+ CASE STUDY:
+
+
+
+ CASE STUDY:
Improving Performance and Morale with Cloud Native
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+
+
+
+ Company AdForm Location Copenhagen, Denmark Industry Adtech
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+ +
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+Challenge
+ Adform’s mission is to provide a secure and transparent full stack of advertising technology to enable digital ads across devices. The company has a large infrastructure: OpenStack-based private clouds running on 1,100 physical servers in 7 data centers around the world, 3 of which were opened in the past year. With the company’s growth, the infrastructure team felt that "our private cloud was not really flexible enough," says IT System Engineer Edgaras Apšega. "The biggest pain point is that our developers need to maintain their virtual machines, so rolling out technology and new software takes time. We were really struggling with our releases, and we didn’t have self-healing infrastructure." + + ++ +
Solution
+ The team, which had already been using Prometheus for monitoring, embraced Kubernetes and cloud native practices in 2017. "To start our Kubernetes journey, we had to adapt all our software, so we had to choose newer frameworks," says Apšega. "We also adopted the microservices way, so observability is much better because you can inspect the bug or the services separately." + + +
+
+
+
+Impact
+ "Kubernetes helps our business a lot because our features are coming to market faster," says Apšega. The release process went from several hours to several minutes. Autoscaling has been at least 6 times faster than the semi-manual VM bootstrapping and application deployment required before. The team estimates that the company has experienced cost savings of 4-5x due to less hardware and fewer man hours needed to set up the hardware and virtual machines, metrics, and logging. Utilization of the hardware resources has been reduced as well, with containers notching 2-3 times more efficiency over virtual machines. "The deployments are very easy because developers just push the code and it automatically appears on Kubernetes," says Apšega. Prometheus has also had a positive impact: "It provides high availability for metrics and alerting. We monitor everything starting from hardware to applications. Having all the metrics in Grafana dashboards provides great insight on your systems." + + +
+
+In that same spirit, Adform is sharing its cloud native journey. "When you see that everyone shares their best practices, it inspires you to contribute back to the project," says IT Systems Engineer Edgaras Apšega.
+The company has a large infrastructure: OpenStack-based private clouds running on 1,100 physical servers in their own seven data centers around the world, three of which were opened in the past year. With the company’s growth, the infrastructure team felt that "our private cloud was not really flexible enough," says Apšega. "The biggest pain point is that our developers need to maintain their virtual machines, so rolling out technology and new software really takes time. We were really struggling with our releases, and we didn’t have self-healing infrastructure." + + +
+Adform made headlines last year when it detected the HyphBot ad fraud network that was costing some businesses hundreds of thousands of dollars a day.
With its mission to provide a secure and transparent full stack of advertising technology to enable an open internet, Adform published a white paper revealing what it did—and others could too—to limit customers’ exposure to the scam.+In that same spirit, Adform is sharing its cloud native journey. "When you see that everyone shares their best practices, it inspires you to contribute back to the project," says IT Systems Engineer Edgaras Apšega.
+The company has a large infrastructure: OpenStack-based private clouds running on 1,100 physical servers in their own seven data centers around the world, three of which were opened in the past year. With the company’s growth, the infrastructure team felt that "our private cloud was not really flexible enough," says Apšega. "The biggest pain point is that our developers need to maintain their virtual machines, so rolling out technology and new software really takes time. We were really struggling with our releases, and we didn’t have self-healing infrastructure." + + +
+
+The team, which had already been using Prometheus for monitoring, embraced Kubernetes, microservices, and cloud native practices. "The fact that Cloud Native Computing Foundation incubated Kubernetes was a really big point for us because it was vendor neutral," says Apšega. "And we can see that a community really gathers around it."
+A proof of concept project was started, with a Kubernetes cluster running on bare metal in the data center. When developers saw how quickly containers could be spun up compared to the virtual machine process, "they wanted to ship their containers in production right away, and we were still doing proof of concept," says IT Systems Engineer Andrius Cibulskis. +Of course, a lot of work still had to be done. "First of all, we had to learn Kubernetes, see all of the moving parts, how they glue together," says Apšega. "Second of all, the whole CI/CD part had to be redone, and our DevOps team had to invest more man hours to implement it. And third is that developers had to rewrite the code, and they’re still doing it." +
+The first production cluster was launched in the spring of 2018, and is now up to 20 physical machines dedicated for pods throughout three data centers, with plans for separate clusters in the other four data centers. The user-facing Adform application platform, data distribution platform, and back ends are now all running on Kubernetes. "Many APIs for critical applications are being developed for Kubernetes," says Apšega. "Teams are rewriting their applications to .NET core, because it supports containers, and preparing to move to Kubernetes. And new applications, by default, go in containers." + + +
++A proof of concept project was started, with a Kubernetes cluster running on bare metal in the data center. When developers saw how quickly containers could be spun up compared to the virtual machine process, "they wanted to ship their containers in production right away, and we were still doing proof of concept," says IT Systems Engineer Andrius Cibulskis. +Of course, a lot of work still had to be done. "First of all, we had to learn Kubernetes, see all of the moving parts, how they glue together," says Apšega. "Second of all, the whole CI/CD part had to be redone, and our DevOps team had to invest more man hours to implement it. And third is that developers had to rewrite the code, and they’re still doing it." +
+The first production cluster was launched in the spring of 2018, and is now up to 20 physical machines dedicated for pods throughout three data centers, with plans for separate clusters in the other four data centers. The user-facing Adform application platform, data distribution platform, and back ends are now all running on Kubernetes. "Many APIs for critical applications are being developed for Kubernetes," says Apšega. "Teams are rewriting their applications to .NET core, because it supports containers, and preparing to move to Kubernetes. And new applications, by default, go in containers." + + +
+This big push has been driven by the real impact that these new practices have had. "Kubernetes helps our business a lot because our features are coming to market faster," says Apšega. "The deployments are very easy because developers just push the code and it automatically appears on Kubernetes." The release process went from several hours to several minutes. Autoscaling is at least six times faster than the semi-manual VM bootstrapping and application deployment required before.
