselves, and we had to integrate it with our other applications," says Lynch.<br><br>
At the same time, Squarespace’s Network Engineering team was modernizing its networking stack, switching from a traditional layer-two network to a layer-three spine-and-leaf network. "It mapped beautifully with what we wanted to do with Kubernetes," says Lynch. "It gives us the ability to have our servers communicate directly with the top-of-rack switches. We use Calico for <a href="https://github.com/containernetworking/cnihttps://github.com/containernetworking/cni">CNI networking for Kubernetes</a>, so we can announce all these individual Kubernetes pod IP addresses and have them integrate seamlessly with our other services that are still provisioned in the VMs."
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After experimenting with another container orchestration platform and "breaking it in very painful ways," Lynch says, the team began experimenting with Kubernetes in mid-2016 and found that it "answered all the questions that we had."
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Within a couple months, they had a stable cluster for their internal use, and began rolling out Kubernetes for production. They also added Zipkin and CNCF projects <a href="https://prometheus.io/">Prometheus</a> and <a href="https://www.fluentd.org/">fluentd</a> to their cloud native stack. "We switched to Kubernetes, a new world, and we revamped all our other tooling as well," says Lynch. "It allowed us to streamline our process, so we can now easily create an entire microservice project from templates, generate the code and deployment pipeline for that, generate the Docker file, and then immediately just ship a workable, deployable project to Kubernetes." Deployments across Dev/QA/Stage/Prod were also "simplified drastically," Lynch adds. "Now there is little configuration variation."
<br><br>
And the whole process takes only five minutes, an almost 85% reduction in time compared to their VM deployment. "From end to end that probably took half an hour, and that’s not accounting for the fact that an infrastructure engineer would be responsible for doing that, so there’s some business delay in there as well."
<br><br>
With faster deployments, "productivity time is the big cost saver," says Lynch. "We had a team that was implementing a new file storage service, and they just started integrating that with our storage back end without our involvement"—which wouldn’t have been possible before Kubernetes. He adds: "When we started the Kubernetes project, we had probably a dozen microservices. Today there are twice that in the pipeline being actively worked on."
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"We switched to Kubernetes, a new world....It allowed us to streamline our process, so we can now easily create an entire microservice project from templates," Lynch says. And the whole process takes only five minutes, an almost 85% reduction in time compared to their VM deployment.
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There’s also been a positive impact on the application’s resilience. "When we’re deploying VMs, we have to build tooling to ensure that a service is spread across racks appropriately and can withstand failure," he says. "Kubernetes just does it. If a node goes down, it’s rescheduled immediately and there’s no performance impact."
<br><br>
Another big benefit is autoscaling. "It wasn’t really possible with the way we’ve been using VMware," says Lynch, "but now we can just add the appropriate autoscaling features via Kubernetes directly, and boom, it’s scaling up as demand increases. And it worked out of the box."
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For others starting out with Kubernetes, Lynch says his best advice is to "fail fast": "Once you’ve planned things out, just execute. Kubernetes has been really great for trying something out quickly and seeing if it works or not."
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"When we’re deploying VMs, we have to build tooling to ensure that a service is spread across racks appropriately and can withstand failure," he says. "Kubernetes just does it. If a node goes down, it’s rescheduled immediately and there’s no performance impact."
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Lynch and his team are planning to open source some of the tools they’ve developed to extend Kubernetes and use it as an API itself. The first tool injects dependent applications as containers in a pod. "When you ship an application, usually it comes along with a whole bunch of dependent applications that need to be shipped with that, for example, fluentd for logging," he explains. With this tool, the developer doesn’t need to worry about the configurations.
<br><br>
Going forward, all new services at Squarespace are going into Kubernetes, and the end goal is to convert everything it can. About a quarter of existing services have been migrated. "Our monolithic application is going to be the last one, just because it’s so big and complex," says Lynch. "But now I’m seeing other services get moved over, like the file storage service. Someone just did it and it worked—painlessly. So I believe if we tackle it, it’s probably going to be a lot easier than we fear. Maybe I should just take my own advice and fail fast!"
