Add Buffer case study. Updates to Ancestry and Wink case study. Updates to Case Study index. Sizes fixes from logo images. (#4568)

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Kaitlyn Barnard
2017-08-01 11:44:09 -07:00
committed by Andrew Chen
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title: Ancestry Case Study
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<title>Ancestry Case Study</title>
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<h1> CASE STUDY:<img src="http://c.mfcreative.com/i/logo/ancestry-on-dark.svg" class="logo" width="22%" style="margin-bottom:-12px;margin-left:3px;"><br> <div class="subhead">Digging Into the Past With New Technology</div></h1>
<h1> CASE STUDY:<img src="http://c.mfcreative.com/i/logo/ancestry-on-dark.svg" width="22%" style="margin-bottom:-12px;margin-left:3px;"><br> <div class="subhead">Digging Into the Past With New Technology</div></h1>
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<h2>Impact</h2>
"Every single product, every decision we make at Ancestry, focuses on delighting our customers with intimate, sometimes life-changing discoveries about themselves and their families," says MacKay. "As the company continues to grow, the increased productivity gains from using Kubernetes has helped Ancestry make customer discoveries faster. With the move to Dockerization for example, instead of taking between 20 to 50 minutes to deploy a new piece of code, we can now deploy in under a minute for much of our code. Weve truly experienced a significant time savings in addition to the various features and benefits from cloud native and Kubernetes-type technologies."
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<h2>It started with a Shaky Leaf.</h2>
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And when it went live smoothly in early 2016, "our deployment time for this service literally was cut down from 50 minutes to 2 or 5 minutes," MacKay adds. "The development team was just thrilled because we're focused on supplying a great experience for our customers. And that means features, it means stability, it means all those things that we need for a first-in-class type operation."<br><br>
The stability of that Shaky Leaf was a signal for MacKay and his team that their decision to embrace cloud native technologies was the right one for the company. With a private data center, Ancestry built its website (which launched in 1996) on hundreds of services and technologies and a traditional deployment methodology. "It worked well for us in the past, but the sum of the legacy systems became quite cumbersome in its processing and was time-consuming," says MacKay. "We were looking for other ways to accelerate, to be more agile in delivering our solutions and our products."
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That need led them in 2015 to explore containerization. Ancestry engineers had already been using technology like <a href="https://www.java.com/en/">Java</a> and <a href="https://www.python.org">Python</a> on Linux, so part of the decision was about making the infrastructure more Linux-friendly. They quickly decided that they wanted to go with Docker for containerization, "but it always comes down to the orchestration part of it to make it really work," says MacKay.<br><br>
His team looked at orchestration platforms offered by <a href="https://docs.docker.com/compose/">Docker Compose</a>, <a href="http://mesos.apache.org">Mesos</a> and <a href="https://www.openstack.org/software/">OpenStack</a>, and even started to prototype some homegrown solutions. And then they started hearing rumblings of the imminent release of Kubernetes v1.0. "At the forefront, we were looking at the secret store, so we didn't have to manage that all ourselves, the config maps, the methodology of seamless deployment strategy," he says. "We found that how Kubernetes had done their resources, their types, their labels and just their interface was so much further advanced than the other things we had seen. It was a feature fit."<br><br>
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Their best practices include allowing their developers to deploy into development stage and production, but then controlling the aspects that need governance and auditing, such as secrets. They found that having one namespace per service is useful for achieving that containment of secrets and config maps. And for their needs, having one container per pod makes it easier to manage and to have a smaller unit of deployment.
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With that process established, the time spent on deployment was cut down to under a minute for some services. "As programmers, we have what's called REPL: read, evaluate, print, and loop, but with Kubernetes, we have CDEL: compile, deploy, execute, and loop," says MacKay. "It's a very quick loop back and a great benefit to understand that when our services are deployed in production, they're the same as what we tested in the pre-production environments. The approach of cloud native for Ancestry provides us a better ability to scale and to accommodate the business needs as work loads occur."<br><br>
The success of Ancestry's first deployment of the hint system on Kubernetes helped create momentum for greater adoption of the technology. "Engineers like to code, they like to do features, they don't like to sit around waiting for things to be deployed and worrying about scaling up and out and down," says MacKay. "After a while the engineers became our champions. At training sessions, the development teams were always the ones saying, 'Kubernetes saved our time tremendously; it's an enabler; it really is incredible.' Over time, we were able to convince our management that this was a transition that the industry is making and that we needed to be a part of it."<br><br>
A year later, Ancestry has transitioned a good number of applications to Kubernetes. "We have many different services that make up the rich environment that [the website] has from both the DNA side and the family history side," says MacKay. "We have front-end stacks, back-end stacks and back-end processing type stacks that are in the cluster."<br><br>
The company continues to weigh which services it will move forward to Kubernetes, which ones will be kept as is, and which will be replaced in the future and thus don't have to be moved over. MacKay estimates that the company is "approaching halfway on those features that are going forward. We don't have to do a lot of convincing anymore. It's more of an issue of timing with getting product management and engineering staff the knowledge and information that they need."
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"... 'I believe in Kubernetes. I believe in containerization. I think
if we can get there and establish ourselves in that world, we will be further along and far better off being agile and all the things we talk about,
and it'll&nbsp;go&nbsp;forward.'"
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