+The team estimates that the company has experienced cost savings of 4-5x due to less hardware and fewer man hours needed to set up the hardware and virtual machines, metrics, and logging. Utilization of the hardware resources has been reduced as well, with containers notching two to three times more efficiency over virtual machines.
+Prometheus has also had a positive impact: "It provides high availability for metrics and alerting," says Apšega. "We monitor everything starting from hardware to applications. Having all the metrics in Grafana dashboards provides great insight on our systems." + + + +
+
+
+
++The team estimates that the company has experienced cost savings of 4-5x due to less hardware and fewer man hours needed to set up the hardware and virtual machines, metrics, and logging. Utilization of the hardware resources has been reduced as well, with containers notching two to three times more efficiency over virtual machines.
+Prometheus has also had a positive impact: "It provides high availability for metrics and alerting," says Apšega. "We monitor everything starting from hardware to applications. Having all the metrics in Grafana dashboards provides great insight on our systems." + + + +
+All of these benefits have trickled down to individual team members, whose working lives have been changed for the better. "They used to have to get up at night to re-start some services, and now Kubernetes handles all of that," says Apšega. Adds Cibulskis: "Releases are really nice for them, because they just push their code to Git and that’s it. They don’t have to worry about their virtual machines anymore." Even the security teams have been impacted. "Security teams are always not happy," says Apšega, "and now they’re happy because they can easily inspect the containers."
+The company plans to remain in the data centers for now, "mostly because we want to keep all the data, to not share it in any way," says Cibulskis, "and it’s cheaper at our scale." But, Apšega says, the possibility of using a hybrid cloud for computing is intriguing: "One of the projects we’re interested in is the Virtual Kubelet that lets you spin up the working nodes on different clouds to do some computing."
+
+Apšega, Cibulskis and their colleagues are keeping tabs on how the cloud native ecosystem develops, and are excited to contribute where they can. "I think that our company just started our cloud native journey," says Apšega. "It seems like a huge road ahead, but we’re really happy that we joined it." + + + +
+
++Apšega, Cibulskis and their colleagues are keeping tabs on how the cloud native ecosystem develops, and are excited to contribute where they can. "I think that our company just started our cloud native journey," says Apšega. "It seems like a huge road ahead, but we’re really happy that we joined it." + + + +
+ CASE STUDY:
+
+ CASE STUDY:
Another Technical Evolution for a 30-Year-Old Company
+
+
+ Company Amadeus IT Group Location Madrid, Spain Industry Travel Technology
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+
+
+
+Challenge
+ 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. +
+
+
+Solution
+ Mountain has been overseeing the company’s migration to Kubernetes, using OpenShift Container Platform, Red Hat’s enterprise container platform. ++
Impact
+ 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." +
+
+ 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.
+ 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."
+ 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."
+
+In his two decades at Amadeus, Eric Mountain has been the migrations guy.
+ 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."+ 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.
+ 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."
+ 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."
+
+ 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 Python and databases like Couchbase, 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.
+
+ 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 Kubernetes whatever happens to be missing from our point of view, or go with OpenShift and build whatever remains there." +
+ 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. +
+ Ultimately, they went with OpenShift Container Platform, Red Hat’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." +
+ 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." +
++ 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 Kubernetes whatever happens to be missing from our point of view, or go with OpenShift and build whatever remains there." +
+ 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. +
+ Ultimately, they went with OpenShift Container Platform, Red Hat’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." +
+ 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." +
+ 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 Prometheus 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."
+
+ 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." +
+ 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." +
+ 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." +
++ 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." +
+ 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." +
+ 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." +
+ 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?"
+
+ "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." +
+ 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." +
+ 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." +
+ 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." +
++ "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." +
+ 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." +
+ 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." +
+ 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." +
+ CASE STUDY:
+
+
+
+ CASE STUDY:
Digging Into the Past With New Technology
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+
+ Company Ancestry Location Lehi, Utah Industry Internet Company, Online Services
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+
+ +
+
+Challenge
+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. Ancestry 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, ancestry.com, 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 products." + ++ +
+
+
+
+Solution
+ + The company is transitioning to cloud native infrastructure, using Docker containerization, Kubernetes orchestration and Prometheus for cluster monitoring.+
+
Impact
+ "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." +
+
+ So when the company decided to begin moving its infrastructure to cloud native technology, the first service that was launched on Kubernetes, 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."
+ 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."
+ 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." +
+It started with a Shaky Leaf.
+ + 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.+ So when the company decided to begin moving its infrastructure to cloud native technology, the first service that was launched on Kubernetes, 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."
+ 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."
+ 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." +
+ That need led them in 2015 to explore containerization. Ancestry engineers had already been using technology like Java and Python 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.
+ His team looked at orchestration platforms offered by Docker Compose, Mesos and OpenStack, 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."
+
+ 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."
+ 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."
+ 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. +
+
++ His team looked at orchestration platforms offered by Docker Compose, Mesos and OpenStack, 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."
+
+ 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."
+ 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."
+ 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."
+ 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. +
+
+ 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."
+ 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."
+ 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."
+ 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." +
++ 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."
+ 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."
+ 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." +
+
+
+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."
+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."
