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Kubernetes 1.34 is here, and it brings a huge wave of enhancements for Dynamic Resource Allocation (DRA)! This
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release marks a major milestone with the Structured Parameters feature graduating to General Availability (GA),
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unlocking the full potential of how you manage devices on Kubernetes. On top of that, several key features have
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- moved to beta, and a fresh batch of new alpha features promise even more expresiveness and flexibility.
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+ moved to beta, and a fresh batch of new alpha features promise even more expressiveness and flexibility.
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Let's dive into what's new for DRA in Kubernetes 1.34!
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### Structured Parameters is Now GA
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- The headline feature for DRA in this release is the graduation of Structured Parameters to General Availability.
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+ The headline feature of the v1.34 release is that the core of DRA has graduated to General Availability.
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Kubernetes Dynamic Resource Allocation (DRA) provides a flexible framework for managing specialized hardware
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- resources such as GPUs and FPGAs. It provices a flexible API for letting workloads specify the properties of the
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+ and infrastructure resources, such as GPUs or FPGAs. DRA provides APIs that enable each workload to specify the properties of the
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devices it needs, but leaving it to the scheduler to allocate actual devices, allowing increased reliability and
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improved utilization of expensive hardware.
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With the graduation to GA, DRA is stable and will be part of Kubernetes for the long run. The community can still
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expect a steady stream of new features being added to DRA over the next several Kubernetes releases, but they will
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not make any breaking changes to DRA. So users and developers of DRA drivers can start adopting DRA with confidence.
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- Starting with Kubernetes 1.34, DRA will be enabled by default, as will DRA features that have reached beta.
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+ Starting with Kubernetes 1.34, DRA is enabled by default; DRA features that have reached beta are also enabled by default.
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+ That's because the default API version for DRA is now the stable ` v1 ` version, and not the earlier versions
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+ (eg: ` v1beta1 ` or ` v1beta2 ` ) that needed explicit opt in.
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### Features promoted to beta
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Several powerful features have been promoted to beta, adding more control, flexibility, and observability to resource
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management with DRA.
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- [ Admin Access] ( /docs/concepts/scheduling-eviction/dynamic-resource-allocation/#admin-access ) has been updated so that
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- only users with access to a namespace with the resource.k8s.io/admin-access: "true" label are authorized to create
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- ResourceClaim or ResourceClaimTemplates objects with the adminAccess field within the namespace. This grants
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- administrators access to in-use devices and may enable additional permissions when making the device available in a
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- container. This ensures that non-admin users cannot misuse the feature.
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+ [ Admin access labelling] ( /docs/concepts/scheduling-eviction/dynamic-resource-allocation/#admin-access ) has been updated.
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+ In v1.34, you can restrict device support to people (or software) authorized to use it. This is meant
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+ as a way to avoid privilege escalation through use of hardware devices that can bypass other security controls.
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+ The restriction works by ensuring that only users with access to a namespace with the
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+ ` resource.k8s.io/admin-access: "true" ` label are authorized to create
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+ ResourceClaim or ResourceClaimTemplates objects with the ` adminAccess ` field set to true. This ensures that non-admin users cannot misuse the feature.
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[ Prioritized List] ( /docs/concepts/scheduling-eviction/dynamic-resource-allocation/#prioritized-list ) lets users specify
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a list of acceptable devices for their workloads, rather than just a single type of device. So while the workload
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might run best on a single high-performance GPU, it might also be able to run on 2 mid-level GPUs. The scheduler will
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attempt to satisfy the alternatives in the list in order, so the workload will be allocated the best set of devices
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- available in the cluster .
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+ available on the node .
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- The PodResources API has been updated to include resources allocated through DRA. This allows node monitoring agents
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+ The kubelet's API has been updated to report on Pod resources allocated through DRA. This allows node monitoring agents
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to know the allocated DRA resources for Pods on a node and makes it possible to use the DRA information in the PodResources API
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to develop new features and integrations.
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### New alpha features
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Kubernetes 1.34 also introduces several new alpha features that give us a glimpse into the future of resource management with DRA.
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- [ Extended Resource ] ( /docs/concepts/scheduling-eviction/dynamic-resource-allocation/#extended-resource ) support in DRA allow
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- cluster administrators to advertise DRA-managed resources as extended resources , allowing developers to consume them using
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+ [ Extended resource mapping ] ( /docs/concepts/scheduling-eviction/dynamic-resource-allocation/#extended-resource ) support in DRA allows
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+ cluster administrators to advertise DRA-managed resources as _ extended resources _ , allowing developers to consume them using
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the familiar, simpler request syntax while still benefiting from dynamic allocation. This makes it possible for existing
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workloads to start using DRA without modifications, simplifying the transition to DRA for both application developers and
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cluster administrators.
@@ -76,7 +79,7 @@ unhealthy device and respond properly.
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### What’s next?
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- While DRA got promoted to GA this cycle, the hard on DRA doesn't stop. There are several features in alpha and beta that
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+ While DRA got promoted to GA this cycle, the hard work on DRA doesn't stop. There are several features in alpha and beta that
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we plan to bring to GA in the next couple of releases and we are looking to continue to improve performance, scalability
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and reliability of DRA. So expect an equally ambitious set of features in DRA for 1.35.
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