Inbucket is an email testing service; it will accept messages for any email address and make them available via web, REST and POP3 interfaces. Once compiled, Inbucket does not have any external dependencies - HTTP, SMTP, POP3 and storage are all built in.

Good alerting hygiene consists of a few components: chasing down alert conditions, reflecting on incidents, and thinking of what makes a signal good or bad. The hope is that we can get our alerts to the stage where they will page us when they should, and they won’t when they shouldn’t.

However, the reality of alerting in a socio-technical system must cater not only to the mess around the signal, but also to the longer term interpretation of alerts by people and automation acting on them. This post will expand on this messiness and why Honeycomb favors an iterative approach to setting our alerts.

Using traditional package managers or applying manifests directly can be super confusing and doesn't scale. Therefore, Glasskube will help you to install your favorite Kubernetes packages using the Glasskube UI for reduced complexity and increased transparency. We are also providing a brew inspired CLI for advanced users. Our packages are dependency aware, as you would expect from a package manager. Designed as a cloud native application, so you can follow your GitOps approach.

Apache APISIX is a dynamic, real-time, high-performance API Gateway.

APISIX API Gateway provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more.

You can use APISIX API Gateway to handle traditional north-south traffic, as well as east-west traffic between services. It can also be used as a k8s ingress controller.

Do you have a set of projects sitting in a mono-repo and having various workspaces, file structures, and Terraform versions? A pain of switching the versions and remembering all path/workspace combinations? Uncertainty about the correctness of the workspace, or plan file before applying it?
I feel you! I’d share my experience in managing such projects, an approach to make it much easier, and a simple tool I wrote a few years ago for that. How is it related to Docker Compose? I’ll tell you…

Cleaner is a Kubernetes controller that identifies unused or unhealthy resources, helping you maintain a streamlined and efficient Kubernetes cluster. It provides flexible scheduling, label filtering, Lua-based selection criteria, resource removal or update and notifications via Slack, Webex and Discord.

The GitButler version control client, backed by Git, powered by Tauri/Rust/Svelte

DotSlash (dotslash) is a command-line tool that lets you represent a set of platform-specific, heavyweight executables with an equivalent small, easy-to-read text file. In turn, this makes it efficient to store executables in source control without hurting repository size. This paves the way for checking build toolchains and other tools directly into the repo, reducing dependencies on the host environment and thereby facilitating reproducible builds.

Basically sad is a Batch File Edit tool.

It will show you a really nice diff of proposed changes before you commit them.

Unlike sed, you can double check before you fat finger your edit.

Over the past decade, more and more closed-source repos have started banning merge commits on trunk and shifting to a squash-rebase-and-merge workflow. The benefits are clear: rebasing creates a cleaner, more understandable history & state of the world without the clutter of merge commits. Trunk branches remain linear, and branches function as brief, atomic diffs off the trunk. Some operations become more complex (largely due to incomplete/missing Git tooling), but the end state is a tidier history.

Programming is full of ups and downs. While the victories always feel great, there are also lots of tricky little things that end up sapping your time and energy. I feel a sense of responsibility to share those experiences in the hopes that it helps even just one fellow programmer.

Everything has limits, including software systems. When you hit these limits, bad things can happen.

You've probably hit memory and disk limits, but those aren't the only ones.

This page lists limits that, when breached, led to someone having a bad time. I tweeted about limits and got all sorts of interesting responses. This page contains some of them, with links to the tweets, which often contain more details.

Here are some proposed questions for interviewing someone for an SRE role. Really, these are just conversation starters to get them reflecting and discussing specific incident details.