Operations | Monitoring | ITSM | DevOps | Cloud

IT infrastructure is now hyper-distributed. We are in a scale-in-seconds era and that means, a typical IT landscape is spread across on-premises data centers, public clouds (AWS, Azure, GCP), containerized environments, and edge locations. With many components comes more points of failure. A single server outage can cascade into customer-facing incidents, SLA violations, and revenue loss measured in thousands per minute.

Claude is one of the go-to AI-native code editors for developers. Because it’s a simple chatbot interface housed inside a familiar CLI, it provides a pretty smooth path between traditional IDEs and agentic AI. But what’s actually happening behind the scenes when you ask it to write code, generate a test, or debug an issue? Who and what is it talking to behind the scenes? Can I prevent data leakage or do I need to add another layer to my tin foil hat?

Kubernetes v1.35 dropped a couple of weeks ago, and while the headlines focus on gang scheduling and in-place resizing going GA, there’s a bigger story here that every platform team needs to understand: Kubernetes is finally acknowledging that cluster utilization is fundamentally broken. At Komodor, we work with hundreds of organizations running Kubernetes at scale.

As AI workloads shift from training to massive-scale inference, SRE teams are about to feel even more pressure. GPU-heavy computing is breaking the assumptions today’s clusters were built on, while enterprises are beginning to trust autonomous operations and cost pressure is pushing consolidation across the cloud-infrastructure stack.

Choosing the right tool to manage your infrastructure can shape how fast your team moves and how reliable your systems become. Two names appear in almost every conversation: Ansible and Terraform. Both help you define, manage, and scale your environment. But they solve different problems and work in very different ways. One focuses on configuration. The other focuses on provisioning. Both are powerful. Both are widely used. And both can work together in the right stack.

When I was invited to join one of our customer’s end-of-year team wrap-up sessions, it came as no surprise when the meeting opened with a familiar refrain: “Next year will be different. Next year, we’ll get ahead of the noise. Next year, tickets won’t pile up while we’re still triaging yesterday’s issues.

Six years of Qovery, and the philosophy behind every pivot.