In the previous article in this series I discussed the ecosystem of supporting services that allow us to operate micro-services in production. If our micro-services are our carries and those tools are our supports, what about our junglers? That’s where our developer ecosystem for cluster management comes in.

Welcome back readers to the Running Online Services at Riot blog series. My name is Maxfield Stewart and I’ve written before about how we use containers to build containers on an open source platform. Today’s article will dig into the five key requirements for any micro-service to become a live running application on our container platforms at Riot.

In our previous article, we discussed some of the networking involved in rCluster, Riot’s solution for worldwide application deployments. Specifically, we talked about the concept of overlay networks, an implementation we leverage called OpenContrail, and how that solution plays with Docker. In this post, we’ll build on that foundation and dive deeper on other topics: infrastructure as code, load balancing, and failover testing.

Hey all, this is David Press and Doug Lardo, two engineers working on improving the data center networking that enables online services at Riot. This article is the third part in a series on exactly that topic, which begins with an overview from Jonathan of a platform we called rCluster.

Our names are Kyle Allan and Carl Quinn, and we work on the infrastructure team here at Riot. Welcome to the second blog post in our multi-part series describing in detail how we deploy and operate backend features around the globe. In this post, we are going to dive into the first core component of the deployment ecosystem: container scheduling.

My name is Jonathan McCaffrey and I work on the infrastructure team here at Riot. This is the first post in a series where we’ll go deep on how we deploy and operate backend features around the globe. Before we dive into the technical details, it’s important to understand how Rioters think about feature development. Player value is paramount at Riot, and development teams often work directly with the player community to inform features and improvements.

Over the past several months I’ve published six articles that discuss using Docker and Jenkins to containerize a build farm. Recently, I went on the road to tell the story at DockerCon 2016 and gathered a tremendous amount of amazing feedback. In fact, the best part of this whole experience has been the conversations we’re having with folks encountering similar challenges. In this short post, I’d like to accomplish two things: share the video of my DockerCon talk, and respond to requests we’ve received to consolidate my articles into a single place.

Over my last two posts, I’ve talked about the challenges facing real-time applications like League that arise from the internet’s architecture, and how Riot is tackling some of those challenges by creating our own network. In this post, I’d like to look forward - what’s next, and how can we collectively get there? This topic has inspired a lot of reflection on my own experience building networks, and has galvanized my perspective that things are changing for the better.

Back in 2014, the Riot Direct team started a journey to provide a better League of Legends experience through network improvements. We started to look at the internet not as an inexhaustible resource, but as a limited system that had to be managed and scaled correctly.

This is the in-depth tutorial for the discussion started here about creating a build farm using Jenkins with Docker containers as the build slaves. When we’re done, you should have a fully functional Jenkins environment that provisions build slaves dynamically running on your local environment and ready for you to productionize.