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<h1> Wikimedia Case Study</h1>
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<h3 id="caseStudyTitle">Using Kubernetes to Build Tools to Improve the World's Wikis</h3>
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The non-profit Wikimedia Foundation operates some of the largest collaboratively edited reference projects in the world, including Wikipedia. To help users maintain and use wikis, it runs Wikimedia Tool Labs, a hosting environment for community developers working on tools and bots to help editors and other volunteers do their work, including reducing vandalism. The community around Wikimedia Tool Labs began forming nearly 10 years ago.
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"Wikimedia Tool Labs is vital for making sure wikis all around the world work as well as they possibly can. Because it's grown organically for almost 10 years, it has become an extremely challenging environment and difficult to maintain. It's like a big ball of mud — you really can't see through it. With Kubernetes, we're simplifying the environment and making it easier for developers to build the tools that make wikis run better."
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<p class="attrib">— Yuvi Panda, operations engineer at Wikimedia Foundation and Wikimedia Tool Labs</p>
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<h4>Challenges:</h4>
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<li>Simplify a complex, difficult-to-manage infrastructure</li>
<li>Allow developers to continue writing tools and bots using existing techniques</li>
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<h4>Why Kubernetes:</h4>
<ul>
<li>Wikimedia Tool Labs chose Kubernetes because it can mimic existing workflows, while reducing complexity</li>
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<h4>Approach:</h4>
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<li>Migrate old systems and a complex infrastructure to Kubernetes</li>
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<h4>Results:</h4>
<ul>
<li>20 percent of web tools that account for more than 40 percent of web traffic now run on Kubernetes</li>
<li>A 25-node cluster that keeps up with each new Kubernetes release</li>
<li>Thousands of lines of old code have been deleted, thanks to Kubernetes</li>
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<h4>Using Kubernetes to provide tools for maintaining wikis</h4>
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Wikimedia Tool Labs is run by a staff of four-and-a-half paid employees and two volunteers. The infrastructure didn't make it easy or intuitive for developers to build bots and other tools to make wikis work more easily. Yuvi says, "It's incredibly chaotic. We have lots of Perl and Bash duct tape on top of it. Everything is super fragile."
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To solve the problem, Wikimedia Tool Labs migrated parts of its infrastructure to Kubernetes, in preparation for eventually moving its entire system. Yuvi said Kubernetes greatly simplifies maintenance. The goal is to allow developers creating bots and other tools to use whatever development methods they want, but make it easier for the Wikimedia Tool Labs to maintain the required infrastructure for hosting and sharing them.
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"With Kubernetes, I've been able to remove a lot of our custom-made code, which makes everything easier to maintain. Our users' code also runs in a more stable way than previously," says Yuvi.
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<h4>Simplifying infrastructure and keeping wikis running better</h4>
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Wikimedia Tool Labs has seen great success with the initial Kubernetes deployment. Old code is being simplified and eliminated, contributing developers don't have to change the way they write their tools and bots, and those tools and bots run in a more stable fashion than they have in the past. The paid staff and volunteers are able to better keep up with fixing issues.
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<p>
In the future, with a more complete migration to Kubernetes, Wikimedia Tool Labs expects to make it even easier to host and maintain the bots and tools that help run wikis across the world. The tool labs already host approximately 1,300 tools and bots from 800 volunteers, with many more being submitted every day. Twenty percent of the tool labs' web tools that account for more than 60 percent of web traffic now run on Kubernetes. The tool labs has a 25-node cluster that keeps up with each new Kubernetes release. Many existing web tools are migrating to Kubernetes.
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"Our goal is to make sure that people all over the world can share knowledge as easily as possible. Kubernetes helps with that, by making it easier for wikis everywhere to have the tools they need to thrive," says Yuvi.
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<h1>CASE STUDY: <img src="/images/wink_logo.png" width="13%" style="margin-bottom:-4px"><br>
<div class="subhead">Cloud-Native Infrastructure Keeps Your Smart Home Connected</div>
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Company &nbsp;<b>Wink</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>New York, N.Y.</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Internet of Things Platform</b>
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<h2>Challenge</h2>
Building a low-latency, highly reliable infrastructure to serve communications between millions of connected smart-home devices and the company’s consumer hubs and mobile app, with an emphasis on horizontal scalability, the ability to encrypt everything quickly and connections that could be easily brought back up if anything went wrong.
