Operations | Monitoring | ITSM | DevOps | Cloud

The dashboard says you can save 30%. The SRE team won’t sign off. You’ve probably been in this meeting. Finance has a number. The platform team has a scar. Somewhere between them sits a senior manager, maybe you, being asked to choose a cost optimization tool that one side will champion and the other side will quietly refuse to deploy in production. The standoff isn’t about price. It’s about trust.

Have you ever considered how you can utilize artificial intelligence (AI) without sacrificing control over your data and autonomy? As we continue to navigate the changes of AI in the 21st century, it is important to understand how decentralized AI infrastructure can empower individuals and organizations to harness the potential of AI while maintaining sovereignty over their data and decision-making processes.

For the past year, I've been hearing a version of the same thing from engineering leaders: AI tools are working, productivity is up, the business case is there. And yet, something about the picture still feels incomplete. So we decided to go find out how widespread that feeling actually is. We surveyed 700 engineers and managers across five countries, and published the results in the State of Engineering Excellence 2026.

Effective disaster recovery testing follows a clear three-phase lifecycle: plan, execute, and review. Most DR programs fail not because of missing tools, but because of untested runbooks and unclear ownership. Platforms like Harness Resilience Testing bring chaos, load, and DR testing into one pipeline so teams can catch risks before they become incidents. Most organizations don't fail at disaster recovery because they lack technology.

Non-technical teams are building apps on Lovable, Bolt.new, and Replit with company data and zero governance. Here's why that's a compliance nightmare - and what enterprise platform teams should deploy instead. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

AI coding tools turned every engineer into a 10x developer. Now your CI/CD pipeline is the bottleneck. Learn how to handle 10x more deploys per engineer with Qovery's dual deployment model. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

In early 2026, two back-to-back Linux kernel exploits, Copy Fail (CVE-2026-31431) and Dirty Frag (CVE-2026-43284 & CVE-2026-43500), shattered assumptions about how quickly attackers can weaponize disclosed CVEs. Dirty Frag, a zero-day Linux vulnerability that affected most major distributions, had PoC exploits published within hours of its disclosure. It’s a stark reminder: the timeline between vulnerability disclosure and active exploitation has shrunk from weeks to hours.

Let’s be real: building reliable tech products is hard. Modernizing that same tech without compromising the user experience is even harder. The "rip and replace" approach to modernization can severely disrupt your customers’ integration efforts and workflows. When it doesn’t work, reversing course might be the least-worst option. By contrast, the evolution of the HAProxy One application delivery platform architecture at HAProxy Technologies over 25 years has been gradual and consistent.