DevOps

Two-thirds of organizations run AI workloads on Kubernetes, but only 7% do it daily. Katie Gamanji says the ecosystem still needs better operational maturity and standards.

As infrastructure gets more complex, "inside the network" is no longer enough. Users, devices, and AI agents need their own identity and only the access they need.

We're burning thousands of dollars on AI conversations that should've been a single slash command.

Getting Debezium to stream the first PostgreSQL change into Kafka is straightforward; keeping it correct through failover is the interesting part.

When dozens of developers share the same environment and Git repository, testing changes quickly becomes chaotic. Here's how Kubernetes solves that.

To get the full power of a Deployment Pipeline, you need more than tools - you need practices that let it shine and reveal both your strengths and your weaknesses.

Want to avoid late-night panic, endless Slack searches, and heart-stopping alerts when you're on call? Then you need to create GOOD runbooks.

75% of respondents saw productivity boosts from AI, with just over a third reporting their gains as moderate (25%) or extreme (10%).

Discover how Jose Javier Moya's motorcycle analogy reveals the secrets of building a successful software deployment process through blueprints, automation, and quality assurance.

How to translate DORA metrics into tangible markers for measuring DevOps adoption and excellence? 

What is DevOps, anyway? It's been around for 15 years, and has grown into an industry - generating countless tools and quite a revenue. And yet, many people can't answer the question with certainty.

A DevOps educator with more than one million subscribers on her YouTube channel TechWorld with Nana shares her perspective on the primary challenges in the world of DevOps.

Michael also shares his opinion on DevOps vs. SRE vs. Platform Engineering debate, and the key ingredient for successful developer platform.