Телеграм канал «mkdev»

What if you could keep your Compose files and lose Docker?

That’s essentially the idea behind running Compose workloads with Podman.

The developer experience can remain surprisingly familiar, while Podman provides a daemonless, largely rootless container engine underneath. Today, podman compose can hand the workload to a Compose provider and connect it transparently to Podman.

Same Compose concept. Different engine.

Our article takes a hands-on look at how Dockerless Compose works. Give it a read: https://mkdev.me/posts/podman-3-and-docker-compose-how-does-the-dockerless-compose-work

Your Kubernetes cluster may be running perfectly and still have serious security gaps.

We dig into permissions, network policies, images, secrets, runtime environments and more—then tell you what to fix and why.

Explore our Kubernetes Security Audit: https://mkdev.me/b/audits/kubernetes-security-audit

The best time to figure out whether your Kubernetes backups work is not during an incident.

With Backup for GKE, you can create scheduled backup plans, protect selected namespaces or workloads, include persistent volume data, and prepare restore plans before you actually need them.

And testing the restore matters just as much as creating the backup.

In this walkthrough, we deliberately remove workloads from a GKE cluster and bring them back using a backup and restore plan.

Take a look at the full guide: https://mkdev.me/posts/how-to-back-up-gke-clusters

In 101st mkdev dispatch, Kirill explores the emerging world of AI decision models, why they could become an essential part of future LLMs, and how they can make AI applications faster and more efficient. From improving search results and routing requests between models to building real-time game AI, he shares some early experiments and explains why this technology is worth paying attention to: https://mkdev.me/posts/decision-models-like-jev-and-clef-are-a-game-changer-101

AI can write shell commands for you. That doesn’t make understanding the terminal less useful.

Knowing your way around cd, grep, ls, ssh, curl and a handful of other basics makes it much easier to understand what a generated command will actually do, debug problems, and work confidently on remote systems.

Kirill built his beginner list from almost 30,000 lines of real shell history rather than choosing commands arbitrarily.

The result is a good reminder that foundational skills tend to age remarkably well.

Read the article for the full top 10: https://mkdev.me/posts/top-10-linux-commands-beginners-should-know-as-analysed-from-my-bash-history-of-30-thousand-lines

GenAI has changed how quickly data and AI teams can prototype, explore ideas and work with internal knowledge. It hasn’t changed the need to prove that an AI system actually creates value.

That distinction is becoming increasingly important. The model is only one part of the equation. Evaluation, governance, data quality, business context and expert oversight still determine whether an experiment becomes a useful production system.

Last year, we spoke with data and AI leaders from Allianz, Thoughtworks and Outbrain about what GenAI has—and hasn’t—changed about leading their teams.

Read the full article: https://mkdev.me/posts/how-genai-has-and-hasn-t-changed-the-way-allianz-thoughtworks-and-outbrain-lead-data-and-ai-teams

Your data lake shouldn't be a swamp.

Messy pipelines, scattered data, and AI projects going nowhere? Sounds like your data infrastructure needs some attention.

Let's clean up the mess together: https://mkdev.me/b/consulting/data-engineering