Cloud-Native Development

Much of the dependency mocking software in use today was not designed with cloud native architectures in mind. The tools that dominate the category today were built for a world where services ...

Ask any penetration tester which part of a Kubernetes assessment reliably produces a finding, and RBAC comes up almost every time. Not because Kubernetes’ permission model is poorly designed — it’s genuinely ...

Some of the most difficult production issues do not start with a failed service. The application is running, the database is reachable, requests are completed successfully and the monitoring dashboard is green ...

Kubernetes readiness probes can pass while applications are still unable to serve real traffic. Protocol-aware checks help close the gap between “running” and truly “ready.” ...

Kubernetes autoscaling works best when teams match the metric to the workload: queue latency for synchronous web traffic, queue depth for background jobs ...

Giving an AI agent the power to change a cluster is now straightforward. Confirming the change landed, did not produce unintended duplicate effects and achieved the outcome the operator actually wanted is ...

A practical way for platform teams to use AI for faster Kubernetes triage without giving agents unsafe control of the cluster. The first time an AI tool gets real cluster context, the ...

Enterprise AI is settling onto the cloud native stack, and the strongest evidence is not a vendor roadmap. It is what the ecosystem has already standardized ...

DataAgent emerged from stealth today with $10 million in pre-seed funding and an agentic AI platform designed to fix production problems inside Kubernetes environments without waiting for a site reliability engineer to ...

Like many of its fellow projects in the open source community, Kubernetes has seen an increase in pull requests, many of which are no doubt generated by AI.  This week’s release of ...