KUBERNETESβ
β
β
β
On behalf of Kubernetes SIG Auth and SIG Node, we are pleased to announce the graduation of fine-grained kubelet API authorization to General Availability (GA) in Kubernetes v1.36! The KubeletFineGrainedAuthz feature gate was introduced as an opt-in alpha feature in Kubernetes v1.32, then graduated to beta (enabled by default) in v1.33. Now, the feature is generally available and the feature gate is locked to enabled. This feature enables more precise, least-privilege access control over the kubelet's HTTPS API, replacing the need to grant the overly broad nodes/proxy permission for common monitoring and observability use cases. Motivation: β¦
KUBERNETESβ
β
β
β
If you run Kubernetes on Linux with SELinux in enforcing mode, plan ahead: a future release (anticipated to be v1.37) is expected to turn the SELinuxMount feature gate on by default. This makes volume setup faster for most workloads, but it can break applications that still depend on the older recursive relabeling model in subtle ways (for example, sharing one volume between privileged and unprivileged Pods on the same node). Kubernetes v1.36 is the right release to audit your cluster and fix or opt out of this change. If your nodes do not use SELinux, nothing changes for you: the kubelet skips the whole SELinux logic when SELinux is unavailβ¦
KUBERNETESβ
β
β
β
Editors: Chad M. Crowell, Kirti Goyal, Sophia Ugochukwu, Swathi Rao, Utkarsh Umre Similar to previous releases, the release of Kubernetes v1.36 introduces new stable, beta, and alpha features. The consistent delivery of high-quality releases underscores the strength of our development cycle and the vibrant support from our community. This release consists of 70 enhancements. Of those enhancements, 18 have graduated to Stable, 25 are entering Beta, and 25 have graduated to Alpha. There are also some deprecations and removals in this release; make sure to read about those. Release theme and logo We open 2026 with Kubernetes v1.36, a release thβ¦
KUBERNETESβ
β
β
β
Kubernetes v1.36 is coming at the end of April 2026. This release will include removals and deprecations, and it is packed with an impressive number of enhancements. Here are some of the features we are most excited about in this cycle! Please note that this information reflects the current state of v1.36 development and may change before release. The Kubernetes API removal and deprecation processThe Kubernetes project has a well-documented deprecation policy for features. This policy states that stable APIs may only be deprecated when a newer, stable version of that same API is available and that APIs have a minimum lifetime for each stabilβ¦
KUBERNETESβ
β
β
YAML has been the standard way to write Kubernetes manifests for years. Every example, tutorial, and configuration file you come across is written in it. The problem isn't that YAML is a bad format. It's that YAML gives you a lot of choices, and not all of them are equally good for writing Kubernetes manifests. Some features make files harder to read, some are easy to misuse and others can lead to surprising behavior. The interesting part is that Kubernetes doesn't actually need most of those features. It only relies on a small subset of YAML. This led to a simple question: if Kubernetes only needs a small part of YAML, why not standardize oβ¦
KUBERNETESβ
β
β
This article has been revised since it was first published, to correct several significant technical inaccuracies in the original text. Kubernetes has long been the default platform for distributed workloads, and writing your own controller for it is now a matter of a few hours. The common path β Golang, using kubebuilder on top of controller-runtime β gives you a project scaffold, types, and a reconciler. For typical scenarios that is more than enough. But as soon as load grows or the controller starts behaving in ways you did not expect, a whole class of edge cases shows up. Most of them trace back to the same root cause: a fuzzy mental moβ¦
KUBERNETESβ
β
β
Kubernetes has quietly become the default platform for AI and machine learning. Whether you run notebook servers for data scientists, schedule distributed training jobs, tune hyperparameters, or orchestrate multi-step ML pipelines, those workloads increasingly land on a Kubernetes cluster. Kubeflow is one of the most popular ways to assemble that stack, and it does so the Kubernetes-native way: every capability is exposed as a Custom Resource Definition (CRD). That design is a gift to cluster operators, because it means ML workloads can be observed and managed with the same primitives as everything else in the cluster. But in practice the spβ¦
KUBERNETESβ
β
β
1. Before you start: know what is changingKubernetes Dashboard and Headlamp both show what is running in a cluster, but they work differently. When Headlamp runs on the desktop, it uses your existing kubeconfig to connect to one or more clusters and can be extended with plugins. When Headlamp runs inside a cluster, it uses a Kubernetes ServiceAccount to access the API and follow RBAC rules. Kubernetes Dashboard, in contrast, only runs in-cluster and always relies on service account tokens. Understanding these models early helps you choose the right setup and permissions. 1.1 How Kubernetes Dashboard worksDashboard is a web app that runs insiβ¦
KUBERNETESβ
β
β
Headlamp is an open-source, extensible Kubernetes SIG UI project designed to let you explore, manage, and debug cluster resources directly from a browser. Cluster API (CAPI) is a Kubernetes sub-project that brings declarative, Kubernetes-style APIs to cluster lifecycle management. It lets platform teams provision, upgrade, and manage the lifecycle of Kubernetes clusters using standard Kubernetes objects stored and reconciled in a management cluster. Managing Cluster API resources has historically required raw kubectl commands and deep familiarity with ownership hierarchies. The Headlamp Cluster API plugin brings visual clarity, faster debuggβ¦
KUBERNETESβ
β
β
Volcano is a cloud native batch scheduler for Kubernetes, built for high-performance computing, AI/ML, and other batch workloads. Headlamp is an extensible Kubernetes web UI. With its plugin system, Headlamp can surface APIs and workflows beyond the built-in Kubernetes resources. The Volcano plugin brings core Volcano resources into Headlamp so you can inspect workload state, queue behavior, and gang scheduling details in one place. Kubernetes was originally designed around long-running services, where applications are expected to start and remain available over time. Batch, AI/ML, and HPC workloads often behave differently: jobs arrive dynaβ¦
KUBERNETESβ
β
β
Headlamp is an open-source, extensible Kubernetes SIG UI project designed to let you explore, manage, and debug cluster resources. Knative brings serverless workloads to Kubernetes, handling traffic routing, autoscaling, and revision management so teams can deploy and iterate without fighting infrastructure. But operating Knative workloads day-to-day can be difficult, there's still a lot of jumping between the kn CLI, kubectl, and the Kubernetes UI to get a full picture of what's running. We built the Headlamp Knative plugin to bridge that very gap, allowing operators to inspect, understand and act on their workloads all from a single place.β¦
KUBERNETESβ
β
β
The rising popularity of AI, Edge, and Telecommunications workloads on Kubernetes has led to new requirements for hardware management. We now need hardware specification beyond CPU time and memory allocations. This includes allocating GPUs, TPUs, network interfaces, and other hardware, sometimes after pod start and occasionally through time-sharing. Efficiently managing this specialized hardware is the mission of the Device Management Working Group. Their cornerstone project, Dynamic Resource Allocation (DRA), recently graduated to GA, marking a fundamental shift in how the project handles hardware-intensive workloads at scale. In this spotlβ¦