You submit a Kubernetes Job and wait for its Pods to appear. A minute passes. Then another. The Job is still suspended, there are no application logs, and there may not even be a Pod to inspect.
In a cluster managed by
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You submit a Kubernetes Job and wait for its Pods to appear. A minute passes. Then another. The Job is still suspended, there are no application logs, and there may not even be a Pod to inspect.
In a cluster managed by
In Linux, cgroups (control groups) are a kernel feature used for managing system resources. Kubernetes uses cgroups to allocate resources like CPU and memory to containers, ensuring that applications run smoothly without interfering with each other. With the release of Kubernetes v1.31, support for v1 cgroup management moved into
Memory is often the first hard limit a Kubernetes cluster hits. Nodes run out of RAM long before they run out of CPU, and the new wave of agentic AI workloads makes this worse. These workloads demand large memory footprints to start up and run untrusted code, then sit idle waiting for the next prompt. That idle but resident memory is expensive, and it caps how many pods a nod...
As Kubernetes adoption has grown, the conversation has shifted beyond running containers to managing increasingly complex application lifecycles. Modern platforms support stateless web services, stateful databases, batch processing, AI workloads, and platform services. At the same time, they must remain reliable during upgrades, scaling events, and infrastructure failures.