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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Announcing HAProxy 3.4

HAProxy 3.4 is a milestone release that significantly advances HAProxy’s legendary flexibility, performance, security, reliability, and observability. Dynamic backend management simplifies integration with modern architectures, memory efficiency improves across a broader range of workloads, native cryptographic operations at the proxy layer open new possibilities for API security architectures, and OpenTelemetry support makes HAProxy a first-class participant in distributed tracing pipelines.

21 AI concepts every beginner should know before their first interview

If you’re prepping for your first AI or MLOps interview, the hardest part usually isn’t always the hands-on element. For me, it’s the vocabulary. Interviewers sometimes lob single-word concepts at you (“what’s quantization?”) and watch how far you can carry the thread. The questions sound clear-cut, but each one is really a doorway into a bigger topic, and the interviewer is judging how cleanly you walk through it.

The Bug Hiding in Your Production Traffic

Your logs showed 500 errors. The traces showed the dependency graph. Neither showed the actual bug, a DEL control character getting appended to the query string. This is how I found it. In this video I walk through Speedscale BYOC (bring your own cloud): capture real production traffic, store it in your own Elasticsearch cluster inside your VPC, pull it down locally with a single script, and reproduce the exact bug using proxymock. The data never leaves your environment.

CloudZero AI Hub: The nexus of autonomous AI cost control

CloudZero originated as a way to make sense of your cloud costs. Costs spread across bills with billions of line items belonging to resources that might or might not have been tagged (or taggable), spun up by engineers working across teams, on different microservices, features, and products, that served a wide range of customers. Kubernetes. Multi-cloud. Check, check, check.

AI ROI: How to measure and provide the return on AI investments in 2026

Every quarter, the same scene plays out in boardrooms across the Fortune 500. The CEO asks: “What is the return on everything the company is spending on AI?” The CTO talks about productivity gains and developer velocity. The CFO points at a cloud bill that doubled but cannot isolate which line items are AI. The board nods politely and tables the discussion until next quarter, when the same question will produce the same non-answer. (If this sounds familiar, you are not alone. Keep reading.)

IBM Think 2026 Infrastructure Insights for IT Leaders

IBM Think 2026 made one thing clear: infrastructure leaders are being asked to support more AI, more automation, and faster decision-making without adding unnecessary complexity or risk. Held earlier this month in Boston, IBM Think 2026 focused heavily on enterprise AI, hybrid cloud, automation, governance, and operational transformation.

Logs told me something broke. Traffic showed me what.

Here’s a problem I run into constantly: something breaks in production, I can see the 500 errors in my logs, but I can’t reproduce it locally. The trace shows me the dependency graph but not the actual request that failed. This is especially painful in microservices. I was looking at a CNCF example the other day (a simple demo app, like 4 pods) and it already had so many cross-service dependencies that understanding what broke required looking at the whole system at once.

The AI ROI Company's new groove: CloudZero's new UI, and what it means for customers

Customizability. Feature velocity. Performance. Capabilities that are critically important to all B2B software users. And capabilities in which CloudZero’s brand-new platform specializes. Pitching a total frontend overhaul didn’t necessarily make me CloudZero’s most popular new PM. But it’s made CloudZero faster, more customizable for a wider range of personas, and easier to update with the new features that matter most to our customers. And, if I may say, it also looks beautiful.

Atlassian Transforms Product Development with AI

What used to take months now takes weeks, and it’s changing what it means to build great products. At Atlassian, product managers and designers are using Rovo and Jira Product Discovery to move faster at every stage of the development lifecycle. From running deep research across all their tools and documents, to capturing ideas, surfacing insights, and prioritizing what to build next. AI is transforming how product decisions get made.