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<h2>Solution</h2>
Across-the-board use of a Kubernetes-Docker-CoreOS Container Linux stack.<br><br>
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<h2>Impact</h2>
"Two of the biggest American retailers [Home Depot and Walmart] are carrying and promoting the brand and the hardware,” Wink Head of Engineering Kit Klein says proudly – though he adds that "it really comes with a lot of pressure. It’s not a retail situation where you have a lot of tech enthusiasts. These are everyday people who want something that works and have no tolerance for technical excuses.” And that’s further testament to how much faith Klein has in the infrastructure that the Wink team has built. With 80 percent of Wink’s workload running on a unified stack of Kubernetes-Docker-CoreOS, the company has put itself in a position to continually innovate and improve its products and services. Committing to this technology, says Klein, "makes building on top of the infrastructure relatively&nbsp;easy.”
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"It’s not proprietary, it’s totally open, it’s really portable. You can run all the workloads across different cloud providers. You can easily run a hybrid AWS or even bring in your own data center. That’s the benefit of having everything unified on one open source Kubernetes-Docker-CoreOS Container Linux stack. There are massive security benefits if you only have one Linux distro/machine image to validate. The benefits are enormous because you save money, and you save time.”<br><br><span style="font-size:15px;letter-spacing:0.08em">- KIT KLEIN, HEAD OF ENGINEERING, WINK</span>
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<h2>How many people does it take to turn on a light bulb?</h2>
Kit Klein whips out his phone to demonstrate. With a few swipes, the head of engineering at Wink pulls up the smart-home app created by the New York City-based company and taps the light button. "Honestly when you’re holding the phone and you’re hitting the light,” he says, "by the time you feel the pressure of your finger on the screen, it’s on. It takes as long as the signal to travel to your brain.”<br><br>
Sure, it takes just one finger and less than 200 milliseconds to turn on the light – or lock a door or change a thermostat. But what allows Wink to help consumers manage their connected smart-home products with such speed and ease is a sophisticated, cloud native infrastructure that Klein and his team built and continue to develop using a unified stack of CoreOS, the open-source operating system designed for clustered deployments, and Kubernetes, an open-source platform for automating deployment, scaling, and operations of application containers across clusters of hosts, providing container-centric infrastructure. "When you have a big, complex network of interdependent microservices that need to be able to discover each other, and need to be horizontally scalable and tolerant to failure, that’s what this is really optimized for,” says Klein. "A lot of people end up relying on proprietary services [offered by some big cloud providers] to do some of this stuff, but what you get by adopting CoreOS/Kubernetes is portability, to not be locked in to anyone. You can really make your own fate.”<br><br>
Indeed, Wink did. The company’s mission statement is to make the connected home accessible – that is, user-friendly for non-technical owners, affordable and perhaps most importantly, reliable. "If you can’t trust that when you hit the switch, you know a light is going to go on, or if you’re remote and you’re checking on your house and that information isn’t accurate, then the convenience of the system is lost,” says Klein. "So that’s where the infrastructure comes in.”<br><br>
Wink was incubated within Quirky, a company that developed crowd-sourced inventions. The Wink app was first introduced in 2013, and at the time, it controlled only a few consumer products such as the PivotPower Strip that Quirky produced in collaboration with GE. As smart-home products proliferated, Wink was launched in 2014 in Home Depot stores nationwide. Its first project: a hub that could integrate with smart products from about a dozen brands like Honeywell and Chamberlain. The biggest challenge would be to build the infrastructure to serve all those communications between the hub and the products, with a focus on maximizing reliability and minimizing latency.<br><br>
"When we originally started out, we were moving very fast trying to get the first product to market, the minimum viable product,” says Klein. "Lots of times you go down a path and end up having to backtrack and try different things. But in this particular case, we did a lot of the work up front, which led to us making a really sound decision to deploy it on CoreOS Container Linux. And that was very early in the life of it.”
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"...what you get by adopting CoreOS/Kubernetes is portability, to not be locked in to anyone. You can really make your own fate.”
