RECENT ROTATIONS

If you think farmwork and software don’t have much in common, think again!

In the third and final part of our series exploring the popular consensus algorithm we’ll finally explore how Raft handles leader election, and in doing so discover how Raft is so incredibly resilient.

Event-driven architectures (EDA) are enjoying a resurgence in interest due to many organizations’ need to accelerate rapid prototyping and get by with smaller, more cross-functional teams. In this post, we’ll demonstrate how to …

In our first installment on how to implement the famous Raft algorithm, we introduced the log: an ordered sequence of operations that serves as the core data structure for distributed consensus. In this second part, we’ll demonstrate …

If nothing else, the last year has brought the winds of change to the tech sector. From high-visibility layoff cycles at FAANGs and crypto companies, to turbulence in our social media infrastructure, to pop culture’s discovery of deep …

With all the blockchain breaches and social media escapades, there’s been an awful lot of buzz about distributed systems lately. But how many of us really understand how they work? Let’s dive in together…

Serialization format is an often-overlooked engineering step that could make your application as slow as a turtle or as speedy as a cheetah!

In this post we’ll explore the question, how does a distributed system actually die?

Even though we are a fully distributed team, we celebrate curiosity, collaboration, and growth together in-person as much as we can. We’ve maintained a tradition of combining tech conferences with team retreats, and this October we …

If you talk about WebAssembly (WASM), you just may spark debate about whether it is really the next best thing in web development or the second coming of Java applets. In this post, we’ll dive into WASM, how it is currently …

Kafka and PubSub and Kinesis, oh my! Which eventing platform is best? In this post we’ll explore the three primary categories of eventing systems and understand their similarities, differences, and key use cases.

The data type choices we make when building data systems or metrics is critically important: as our systems run for long periods of time it can be easy to overflow the integers that we use (Y2K bug anyone?). As a result, I find myself …