+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 meetups 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." +
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."
+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.
+"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."
+He pauses. "So, yeah, I guess you can say I'm an evangelist for Kubernetes," he says. "But I'm not getting a tattoo!" + + +
++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."
+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 meetups 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." +
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."
+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.
+"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."
+He pauses. "So, yeah, I guess you can say I'm an evangelist for Kubernetes," he says. "But I'm not getting a tattoo!" + + +
+ CASE STUDY:
+
+
+
+ CASE STUDY:
Ant Financial’s Hypergrowth Strategy Using Kubernetes
+
+
+
+
+ Company Ant Financial Location Hangzhou, China Industry Financial Services
+
+
++
+
+
+
+
+
+Challenge
+ Officially founded in October 2014, Ant Financial originated from Alipay, the world’s largest online payment platform that launched in 2004. The company also offers numerous other services leveraging technology innovation. With the volume of transactions Alipay handles for its 900+ million users worldwide (through its local and global partners)—256,000 transactions per second at the peak of Double 11 Singles Day 2017, and total gross merchandise value of $31 billion for Singles Day 2018—not to mention that of its other services, Ant Financial faces “data processing challenge in a whole new way,” says Haojie Hang, who is responsible for Product Management for the Storage and Compute Group. “We see three major problems of operating at that scale: how to provide real-time compute, storage, and processing capability, for instance to make real-time recommendations for fraud detection; how to provide intelligence on top of this data, because there’s too much data and then we’re not getting enough insight; and how to apply security in the application level, in the middleware level, the system level, even the chip level.” In order to provide reliable and consistent services to its customers, Ant Financial embraced containers in early 2014, and soon needed an orchestration solution for the tens-of-thousands-of-node clusters in its data centers. + +Solution
+ After investigating several technologies, the team chose Kubernetes for orchestration, as well as a number of other CNCF projects, including Prometheus, OpenTracing, etcd and CoreDNS. “In late 2016, we decided that Kubernetes will be the de facto standard,” says Hang. “Looking back, we made the right bet on the right technology. But then we needed to move the production workload from the legacy infrastructure to the latest Kubernetes-enabled platform, and that took some time, because we are very careful in terms of reliability and consistency.” All core financial systems were containerized by November 2017, and the migration to Kubernetes is ongoing. ++
Impact
+ “We’ve seen at least tenfold in improvement in terms of the operations with cloud native technology, which means you can have tenfold increase in terms of output,” says Hang. Ant also provides its fully integrated financial cloud platform to business partners around the world, and hopes to power the next generation of digital banking with deep experience in service innovation and technology expertise. Hang says the team hasn’t begun to focus on optimizing the Kubernetes platform, either: “Because we’re still in the hyper growth stage, we’re not in a mode where we do cost saving yet.” +
+
+ Combine that with the operations of its other properties—such as the Huabei online credit system, Jiebei lending service, and the 350-million-user Ant Forest green energy mobile app—and Ant Financial faces “data processing challenge in a whole new way,” says Haojie Hang, who is responsible for Product Management for the Storage and Compute Group. “We see three major problems of operating at that scale: how to provide real-time compute, storage, and processing capability, for instance to make real-time recommendations for fraud detection; how to provide intelligence on top of this data, because there’s too much data and we’re not getting enough insight; and how to apply security in the application level, in the middleware level, the system level, even the chip level.” +
+ To address those challenges and provide reliable and consistent services to its customers, Ant Financial embraced Docker containerization in 2014. But they soon realized that they needed an orchestration solution for some tens-of-thousands-of-node clusters in the company’s data centers. +
+A spinoff of the multinational conglomerate Alibaba, Ant Financial boasts a $150+ billion valuation and the scale to match. The fintech startup, launched in 2014, is comprised of Alipay, the world’s largest online payment platform, and numerous other services leveraging technology innovation.
+ And the volume of transactions that Alipay handles for over 900 million users worldwide (through its local and global partners) is staggering: 256,000 per second at the peak of Double 11 Singles Day 2017, and total gross merchandise value of $31 billion for Singles Day 2018. With the mission of “bringing the world equal opportunities,” Ant Financial is dedicated to creating an open, shared credit system and financial services platform through technology innovations. ++ Combine that with the operations of its other properties—such as the Huabei online credit system, Jiebei lending service, and the 350-million-user Ant Forest green energy mobile app—and Ant Financial faces “data processing challenge in a whole new way,” says Haojie Hang, who is responsible for Product Management for the Storage and Compute Group. “We see three major problems of operating at that scale: how to provide real-time compute, storage, and processing capability, for instance to make real-time recommendations for fraud detection; how to provide intelligence on top of this data, because there’s too much data and we’re not getting enough insight; and how to apply security in the application level, in the middleware level, the system level, even the chip level.” +
+ To address those challenges and provide reliable and consistent services to its customers, Ant Financial embraced Docker containerization in 2014. But they soon realized that they needed an orchestration solution for some tens-of-thousands-of-node clusters in the company’s data centers. +
+ The team investigated several technologies, including Docker Swarm and Mesos. “We did a lot of POCs, but we’re very careful in terms of production systems, because we want to make sure we don’t lose any data,” says Hang. “You cannot afford to have a service downtime for one minute; even one second has a very, very big impact. We operate every day under pressure to provide reliable and consistent services to consumers and businesses in China and globally.”
