I recently started using Visual Studio Code Dev Containers with LLM coding agents and I thought to share it because, in my opinion, it is one of the simplest ways to make agentic development safer. LLM agents are incredibly useful,…
14:47 UTC, Tuesday. Pods in the checkout-api deployment start OOMKilling in a loop, three or four at a time, in the middle of an ordinary afternoon. Traffic is flat. No deploy went out today. PagerDuty fires on KubePodCrashLooping, not on anything…
Live Webinar and Q&A: Scaling OpenTelemetry: Managing Collectors, Configuration, and Cost (Nov 19, 2026) Save Your Seat Agentic LLM systems have moved from linear prompt chains to graph-based workflows and, more recently, code-executing harnesses. Chains are simple but fragile, graphs add branching,…
Most MCP servers start life as a local, stdio-based process — the client spawns the server as a child process, messages flow over stdin and stdout. The instinct once that server needs to serve more than one client is to containerize…
The video version walks the same optimization live if you prefer to watch it: The idea: use one stage with the full toolchain to build, then copy only the finished artifacts into a minimal runtime stage. The build stage is…
This post walks one realistic incident end to end, the way you would narrate it in an interview or actually run it during an outage. If you prefer watching it as a live terminal walkthrough, the video version covers the…
A config change goes out. A couple of minutes later every request to the app fails, and kubectl get pods shows the status nobody wants to see: I broke a small Go service on purpose to walk through this one…
Every request to the app fails with a 503. The body says no available server. And yet kubectl get pods looks perfect: One of one ready, zero restarts, nothing deployed. I broke a small Go service on purpose to walk through…
A single ansible-playbook site.yml that restarts every web node at once turns a routine release into a short outage. An Ansible rolling deployment avoids that by updating hosts in small batches. Each host is taken out of the load…
Your AI agent burns tokens to think. Most of that thinking - the tool-call planning, the YAML editing, the re-reads of the same file - does not need a frontier model behind an API. Docker Model Runner keeps a real LLM inside…
FAIR data, notebooks, containers, and repeatable analysis pipelines.
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