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Concern number one: Wink’s products need to connect to consumer devices in people’s homes, behind a firewall. "You don’t have an end point like a URL, and you don’t even know what ports are open behind that firewall,” Klein explains. "So you essentially need to have this thing wake up and talk to your system and then open real-time, bidirectional communication between the cloud and the device. And it’s really, really important that it’s persistent because you want to decrease as much as possible the overhead of sending a message – you never know when someone is going to turn on the lights.”<br><br>
With the earliest version of the Wink Hub, when you decided to turn your lights on or off, the request would be sent to the cloud and then executed. Subsequent updates to Wink’s software enabled local control, cutting latency down to about 10 milliseconds for many devices. But with the need for cloud-enabled integrations of an ever-growing ecosystem of smart home products, low-latency internet connectivity is still a critical consideration.
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<h2>"You essentially need to have this thing wake up and talk to your system and then open real-time, bidirectional communication between the cloud and the device. And it’s really, really important that it’s persistent...you never know when someone is going to turn on the&nbsp;lights.”</h2>
In addition, Wink had other requirements: horizontal scalability, the ability to encrypt everything quickly, connections that could be easily brought back up if something went wrong. "Looking at this whole structure we started, we decided to make a secure socket-based service,” says Klein. "We’ve always used, I would say, some sort of clustering technology to deploy our services and so the decision we came to was, this thing is going to be containerized, running on Docker.”<br><br>
At the time – just over two years ago – Docker wasn’t yet widely used, but as Klein points out, "it was certainly understood by the people who were on the frontier of technology. We started looking at potential technologies that existed. One of the limiting factors was that we needed to deploy multi-port non-http/https services. It wasn’t really appropriate for some of the early cluster technology. We liked the project a lot and we ended up using it on other stuff for a while, but initially it was too targeted toward http workloads.”<br><br>
Once Wink’s backend engineering team decided on a Dockerized workload, they had to make decisions about the OS and the container orchestration platform. "Obviously you can’t just start the containers and hope everything goes well,” Klein says with a laugh. "You need to have a system that is helpful [in order] to manage where the workloads are being distributed out to. And when the container inevitably dies or something like that, to restart it, you have a load balancer. All sorts of housekeeping work is needed to have a robust infrastructure.”
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"Obviously you can’t just start the containers and hope everything goes well,” Klein says with a laugh. "You need to have a system that is helpful [in order] to manage where the workloads are being distributed out to. And when the container inevitably dies or something like that, to restart it, you have a load balancer. All sorts of housekeeping work is needed to have a robust infrastructure.”
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Wink considered building directly on a general purpose Linux distro like Ubuntu (which would have required installing tools to run a containerized workload) and cluster management systems like Mesos (which was targeted toward enterprises with larger teams/workloads), but ultimately set their sights on CoreOS Container Linux. "A container-optimized Linux distribution system was exactly what we needed,” he says. "We didn’t have to futz around with trying to take something like a Linux distro and install everything. It’s got a built-in container orchestration system, which is Fleet, and an easy-to-use API. It’s not as feature-rich as some of the heavier solutions, but we realized that, at that moment, it was exactly what we needed.”<br><br>
Wink’s hub (along with a revamped app) was introduced in July 2014 with a short-term deployment, and within the first month, they had moved the service to the Dockerized CoreOS deployment. Since then, they’ve moved almost every other piece of their infrastructure – from third-party cloud-to-cloud integrations to their customer service and payment portals – onto CoreOS Container Linux clusters. <br><br>
Using this setup did require some customization. "Fleet is really nice as a basic container orchestration system, but it doesn’t take care of routing, sharing configurations, secrets, et cetera, among instances of a service,” Klein says. "All of those layers of functionality can be implemented, of course, but if you don’t want to spend a lot of time writing unit files manually – which of course nobody does – you need to create a tool to automate some of that, which we did.”<br><br>
Wink quickly embraced the Kubernetes container cluster manager when it was launched in 2015 and integrated with CoreOS core technology, and as promised, it ended up providing the features Wink wanted and had planned to build. "If not for Kubernetes, we likely would have taken the logic and library we implemented for the automation tool that we created, and would have used it in a higher level abstraction and tool that could be used by non-DevOps engineers from the command line to create and manage clusters,” Klein says. "But Kubernetes made that totally unnecessary – and is written and maintained by people with a lot more experience in cluster management than us, so all the better.” Now, an estimated 80 percent of Wink’s workload is run on Kubernetes on top of CoreOS Container Linux.
