A few weeks ago we were alerted that Docker Swarm was using over 8GB of RAM. Our investigation led us to discover an unexpected factor that determines its memory usage. After a bit of graphing and math, we were able to locate the code behind this unexpected behavior.
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Kubernetes (lovingly referred to as “K8s”, “K8”, or even “the Kubes”) is becoming the most widely adopted container cluster manager out there. At a very basic level, Kubernetes provides an abstraction layer over containers that allows developers to organize all the different layers of their application through Kubernetes configurations. The challenge with Kubernetes is that you need to understand when and how to correctly use the abstractions it provides.
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We’re excited to announce Runnable Environments for JIRA is now available on the Atlassian Marketplace. This integration between Runnable and JIRA provides the ultimate collaboration experience for dev teams moving quickly to ship new features to customers.
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Debugging event-driven microservices can be a nightmare: logging is typically distributed across every service, and the event flow can’t easily be followed through code. This means debugging often involves going code-spelunking; mapping out every event that has been sent and following the chain. But this can yield complicated state diagrams with arrows crossing over themselves as you discover some events can call back up the chain — you can pull your hair out trying to keep all of it in your head.
The lesson here is that you can’t debug microservices in the same way you’d debug a monolith. But by appending some data to each event, you can start spotting issues more easily:
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There has been a lot of protest related to pipelines recently, but there is one that we can all agree brings value and profit to our work: the MongoDB Aggregation Pipeline. When MongoDB v2.2 was released, this performant method of data aggregation was introduced that utilizes stages to filter data and perform operations like grouping, sorting and transforming the output of each operator. This framework is an alternative to Mongo’s MapReduce functionality, and the output can be piped to a new collection or used to update specific documents.
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We’re always trying to eliminate points of drop-off in our onboarding flow — we want to show value as quickly as possible to new users. Recently, we applied some unconventional methods to make this happen.
The first thing a user experiences in Runnable is our demo. Our app builds environments for git branches. We want users to see what that’s like right off the bat, so we start them off with a demo application. Since it’s tied to a repository on their own GitHub account, we can’t build it in advance, which means they have to wait for it to build.
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Creating custom UI behavior in Angular can seem daunting. Once you know how to break the problem down, its complexity can just fizzle away. In this tutorial, we’ll be exploring the use of mouse events, locations, and some simple geometry to add an on-hover popover menu to a button. Not just any simple on-hover behavior, but one that stays open if the user is heading toward the content.
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In my previous two blog posts, I explored how Runnable’s architecture evolved over the last two years. There’s no one-size-fits-all solution, but the microservices approach has yielded a lot of benefits for us. In this post, I’ll talk about how Conway’s law has worked in reverse for us, and what the results of that look like.
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