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Jun 10th 2026, 15:00 by Sandesh Basrur
Over the last two decades, my code has been deployed in a live environment.
I disrupted stress testing processes on Black Friday, rendered user authentication impossible at 2 am, and saw a system handling 40 million users break due to a minor modification in the configuration file.
Jun 10th 2026, 14:30 by Shai Almog
This week's release post looks different on purpose. The Friday omnibus has been getting longer and longer, and that has been working against us in two ways. SEO ignores 5,000-word pages that cover twelve unrelated topics, so the actual material gets buried instead of being indexed against the queries that should find it. And when a single release post covers ten things, it becomes hard to point a colleague at "that one Codename One change from a few weeks ago" without scrolling for ten minutes.
So from this week onwards, the Friday post is the short one. A quick set of headline items, a "what is coming next" list, and that is it. The specific features get their own posts over the following days, with their own slugs, their own searchable titles, and their own discussion threads. The weekly post lives at the top of the homepage as the index; the deeper posts back-link to it, and you can read whichever ones are actually relevant to your project.
Jun 10th 2026, 14:00 by Sai Teja Erukude
When I started working with AI agents, the hardest part was not always getting an answer. The hardest part was understanding how the agent got there.
The final response might look acceptable, but the path behind it was often blurry.
Jun 10th 2026, 13:00 by VIVEK KATARYA
Part 1 dived into what to trace in an agentic system and why. How the traditional tracing and metrics, such as latency, scale, cost, uptime, and throughput, need to be redefined. And how to define the new metrics that are at the core of an agentics system, such as response quality, accuracy, and task completion.
This part is about the mechanics: how a trace is structured, how context propagates across agent boundaries, and how to make sense of it all.
Jun 10th 2026, 12:00 by Akhil Madineni
Zero-downtime deployment is often described as a rollout strategy, but in production, it is more accurately a coordination problem. Traffic must remain on healthy instances while new ones warm up, controllers must wait for readiness before shifting load, and promotion must stop cleanly when metrics degrade.
Kubernetes rolling updates already replace Pods incrementally and wait for new instances to start before removing old ones, while readiness probes determine when a Pod should receive traffic. Progressive delivery systems such as Argo Rollouts add weighted traffic shifts, pauses, and analysis gates. The difficult part is not the individual primitive, but the stateful control flow around all of them when retries, human approvals, controller restarts, and rollback decisions intersect.
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