Kubernetes-native scale-to-zero with zero traffic loss, no code changes, and direct integration with kubernetes resources

The OpenTelemetry Operator is an implementation of a Kubernetes Operator.

Zarf eliminates the complexity of airgap software delivery for Kubernetes clusters and cloud-native workloads using a declarative packaging strategy to support DevSecOps in offline and semi-connected environments.

The SR-IOV Network Device Plugin is Kubernetes device plugin for discovering and advertising networking resources in the form of:

- SR-IOV virtual functions (VFs)
- PCI physical functions (PFs)
- Auxiliary network devices, in particular Subfunctions (SFs)

which are available on a Kubernetes host

"Oops, I accidentally deleted my Docker registry. Can I get my images back?" YES. This tool does exactly that.

A cautionary tale about AWS VPC networking, NAT Gateways, and how a missing VPC Endpoint turned our S3 data transfers into an expensive lesson.

Postgres has an awesome amount of data collected in its own internal tables. Postgres hackers know all about this - but software developers and folks working with day to day Postgres tasks often miss out the good stuff.

The Postgres catalog is how Postgres keeps track of itself. Of course, Postgres would do this in a relational database with its own schema. Throughout the years several nice features have been added to the internal tables like psql tools and views that make navigating Postgres’ internal tables even easier.

Today I want to walk through some of the most important Postgres internal data catalog details. What they are, what is in them, and how they might help you understand more about what is happening inside your database.

After stumbling on a pair of interesting blog posts — You Don’t Need Kafka, Just Use Postgres (Considered Harmful) — somewhat in the style of good old “flame wars” (which are increasingly rare these days) in the recent Postgres Weekly, as a response to a previous article — Kafka is fast – I’ll use Postgres — on using Postgres for “Kafkaesque” business, I felt the urge to chip in a bit.

But first off — I’d like to laud the authors of both pieces. They’re well-argued reads with a crazy amount of good tidbits and food for thought. I especially liked that the original one tried to be open and repeatable and actually tested things. Gunnar’s take was maybe a bit too morbid for my taste, of course 🐘

To recap — the main question in the debate was whether Postgres is generally “good enough” to implement a low-to-medium volume event queue or even a pub-sub system. The general sentiment from Hacker News readers at least was that unless scale truly demands Kafka, Postgres is indeed good enough — and many teams plain overestimate their scaling needs and don’t actually need Kafka’s distributed complexity.

Spoiler: there’s obviously no definitive answer as to when one should use a “proper” database for something — and there sure are reasons why we have so many purpose-specific databases: relational, event logs, analytical column stores, key-value, time-series, ledger, graph, hierarchical, document, blob, text search, vector, …

Anyway, below are some thoughts that came to mind — I can’t go too deep on Kafka though, as I’m just not qualified enough.

VectorChord (vchord) is a PostgreSQL extension designed for scalable, high-performance, and disk-efficient vector similarity search.

Baserow is the secure, open-source platform for building databases, applications, automations, and AI agents — all without code. Trusted by over 150,000 users, Baserow delivers enterprise-grade security with GDPR, HIPAA, and SOC 2 Type II compliance, plus cloud and self-hosted deployments for full data control. With a built-in AI Assistant that lets you create databases and workflows using natural language, Baserow empowers teams to structure data, automate processes, build internal tools, and create custom dashboards. Fully extensible and API-first, Baserow integrates seamlessly with your existing tools and performs at any scale.

Doco-CD is a lightweight GitOps tool that automatically deploys and updates Docker Compose projects/services and Swarm stacks using polling and webhooks.

You can think of it as a simple Portainer or ArgoCD alternative for Docker.

Securely share sensitive information with automatic expiration & deletion after a set number of views or duration. Track who, what and when with full audit logs.

Free, open source and self-hosted solution for automated PostgreSQL backups. With multiple storage options and notifications

Ever since git init ten years ago, Zig has been hosted on GitHub. Unfortunately, when it sold out to Microsoft, the clock started ticking. “Please just give me 5 years before everything goes to shit,” I thought to myself. And here we are, 7 years later, living on borrowed time.

Putting aside GitHub’s relationship with ICE, it’s abundantly clear that the talented folks who used to work on the product have moved on to bigger and better things, with the remaining rookies eager to inflict some kind of bloated, buggy JavaScript framework on us in the name of progress. Stuff that used to be snappy is now sluggish and often entirely broken.

More importantly, Actions is created by monkeys and completely neglected. After the CEO of GitHub said to “embrace AI or get out”, it seems the lackeys at Microsoft took the hint, because GitHub Actions started “vibe-scheduling”; choosing jobs to run seemingly at random. Combined with other bugs and inability to manually intervene, this causes our CI system to get so backed up that not even master branch commits get checked.

Rather than wasting donation money on more CI hardware to work around this crumbling infrastructure, we’ve opted to switch Git hosting providers instead.

As a bonus, we look forward to fewer violations (exhibit A, B, C) of our strict no LLM / no AI policy, which I believe are at least in part due to GitHub aggressively pushing the “file an issue with Copilot” feature in everyone’s face.