+
+ Ultimately, Hang says Ant chose Kubernetes because it checked all the boxes: a strong community, technology that “will be relevant in the next three to five years,” and a good match for the company’s engineering talent. “In late 2016, we decided that Kubernetes will be the de facto standard,” says Hang. “Looking back, we made the right bet on the right technology. But then we needed to move the production workload from the legacy infrastructure to the latest Kubernetes-enabled platform. We spent a lot of time learning and then training our people to build applications on Kubernetes well.” +
+ All core financial systems were containerized by November 2017, and the migration to Kubernetes is ongoing. Ant’s platform also leverages a number of other CNCF projects, including Prometheus, OpenTracing, etcd and CoreDNS. “On Double 11 this year, we had plenty of nodes on Kubernetes, but compared to the whole scale of our infrastructure, this is still in progress,” says Ranger Yu, Global Technology Partnership & Development. +
++ Ultimately, Hang says Ant chose Kubernetes because it checked all the boxes: a strong community, technology that “will be relevant in the next three to five years,” and a good match for the company’s engineering talent. “In late 2016, we decided that Kubernetes will be the de facto standard,” says Hang. “Looking back, we made the right bet on the right technology. But then we needed to move the production workload from the legacy infrastructure to the latest Kubernetes-enabled platform. We spent a lot of time learning and then training our people to build applications on Kubernetes well.” +
+ All core financial systems were containerized by November 2017, and the migration to Kubernetes is ongoing. Ant’s platform also leverages a number of other CNCF projects, including Prometheus, OpenTracing, etcd and CoreDNS. “On Double 11 this year, we had plenty of nodes on Kubernetes, but compared to the whole scale of our infrastructure, this is still in progress,” says Ranger Yu, Global Technology Partnership & Development. +
+ Still, there has already been an impact. “Cloud native technology has benefited us greatly in terms of efficiency,” says Hang. “In general, we want to make sure our infrastructure is nimble and flexible enough for the work that could happen tomorrow. That’s the goal. And with cloud native technology, we’ve seen at least tenfold improvement in operations, which means you can have tenfold increase in terms of output. Let’s say you are operating 10 nodes with one person. With cloud native, tomorrow you can have 100 nodes.”
+
+ Ant also provides its financial cloud platform to partners around the world, and hopes to power the next generation of digital banking with deep experience in service innovation and technology expertise. Hang says the team hasn’t begun to focus on optimizing the Kubernetes platform, either: “Because we’re still in the hyper growth stage, we’re not in a mode where we do cost-saving yet.” +
+ The CNCF community has also been a valuable asset during Ant Financial’s move to cloud native. “If you are applying a new technology, it’s very good to have a community to discuss technical problems with other users,” says Hang. “We’re very grateful for CNCF and this amazing technology, which we need as we continue to scale globally. We’re definitely embracing the community and open sourcing more in the future.” +
+
+
+
++ Ant also provides its financial cloud platform to partners around the world, and hopes to power the next generation of digital banking with deep experience in service innovation and technology expertise. Hang says the team hasn’t begun to focus on optimizing the Kubernetes platform, either: “Because we’re still in the hyper growth stage, we’re not in a mode where we do cost-saving yet.” +
+ The CNCF community has also been a valuable asset during Ant Financial’s move to cloud native. “If you are applying a new technology, it’s very good to have a community to discuss technical problems with other users,” says Hang. “We’re very grateful for CNCF and this amazing technology, which we need as we continue to scale globally. We’re definitely embracing the community and open sourcing more in the future.” +
+ In fact, the company has already started to open source some of its cloud native middleware. “We are going to be very proactive about that,” says Yu. “CNCF provided a platform so everyone can plug in or contribute components. This is very good open source governance.”
+
+ Looking ahead, the Ant team will continue to evaluate many other CNCF projects. Building a service mesh community in China, the team has brought together many China-based companies and developers to discuss the potential of that technology. “Service mesh is very attractive for Chinese developers and end users because we have a lot of legacy systems running now, and it’s an ideal mid-layer to glue everything together, both new and legacy,” says Hang. “For new technologies, we look very closely at whether they will last.” +
+ At Ant, Kubernetes passed that test with flying colors, and the team hopes other companies will follow suit. “In China, we are the North Star in terms of innovation in financial and other related services,” says Hang. “We definitely want to make sure we’re still leading in the next 5 to 10 years with our investment in technology.” + +
++ Looking ahead, the Ant team will continue to evaluate many other CNCF projects. Building a service mesh community in China, the team has brought together many China-based companies and developers to discuss the potential of that technology. “Service mesh is very attractive for Chinese developers and end users because we have a lot of legacy systems running now, and it’s an ideal mid-layer to glue everything together, both new and legacy,” says Hang. “For new technologies, we look very closely at whether they will last.” +
+ At Ant, Kubernetes passed that test with flying colors, and the team hopes other companies will follow suit. “In China, we are the North Star in terms of innovation in financial and other related services,” says Hang. “We definitely want to make sure we’re still leading in the next 5 to 10 years with our investment in technology.” + +
+ CASE STUDY:
+
+
+
+ CASE STUDY:
AppDirect: How AppDirect Supported the 10x Growth of Its Engineering Staff with Kubernetess
+
+
+
+ Company AppDirect Location San Francisco, California
+ Industry Software
+
+
++
+
+
+
+
+
+Challenge
+ AppDirect provides an end-to-end commerce platform for cloud-based products and services. When Director of Software Development Pierre-Alexandre Lacerte began working there in 2014, the company had a monolith application deployed on a "tomcat infrastructure, and the whole release process was complex for what it should be," he says. "There were a lot of manual steps involved, with one engineer building a feature, then another team picking up the change. So you had bottlenecks in the pipeline to ship a feature to production." At the same time, the engineering team was growing, and the company realized it needed a better infrastructure to both support that growth and increase velocity. ++
