From Production — week of 2026-09-01
The good ol’ days of building Java
Stack Overflow
Ryan sits down with Tim Lindholm, an early contributor to the Java language at Sun Microsystems, to chat about what it was like building one of the most popular programming languages ever at its inception, why it was strategically important for the Java team to create a cross-platform ABI to compete with Windows NT, and how applets were initially just an interesting demo.
Orchestrate production RAG with OpenShift AI
Red Hat
In the previous post in this series, we built a streaming retrieval-augmented generation (RAG) pipeline that parses, chunks, embeds, and writes to Milvus in a single Ray Data script. It works well. But it is a monolithic script. When parsing fails at file 847 of 1,000, you rerun everything from scratch. The post Orchestrate production RAG with OpenShift AI appeared first on Red Hat Developer.
How Identity Federation Empowers Partner API Strategy
Nordic APIs
Business identity is a complex issue rife with risks across the board. Large enterprises often require deep, flexible integrations with dozens or hundreds of partners, but this comes with significant risk — between the potential for information leakage, concerns around replays or data usage for continued insecure access, and the sheer friction of such a ...
Developing LLM guardrail configs locally with NeMo Guardrails
Red Hat
Large language models are powerful, but deploying them in production means thinking about risks like prompt injection, toxicity, PII leakage, and more. To address this, Red Hat has partnered with NVIDIA to develop and support NeMo Guardrails, an enterprise-ready open source framework that lets you add programmable safety rails to any LLM application. The post Developing LLM guardrail configs locally with NeMo Guardrails appeared first on Red Hat Developer.
Building hermetic notebook images for Open Data Hub and Red Hat OpenShift AI
Red Hat
If you've ever watched a container build fail because a package mirror glitched, or wondered whether last month's image really matches what you ship today, then you already know the pain that a hermetic build is meant to solve. For Open Data Hub (ODH) and Red Hat OpenShift AI notebook images, we implemented a simple rule: Nothing downloads during the image build. Dependencies are pinned in lockfiles, prefetched ahead of time, and installed from a local cache while the build runs with no network. The same Containerfile works on a laptop, in GitHub Actions, and on Konflux. The post Building…
Rootless Jailbreak Detection: Updating the Signals, Not the Claim
CodeName One
Codename One's iOS integrity checks now detect current rootless jailbreak layouts, cross-check hooked APIs, inspect mounts and loaded images, and rerun on foreground entry.
Amazon EC2 R9g and R9gd instances powered by AWS Graviton5 processors are now generally available
AWS
Amazon EC2 R9g and R9gd instances powered by AWS Graviton5 are now generally available, delivering up to 25% better compute performance than R8g, ideal for databases, in-memory caches, and real-time analytics.
Rerouting the Stream: How Lyft Moved to the Apache Flink Operator
Lyft
Written by Maheep Myneni, Arda Kuyumcu, and Prem Santosh Udaya Shankar at Lyft.Why We Migrated: Technical Debt Meets Modern Streaming DemandsOver the past several quarters, Lyft’s Streaming Compute team retired our internally developed Flink Kubernetes operator and moved our entire streaming fleet onto the open-source Apache Flink Kubernetes operator. This post is about why we made the switch, how we pulled it off incrementally without disrupting users, and the follow-on work it took to actually get the benefits we were after.Back in 2020, when we first architected the Lyft Flink Kubernetes…
Vercel Sandbox now calculates snapshot storage costs daily
Vercel
Vercel now calculates charges for Sandbox snapshot storage from each day’s average usage and adds them to your monthly invoice. Previously, billing used one average across the entire monthly billing period. You can track these daily charges on the team’s Usage page and see how changes in storage affect your cost. The rate remains $0.08 per GB-month; only how usage is calculated has changed. The update takes effect automatically at the start of the next billing period for Pro and Enterprise teams. No action is required. Learn more about Sandbox snapshot storage in the documentation.…
How Companion.energy Reduced Query Latency 25x and Compressed Terabytes to Gigabytes with Tiger Cloud
Timescale
How Companion.energy optimized real-time energy data: 25x faster queries, 43.5x compression, continuous aggregates, and unified Tiger Cloud architecture.
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