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"Stay close to the development. Understand why decisions are being made. If you understand the intent behind the project, from the technological intent to a certain philosophical intent, then it helps you understand how to build your system in harmony with those systems as opposed to trying to work against it.”
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Wink’s reasons for going all in are clear: "It’s not proprietary, it’s totally open, it’s really portable,” Klein says. "You can run all the workloads across different cloud providers. You can easily run a hybrid AWS or even bring in your own data center. That’s the benefit of having everything unified on one Kubernetes-Docker-CoreOS Container Linux stack. There are massive security benefits if you only have one Linux distro to try to validate. The benefits are enormous because you save money, you save time.”<br><br>
Klein concedes that there are tradeoffs in every technology decision. "Cutting-edge technology is going to be scary for some people,” he says. "In order to take advantage of this, you really have to keep up with the technology. You can’t treat it like it’s a black box. Stay close to the development. Understand why decisions are being made. If you understand the intent behind the project, from the technological intent to a certain philosophical intent, then it helps you understand how to build your system in harmony with those systems as opposed to trying to work against it.”<br><br>
Wink, which was acquired by Flex in 2015, now controls 2.3 million connected devices in households all over the country. What’s next for the company? A new version of the hub - Wink Hub 2 - hit shelves last November – and is being offered for the first time at Walmart stores in addition to Home Depot. "Two of the biggest American retailers are carrying and promoting the brand and the hardware,” Klein says proudly – though he adds that "it really comes with a lot of pressure. It’s not a retail situation where you have a lot of tech enthusiasts. These are everyday people who want something that works and have no tolerance for technical excuses.” And that’s further testament to how much faith Klein has in the infrastructure that the Wink team has have built.<br><br>
Wink’s engineering team has grown exponentially since its early days, and behind the scenes, Klein is most excited about the machine learning Wink is using. "We built [a system of] containerized small sections of the data pipeline that feed each other and can have multiple outputs,” he says. "It’s like data pipelines as microservices.” Again, Klein points to having a unified stack running on CoreOS Container Linux and Kubernetes as the primary driver for the innovations to come. "You’re not reinventing the wheel every time,” he says. "You can just get down to work.” </div>
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<h1> CASE STUDY:<img src="/images/zalando_logo.png" class="header_logo"><br> <div class="subhead">Europe’s Leading Online Fashion Platform Gets Radical with Cloud Native
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Company &nbsp;<b>Zalando</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Location &nbsp;<b>Berlin, Germany</b>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Industry &nbsp;<b>Online Fashion</b>
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<h2>Challenge</h2>
Zalando, Europe’s leading online fashion platform, has experienced exponential growth since it was founded in 2008. In 2015, with plans to further expand its original e-commerce site to include new services and products, Zalando embarked on a <a href="https://jobs.zalando.com/tech/blog/radical-agility-study-notes/">radical transformation</a> resulting in autonomous self-organizing teams. This change requires an infrastructure that could scale with the growth of the engineering organization. Zalando’s technology department began rewriting its applications to be cloud-ready and started moving its infrastructure from on-premise data centers to the cloud. While orchestration wasn’t immediately considered, as teams migrated to <a href="https://aws.amazon.com/">Amazon Web Services</a> (AWS): "We saw the pain teams were having with infrastructure and Cloud Formation on AWS," says Henning Jacobs, Head of Developer Productivity. "There’s still too much operational overhead for the teams and compliance. " To provide better support, cluster management was brought into play.
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The company now runs its Docker containers on AWS using Kubernetes orchestration.
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With the old infrastructure "it was difficult to properly embrace new technologies, and DevOps teams were considered to be a bottleneck," says Jacobs. "Now, with this cloud infrastructure, they have this packaging format, which can contain anything that runs on the Linux kernel. This makes a lot of people pretty happy. The engineers love autonomy."