Solution
+ "My idea was: Let’s create an environment where teams can deploy their services faster, and they will say, ‘Okay, I don’t want to build in the monolith anymore. I want to build a service,’" says Lacerte. They considered and prototyped several different technologies before deciding to adopt Kubernetes in early 2016. Lacerte’s team has also integrated Prometheus monitoring into the platform; tracing is next. Today, AppDirect has more than 50 microservices in production and 15 Kubernetes clusters deployed on AWS and on premise around the world. ++
Impact
+ The Kubernetes platform has helped support the engineering team’s 10x growth over the past few years. Coupled with the fact that they were continually adding new features, Lacerte says, "I think our velocity would have slowed down a lot if we didn’t have this new infrastructure." Moving to Kubernetes and services has meant that deployments have become much faster due to less dependency on custom-made, brittle shell scripts with SCP commands. Time to deploy a new version has shrunk from 4 hours to a few minutes. Additionally, the company invested a lot of effort to make things self-service for developers. "Onboarding a new service doesn’t require Jira tickets or meeting with three different teams," says Lacerte. Today, the company sees 1,600 deployments per week, compared to 1-30 before. The company also achieved cost savings by moving its marketplace and billing monoliths to Kubernetes from legacy EC2 hosts as well as by leveraging autoscaling, as traffic is higher during business hours. +
+
+ When Director of Software Development Pierre-Alexandre Lacerte started working there in 2014, the company had a monolith application deployed on a "tomcat infrastructure, and the whole release process was complex for what it should be," he says. "There were a lot of manual steps involved, with one engineer building a feature then creating a pull request, and a QA or another engineer validating the feature. Then it gets merged and someone else will take care of the deployment. So we had bottlenecks in the pipeline to ship a feature to production."
+ At the same time, the engineering team of 40 was growing, and the company wanted to add an increasing number of features to its products. As a member of the platform team, Lacerte began hearing from multiple teams that wanted to deploy applications using different frameworks and languages, from Node.js to Spring Boot Java. He soon realized that in order to both support growth and increase velocity, the company needed a better infrastructure, and a system in which teams are autonomous, can do their own deploys, and be responsible for their services in production. + +
+With its end-to-end commerce platform for cloud-based products and services, AppDirect has been helping organizations such as Comcast and GoDaddy simplify the digital supply chain since 2009.
++ When Director of Software Development Pierre-Alexandre Lacerte started working there in 2014, the company had a monolith application deployed on a "tomcat infrastructure, and the whole release process was complex for what it should be," he says. "There were a lot of manual steps involved, with one engineer building a feature then creating a pull request, and a QA or another engineer validating the feature. Then it gets merged and someone else will take care of the deployment. So we had bottlenecks in the pipeline to ship a feature to production."
+ At the same time, the engineering team of 40 was growing, and the company wanted to add an increasing number of features to its products. As a member of the platform team, Lacerte began hearing from multiple teams that wanted to deploy applications using different frameworks and languages, from Node.js to Spring Boot Java. He soon realized that in order to both support growth and increase velocity, the company needed a better infrastructure, and a system in which teams are autonomous, can do their own deploys, and be responsible for their services in production. + +
+ From the beginning, Lacerte says, "My idea was: Let’s create an environment where teams can deploy their services faster, and they will say, ‘Okay, I don’t want to build in the monolith anymore. I want to build a service.’" (Lacerte left the company in 2019.)
+ Working with the operations team, Lacerte’s group got more control and access to the company’s AWS infrastructure, and started prototyping several orchestration technologies. "Back then, Kubernetes was a little underground, unknown," he says. "But we looked at the community, the number of pull requests, the velocity on GitHub, and we saw it was getting traction. And we found that it was much easier for us to manage than the other technologies." + They spun up the first few services on Kubernetes using Chef and Terraform provisioning, and as more services were added, more automation was, too. "We have clusters around the world—in Korea, in Australia, in Germany, and in the U.S.," says Lacerte. "Automation is critical for us." They’re now largely using Kops, and are looking at managed Kubernetes offerings from several cloud providers.
+ Today, though the monolith still exists, there are fewer and fewer commits and features. All teams are deploying on the new infrastructure, and services are the norm. AppDirect now has more than 50 microservices in production and 15 Kubernetes clusters deployed on AWS and on premise around the world.
+ Lacerte’s strategy ultimately worked because of the very real impact the Kubernetes platform has had to deployment time. Due to less dependency on custom-made, brittle shell scripts with SCP commands, time to deploy a new version has shrunk from 4 hours to a few minutes. Additionally, the company invested a lot of effort to make things self-service for developers. "Onboarding a new service doesn’t require Jira tickets or meeting with three different teams," says Lacerte. Today, the company sees 1,600 deployments per week, compared to 1-30 before. +
++ Working with the operations team, Lacerte’s group got more control and access to the company’s AWS infrastructure, and started prototyping several orchestration technologies. "Back then, Kubernetes was a little underground, unknown," he says. "But we looked at the community, the number of pull requests, the velocity on GitHub, and we saw it was getting traction. And we found that it was much easier for us to manage than the other technologies." + They spun up the first few services on Kubernetes using Chef and Terraform provisioning, and as more services were added, more automation was, too. "We have clusters around the world—in Korea, in Australia, in Germany, and in the U.S.," says Lacerte. "Automation is critical for us." They’re now largely using Kops, and are looking at managed Kubernetes offerings from several cloud providers.
+ Today, though the monolith still exists, there are fewer and fewer commits and features. All teams are deploying on the new infrastructure, and services are the norm. AppDirect now has more than 50 microservices in production and 15 Kubernetes clusters deployed on AWS and on premise around the world.
