In this post, I’ll start off with a brief overview of “shared nothing” vs. “shared storage” architectures in general. This discussion will be a bit abstract and high-level, but the goal is to share with you some of the guiding philosophy that ultimately led to WarpStream’s architecture. We’ll then quickly transition to discussing the trade-offs between the two architectures more specifically in the context of data streaming and WarpStream; this is the WarpStream blog after all!

The Performance Engineering team at GitHub assessed how CPU performance degrades as utilization increases and how this relates to capacity.

Fastmail has a long history of using our own hardware. We have over two decades of experience running and optimising our systems to use our own bare metal servers efficiently.

This article explores the challenges and pitfalls of Terralith, a monolithic Terraform architecture in Infrastructure as Code, and uncovers why a Terralith is not considered best practice.

Terraform users will likely be familiar with “data source will be read during apply” messages that may appear in the plan output. These messages can be confusing and may even lead to unexpected re-creation of resources. Typically, these messages are related to using data sources in combination with Terraform modules and explicit dependencies.

In our company we have thousands of resources managed by Terraform. Which are deployed to multiple environments (dev, staging, production) and different regions.

This go package provides a terminal user interface for ufw.

Techniques to Avoid Potential Failures Caused by Sudden Traffic Spikes

Bento is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads.

A lightweight Database GUI in your browser. It supports connecting to Postgres, MySQL, and SQLite.

In this study, our goal was to find the solution with the lowest latency, highest throughput, and the lowest setup cost. Since our load is latency-sensitive, our intent is to measure high percentile latencies at relatively high network utilization. We particularly focused on the performance under 30–50% of the maximum load, because we think this best represents the most common use cases of a non-overloaded system.

Target audience: This article is a deep dive for people living the Kubernetes lifestyle, for people who know or want to know how the low level stuff works and performs. I do not explain every container or Kubernetes component as it is expected to be known.