Infrastructure intelligence

This article is a mirror of the original announcement Today, SIG etcd is releasing etcd v3.7.0, the latest minor release of the popular distributed key-value store and core Kubernetes component. v3.7 ships the long-requested RangeStream feature, delivers several other performance improvements, removes the last remnants of the legacy v2store, and completes a major protobuf overhaul. You can download etcd v3.7.0 here: Source code Binaries Official container images This release also includes new versions of the two core etcd dependencies, bbolt v1.5.0 and raft v3.7.0. For instructions on installing etcd, see the install documentation. For the full list of changes, see the etcd v3.7 changelog. A heartfelt thank you to all the contributors who made this release possible!

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 debugging, and simplified operations for platform teams, directly inside Headlamp.

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 dynamically, compete for limited resources, and may need multiple workers to start together before useful work can begin. Volcano extends Kubernetes with concepts such as queues, priorities, quotas, and gang scheduling.

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. This plugin was built as part of the LFX mentorship. Here's a tour of what we shipped.

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 our ongoing SIG Spotlight series, we shine a light on the groups that keep the Kubernetes project moving forward. This time, we catch up with SIG Storage, the group responsible for persistent data, volume management, and the interfaces that connect Kubernetes workloads to the storage systems beneath them. We spoke with Xing Yang, Co-Chair of SIG Storage and Software Engineer at VMware by Broadcom, about the SIG's history, the features shipping in recent Kubernetes releases, and where storage in Kubernetes is headed as AI workloads become the norm. Introductions Could you introduce yourself and share your role(s) within SIG Storage? My name is Xing Yang, a software engineer at VMware by Broadcom. I'm a co-chair in SIG Storage, alongside another co-chair Saad Ali from Google. There are also two Tech Leads in SIG Storage: Michelle Au from Google and Jan Šafránek from Red Hat.