+ Lacerte’s strategy ultimately worked because of the very real impact the Kubernetes platform has had to deployment time. Due to less dependency on custom-made, brittle shell scripts with SCP commands, time to deploy a new version has shrunk from 4 hours to a few minutes. Additionally, the company invested a lot of effort to make things self-service for developers. "Onboarding a new service doesn’t require Jira tickets or meeting with three different teams," says Lacerte. Today, the company sees 1,600 deployments per week, compared to 1-30 before. +
+ Additionally, the Kubernetes platform has helped support the engineering team’s 10x growth over the past few years. "Ownership, a core value of AppDirect, reflects in our ability to ship services independently of our monolith code base," says Staff Software Developer Alexandre Gervais, who worked with Lacerte on the initiative. "Small teams now own critical parts of our business domain model, and they operate in their decoupled domain of expertise, with limited knowledge of the entire codebase. This reduces and isolates some of the complexity." Coupled with the fact that they were continually adding new features, Lacerte says, "I think our velocity would have slowed down a lot if we didn’t have this new infrastructure."
+ The company also achieved cost savings by moving its marketplace and billing monoliths to Kubernetes from legacy EC2 hosts as well as by leveraging autoscaling, as traffic is higher during business hours.
+ AppDirect’s cloud native stack also includes gRPC and Fluentd, and the team is currently working on setting up OpenCensus. The platform already has Prometheus integrated, so "when teams deploy their service, they have their notifications, alerts and configurations," says Lacerte. "For example, in the test environment, I want to get a message on Slack, and in production, I want a Slack message and I also want to get paged. We have integration with pager duty. Teams have more ownership on their services." + +
+
+
+
++ AppDirect’s cloud native stack also includes gRPC and Fluentd, and the team is currently working on setting up OpenCensus. The platform already has Prometheus integrated, so "when teams deploy their service, they have their notifications, alerts and configurations," says Lacerte. "For example, in the test environment, I want to get a message on Slack, and in production, I want a Slack message and I also want to get paged. We have integration with pager duty. Teams have more ownership on their services." + +
+ That of course also means more responsibility. "We asked engineers to expand their horizons," says Gervais. "We moved from a culture limited to ‘pushing code in a branch’ to exciting new responsibilities outside of the code base: deployment of features and configurations; monitoring of application and business metrics; and on-call support in case of outages. It was an immense engineering culture shift, but the benefits are undeniable in terms of scale and speed."
+ As the engineering ranks continue to grow, the platform team has a new challenge, of making sure that the Kubernetes platform is accessible and easily utilized by everyone. "How can we make sure that when we add more people to our team that they are efficient, productive, and know how to ramp up on the platform?" Lacerte says. So we have the evangelists, the documentation, some project examples. We do demos, we have AMA sessions. We’re trying different strategies to get everyone’s attention."
+ Three and a half years into their Kubernetes journey, Gervais feels AppDirect "made the right decisions at the right time," he says. "Kubernetes and the cloud native technologies are now seen as the de facto ecosystem. We know where to focus our efforts in order to tackle the new wave of challenges we face as we scale out. The community is so active and vibrant, which is a great complement to our awesome internal team. Going forward, our focus will really be geared towards benefiting from the ecosystem by providing added business value in our day-to-day operations." + + +
++ As the engineering ranks continue to grow, the platform team has a new challenge, of making sure that the Kubernetes platform is accessible and easily utilized by everyone. "How can we make sure that when we add more people to our team that they are efficient, productive, and know how to ramp up on the platform?" Lacerte says. So we have the evangelists, the documentation, some project examples. We do demos, we have AMA sessions. We’re trying different strategies to get everyone’s attention."
+ Three and a half years into their Kubernetes journey, Gervais feels AppDirect "made the right decisions at the right time," he says. "Kubernetes and the cloud native technologies are now seen as the de facto ecosystem. We know where to focus our efforts in order to tackle the new wave of challenges we face as we scale out. The community is so active and vibrant, which is a great complement to our awesome internal team. Going forward, our focus will really be geared towards benefiting from the ecosystem by providing added business value in our day-to-day operations." + + +
+ CASE STUDY:
+
+
+
+ CASE STUDY:
Turning to Containerization to Support Millions of Rideshares
+
+
+ Company BlaBlaCar Location Paris, France Industry Ridesharing Company
+
+
++
+
+
+
+
+
+
+Challenge
+ The world’s largest long-distance carpooling community, BlaBlaCar, 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. ++
+
Solution
+ 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 rkt, initially deployed using fleet cluster manager. Last year, the company switched to Kubernetes orchestration, and now also uses Prometheus for monitoring. +
+
+Impact
+ "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." +
+
+ By 2015, the company had about 50 bare metal servers. The team was using a MySQL database and PHP, but, Lallemand says, "it was a very static way." They also utilized the configuration management system, Chef, 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."
+ 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.
+ 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 CoreOS 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." +
+For the 40 million users of BlaBlaCar, 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.
+ 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."+ By 2015, the company had about 50 bare metal servers. The team was using a MySQL database and PHP, but, Lallemand says, "it was a very static way." They also utilized the configuration management system, Chef, 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."
+ 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.
+ 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 CoreOS 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." +
+ 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 Docker but decided to go with rkt. 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.
+ 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."
+ 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 dgr, 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 Nerve and Synapse; their versions, Go-Nerve and Go-Synapse, were written in Go and built to be more efficient and include new features. All of these tools were open-sourced.
+ 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."
+ 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." +
++ 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."
+ 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 dgr, 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 Nerve and Synapse; their versions, Go-Nerve and Go-Synapse, were written in Go and built to be more efficient and include new features. All of these tools were open-sourced.