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"We envision all Zalando delivery teams running their containerized applications on a state-of-the-art, reliable and scalable cluster infrastructure provided by Kubernetes."<br style="height:25px"><span style="font-size:14px;letter-spacing:2px;text-transform:uppercase;margin-top:5% !important;"><br>- Henning Jacobs, Head of Developer Productivity at Zalando</span>
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<h2>When Henning Jacobs arrived at Zalando in 2010, the company was just two years old with 180 employees running an online store for European shoppers to buy fashion items.</h2>
"It started as a PHP e-commerce site which was easy to get started with, but was not scaling with the business' needs" says Jacobs, Head of Developer Productivity at Zalando.<br><br>
At that time, the company began expanding beyond its German origins into other European markets. Fast-forward to today and Zalando now has more than 14,000 employees, 3.6 billion Euro in revenue for 2016 and operates across 15 countries. "With growth in all dimensions, and constant scaling, it has been a once-in-a-lifetime experience," he says.<br><br>
Not to mention a unique opportunity for an infrastructure specialist like Jacobs. Just after he joined, the company began rewriting all their applications in-house. "That was generally our strategy," he says. "For example, we started with our own logistics warehouses but at first you don’t know how to do logistics software, so you have some vendor software. And then we replaced it with our own because with off-the-shelf software you’re not competitive. You need to optimize these processes based on your specific business needs."<br><br>
In parallel to rewriting their applications, Zalando had set a goal of expanding beyond basic e-commerce to a platform offering multi-tenancy, a dramatic increase in assortments and styles, same-day delivery and even <a href="https://www.zalon.de">your own personal online stylist</a>.<br><br>
The need to scale ultimately led the company on a cloud-native journey. As did its embrace of a microservices-based software architecture that gives engineering teams more autonomy and ownership of projects. "This move to the cloud was necessary because in the data center you couldn’t have autonomous teams. You have the same infrastructure and it was very homogeneous, so you could only run your Java or Python app," Jacobs says.
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"This move to the cloud was necessary because in the data center you couldn’t have autonomous teams. You have the same infrastructure and it was very homogeneous, so you could only run your Java or Python app."
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Zalando began moving its infrastructure from two on-premise data centers to the cloud, requiring the migration of older applications for cloud-readiness. "We decided to have a clean break," says Jacobs. "Our <a href="https://aws.amazon.com/">Amazon Web Services</a> infrastructure was set up like so: Every team has its own AWS account, which is completely isolated, meaning there’s no ‘lift and shift.’ You basically have to rewrite your application to make it cloud-ready even down to the persistence layer. We bravely went back to the drawing board and redid everything, first choosing Docker as a common containerization, then building the infrastructure from there."<br><br>
The company decided to hold off on orchestration at the beginning, but as teams were migrated to AWS, "we saw the pain teams were having with infrastructure and cloud formation on AWS," says Jacobs. <br><br>
Zalandos 200+ autonomous engineering teams decide what technologies to use and could operate their own applications using their own AWS accounts. This setup proved to be a compliance challenge. Even with strict rules-of-play and automated compliance checks in place, engineering teams and IT-compliance were overburdened addressing compliance issues. "Violations appear for non-compliant behavior, which we detect when scanning the cloud infrastructure," says Jacobs. "Everything is possible and nothing enforced, so you have to live with violations (and resolve them) instead of preventing the error in the first place. This means overhead for teams—and overhead for compliance and operations. It also takes time to spin up new EC2 instances on AWS, which affects our deployment velocity." <br><br>
The team realized they needed to "leverage the value you get from cluster management," says Jacobs. When they first looked at Platform as a Service (PaaS) options in 2015, the market was fragmented; but "now there seems to be a clear winner. It seemed like a good bet to go with Kubernetes."<br><br>
The transition to Kubernetes started in 2016 during Zalando’s <a href="https://jobs.zalando.com/tech/blog/hack-week-5-is-live/?gh_src=4n3gxh1">Hack Week</a> where participants deployed their projects to a Kubernetes cluster. From there 60 members of the tech infrastructure department were on-boarded - and then engineering teams were brought on one at a time. "We always start by talking with them and make sure everyone’s expectations are clear," says Jacobs. "Then we conduct some Kubernetes training, which is mostly training for our CI/CD setup, because the user interface for our users is primarily through the CI/CD system. But they have to know fundamental Kubernetes concepts and the API. This is followed by a weekly sync with each team to check their progress. Once they have something in production, we want to see if everything is fine on top of what we can improve."
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Once Zalando began migrating applications to Kubernetes, the results were immediate. "Kubernetes is a cornerstone for our seamless end-to-end developer experience. We are able to ship ideas to production using a single consistent and declarative API," says Jacobs.