+ 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."
+ 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." +
+ 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 fleet tool from CoreOS to deploy their containers. (They did build a tool called GGN, which they’ve open-sourced, to make it more manageable for their system engineers to use.)
+ 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 Kubernetes, which had just begun supporting rkt implementation.
+ 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 Prometheus, 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.
+ 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."
+ 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." +
++ 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 Kubernetes, which had just begun supporting rkt implementation.
+ 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 Prometheus, 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.
+ 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."
+ 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." +
+ 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."
+ 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."
+ 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."
+ 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."
+ 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." +
++ 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."
+ 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."
+ 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."
+ 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." +
+ CASE STUDY:
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+ CASE STUDY: 
+ Rolling Out Kubernetes in Production in 100 Days
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+ Company BlackRock Location New York, NY Industry Financial Services
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+Challenge
+ The world’s largest asset manager, BlackRock 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 Python notebooks, or even something much more advanced, like a MapReduce engine based on Spark," 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?" +
+
+
+Solution
+ Drawing from what they learned during a pilot done last year using Docker environments, Francis put together a cross-sectional team of 20 to build an investor research web app using Kubernetes with the goal of getting it into production within one quarter. ++
Impact
+ "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." + +
+ 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.
+ 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."
+ 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."
+ 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.
+ 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 Python notebooks, or even something much more advanced, like a MapReduce engine based on Spark," 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." +
++ 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."
+ 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."
+ 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.
+ 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 Python notebooks, or even something much more advanced, like a MapReduce engine based on Spark," 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." +
+ 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."
+ 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 Ansible 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."
+ 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 OpenShift 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."
+ 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?"
+ 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 Minikube and did a few small pushes back to the open source project. + + +
++ 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 Ansible 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."
+ 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 OpenShift 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."
+ 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?"
+ 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 Minikube and did a few small pushes back to the open source project. + + +
+ 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]?"
+ 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."
+ 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."
+ 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."
+ 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."
+ 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." + + +
++ 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."
+ 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."
+ 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."
+ 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."
+ 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." + + +
+ 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 Helm is one example]. People have similar problems."
+ 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.
+ 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."
+ 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." + +
++ 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.
+ 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."
+ 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." + +
+ CASE STUDY:
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+ CASE STUDY:
Bose: Supporting Rapid Development for Millions of IoT Products With Kubernetes
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+ Company Bose Corporation Location Framingham, Massachusetts
+ Industry Consumer Electronics
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+Challenge
+ A household name in high-quality audio equipment, Bose has offered connected products for more than five years, and as that demand grew, the infrastructure had to change to support it. "We needed to provide a mechanism for developers to rapidly prototype and deploy services all the way to production pretty fast,” says Lead Cloud Engineer Josh West. In 2016, the company decided to start building a platform from scratch. The primary goal: "To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale,” says Cloud Architecture Manager Dylan O’Mahony. ++
Solution
+ From the beginning, the team knew it wanted a microservices architecture. After evaluating and prototyping a couple of orchestration solutions, the team decided to adopt Kubernetes for its scaled IoT Platform-as-a-Service running on AWS. The platform, which also incorporated Prometheus monitoring, launched in production in 2017, serving over 3 million connected products from the get-go. Bose has since adopted a number of other CNCF technologies, including Fluentd, CoreDNS, Jaeger, and OpenTracing. ++
Impact
+ With about 100 engineers onboarded, the platform is now enabling 30,000 non-production deployments across dozens of microservices per year. In 2018, there were 1250+ production deployments. Just one production cluster holds 1,800 namespaces and 340 worker nodes. "We had a brand new service taken from concept through coding and deployment all the way to production, including hardening, security testing and so forth, in less than two and a half weeks,” says O’Mahony. +
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+In 2016, the company decided to start building an IoT platform from scratch. The primary goal: "To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale,” says Cloud Architecture Manager Dylan O’Mahony. "If they release a new connected product, we want to be already well ahead of being able to handle whatever scale that they’re going to throw at us.”
+From the beginning, the team knew it wanted a microservices architecture and platform as a service. After evaluating and prototyping orchestration solutions, including Mesos and Docker Swarm, the team decided to adopt Kubernetes for its platform running on AWS. Kubernetes was still in 1.5, but already the technology could do much of what the team wanted and needed for the present and the future. For West, that meant having storage and network handled. O’Mahony points to Kubernetes’ portability in case Bose decides to go multi-cloud.
+"Bose is a company that looks out for the long term,” says West. "Going with a quick commercial off-the-shelf solution might’ve worked for that point in time, but it would not have carried us forward, which is what we needed from Kubernetes and the CNCF.” + + +
+A household name in high-quality audio equipment, Bose has offered connected products for more than five years, and as that demand grew, the infrastructure had to change to support it.
+ "We needed to provide a mechanism for developers to rapidly prototype and deploy services all the way to production pretty fast,” says Lead Cloud Engineer Josh West. "There were a lot of cloud capabilities we wanted to provide to support our audio equipment and experiences.”+In 2016, the company decided to start building an IoT platform from scratch. The primary goal: "To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale,” says Cloud Architecture Manager Dylan O’Mahony. "If they release a new connected product, we want to be already well ahead of being able to handle whatever scale that they’re going to throw at us.”
+From the beginning, the team knew it wanted a microservices architecture and platform as a service. After evaluating and prototyping orchestration solutions, including Mesos and Docker Swarm, the team decided to adopt Kubernetes for its platform running on AWS. Kubernetes was still in 1.5, but already the technology could do much of what the team wanted and needed for the present and the future. For West, that meant having storage and network handled. O’Mahony points to Kubernetes’ portability in case Bose decides to go multi-cloud.