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At the moment, Zalando is running an initial 40 Kubernetes clusters with plans to scale for the foreseeable future.
Once Zalando began migrating applications to Kubernetes, the results were immediate. "Kubernetes is a cornerstone for our seamless end-to-end developer experience. We are able to ship ideas to production using a single consistent and declarative API," says Jacobs. "The self-healing infrastructure provides a frictionless experience with higher-level abstractions built upon low-level best practices. We envision all Zalando delivery teams will run their containerized applications on a state-of-the-art reliable and scalable cluster infrastructure provided by Kubernetes."<br><br>
With the old on-premise infrastructure "it was difficult to properly embrace new technologies, and DevOps teams were considered to be a bottleneck," says Jacobs. "Now, with this cloud infrastructure, they have this packaging format, which can contain anything that runs in the Linux kernel. This makes a lot of people pretty happy. The engineers love the autonomy."
There were a few challenges in Zalando’s Kubernetes implementation. "We are a team of seven people providing clusters to different engineering teams, and our goal is to provide a rock-solid experience for all of them," says Jacobs. "We don’t want pet clusters. We don’t want to have to understand what workload they have; it should just work out of the box. With that in mind, cluster autoscaling is important. There are many different ways of doing cluster management, and this is not part of the core. So we created two components to provision clusters, have a registry for clusters, and to manage the whole cluster life cycle."<br><br>
Jacobs’s team also worked to improve the Kubernetes-AWS integration. "Thus you're very restricted. You need infrastructure to scale each autonomous team’s idea.""<br><br>
Plus, "there are still a lot of best practices missing," says Jacobs. The team, for example, recently solved a pod security policy issue. "There was already a concept in Kubernetes but it wasn’t documented, so it was kind of tricky," he says. The large Kubernetes community was a big help to resolve the issue. To help other companies start down the same path, Jacobs compiled his team’s learnings in a document called <a href="http://kubernetes-on-aws.readthedocs.io/en/latest/admin-guide/kubernetes-in-production.html">Running Kubernetes in Production</a>.
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"The Kubernetes API allows us to run applications in a cloud provider-agnostic way, which gives us the freedom to revisit IaaS providers in the coming years... We expect the Kubernetes API to be the global standard for PaaS infrastructure and are excited about the continued journey."
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In the end, Kubernetes made it possible for Zalando to introduce and maintain the new products the company envisioned to grow its platform. "<a href="https://www.zalon.de/">The fashion advice</a> product used Scala, and there were struggles to make this possible with our former infrastructure," says Jacobs. "It was a workaround, and that team needed more and more support from the platform team, just because they used different technologies. Now with Kubernetes, it’s autonomous. Whatever the workload is, that team can just go their way, and Kubernetes prevents other bottlenecks."<br><br>
Looking ahead, Jacobs sees Zalando’s new infrastructure as a great enabler for other things the company has in the works, from its new logistics software, to a platform feature connecting brands, to products dreamed up by data scientists. "One vision is if you watch the next James Bond movie and see the suit he’s wearing, you should be able to automatically order it, and have it delivered to you within an hour," says Jacobs. "It’s about connecting the full fashion sphere. This is definitely not possible if you have a bottleneck with everyone running in the same data center and thus very restricted. You need infrastructure to scale each autonomous team’s idea."<br><br>
For other companies considering this technology, Jacobs says he wouldn’t necessarily advise doing it exactly the same way Zalando did. "It’s okay to do so if you’re ready to fail at some things," he says. "You need to set the right expectations. Not everything will work. Rewriting apps and this type of organizational change can be disruptive. The first product we moved was critical. There were a lot of dependencies, and it took longer than expected. Maybe we should have started with something less complicated, less business critical, just to get our toes wet."<br><br>
But once they got to the other side "it was clear for everyone that there’s no big alternative," Jacobs adds. "The Kubernetes API allows us to run applications in a cloud provider-agnostic way, which gives us the freedom to revisit IaaS providers in the coming years. Zalando Technology benefits from migrating to Kubernetes as we are able to leverage our existing knowledge to create an engineering platform offering flexibility and speed to our engineers while significantly reducing the operational overhead. We expect the Kubernetes API to be the global standard for PaaS infrastructure and are excited about the continued journey."
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