+"Bose is a company that looks out for the long term,” says West. "Going with a quick commercial off-the-shelf solution might’ve worked for that point in time, but it would not have carried us forward, which is what we needed from Kubernetes and the CNCF.” + + +
+ The team spent time working on choosing tooling to make the experience easier for developers. "Our developers interact with tools provided by our Ops team, and the Ops team run all of their tooling on top of Kubernetes,” says O’Mahony. "We try not to make direct Kubernetes access the only way. In fact, ideally, our developers wouldn’t even need to know that they’re running on Kubernetes.”
+ The platform, which also incorporated Prometheus monitoring from the beginning, backdoored its way into production in 2017, serving over 3 million connected products from the get-go. "Even though the speakers and the products that we were designing this platform for were still quite a ways away from being launched, we did have some connected speakers on the market,” says O’Mahony. "We basically started to point certain features of those speakers and the apps that go with those speakers to this platform.”
+ Today, just one of Bose’s production clusters holds 1,800 namespaces/discrete services and 340 nodes. With about 100 engineers now onboarded, the platform infrastructure is now enabling 30,000 non-production deployments across dozens of microservices per year. In 2018, there were 1250+ production deployments.. It’s a staggering improvement over some of Bose’s previous deployment processes, which supported far fewer deployments and services. + +
++ The platform, which also incorporated Prometheus monitoring from the beginning, backdoored its way into production in 2017, serving over 3 million connected products from the get-go. "Even though the speakers and the products that we were designing this platform for were still quite a ways away from being launched, we did have some connected speakers on the market,” says O’Mahony. "We basically started to point certain features of those speakers and the apps that go with those speakers to this platform.”
+ Today, just one of Bose’s production clusters holds 1,800 namespaces/discrete services and 340 nodes. With about 100 engineers now onboarded, the platform infrastructure is now enabling 30,000 non-production deployments across dozens of microservices per year. In 2018, there were 1250+ production deployments.. It’s a staggering improvement over some of Bose’s previous deployment processes, which supported far fewer deployments and services. + +
+ "We had a brand new service deployed from concept through coding and deployment all the way to production, including hardening, security testing and so forth, in less than two and a half weeks,” says O’Mahony. "Everybody thinks in terms of automation, leaning out the processes, getting things done as quickly as possible. When you step back and look at what it means for a 50-plus-year-old speaker company to have that sort of culture, it really is quite incredible, and I think the tools that we use and the foundation that we’ve built is a huge piece of that.”
+ Many of those technologies—such as Fluentd, CoreDNS, Jaeger, and OpenTracing—come from the CNCF Landscape, which West and O’Mahony have relied upon throughout Bose’s cloud native journey. "The CNCF Landscape quickly explains what’s going on in all the different areas from storage to cloud providers to automation and so forth,” says West. "This is our shopping cart to build a cloud infrastructure. We can go choose from the different aisles.”
+ And, he adds, "If it weren’t for Kubernetes and the rest of the CNCF projects being free open source software with such a strong community, we would never have achieved scale, or even gotten to launch on schedule.”
+ Another benefit of going cloud native: "We are even attracting much more talent into Bose because we’re so involved with the CNCF Landscape,” says West. (Yes, they’re hiring.) "It’s just enabled so many people to do so many great things and really brought Bose into the future of cloud.” + + +
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++ Many of those technologies—such as Fluentd, CoreDNS, Jaeger, and OpenTracing—come from the CNCF Landscape, which West and O’Mahony have relied upon throughout Bose’s cloud native journey. "The CNCF Landscape quickly explains what’s going on in all the different areas from storage to cloud providers to automation and so forth,” says West. "This is our shopping cart to build a cloud infrastructure. We can go choose from the different aisles.”
+ And, he adds, "If it weren’t for Kubernetes and the rest of the CNCF projects being free open source software with such a strong community, we would never have achieved scale, or even gotten to launch on schedule.”
+ Another benefit of going cloud native: "We are even attracting much more talent into Bose because we’re so involved with the CNCF Landscape,” says West. (Yes, they’re hiring.) "It’s just enabled so many people to do so many great things and really brought Bose into the future of cloud.” + + +
+ In the coming year, the team wants to work on service mesh and serverless, as well as expansion around the world. "Getting our latency down by going multi-region is going to be a big focus for us,” says O’Mahony. "In order to make sure that our customers in Japan, Australia, and everywhere else are having a good experience, we want to have points of presence closer to them. It’s never been done at Bose before.”
+ That won’t stop them, because the team is all about lofty goals. "We want to get to billions of connected products!” says West. "We have a lot going on to support many more of our business units at Bose in addition to the consumer electronics division, which we currently do. It’s only because of the cloud native landscape and the tools and the features that are available that we can provide such a fantastic cloud platform for all the developers and divisions that are trying to enable some pretty amazing experiences.”
+ In fact, given the scale the platform is already supporting, says O’Mahony, "doing anything other than Kubernetes, I think, would be folly at this point.” + + +
++ That won’t stop them, because the team is all about lofty goals. "We want to get to billions of connected products!” says West. "We have a lot going on to support many more of our business units at Bose in addition to the consumer electronics division, which we currently do. It’s only because of the cloud native landscape and the tools and the features that are available that we can provide such a fantastic cloud platform for all the developers and divisions that are trying to enable some pretty amazing experiences.”
+ In fact, given the scale the platform is already supporting, says O’Mahony, "doing anything other than Kubernetes, I think, would be folly at this point.” + + +