# Kubernetes v1.36: Pod-Level Resource Managers (Alpha)

DevFeed: [Kubernetes v1.36: Pod-Level Resource Managers (Alpha)](<https://devfeed.tech/articles/kubernetes-v1-36-pod-level-resource-managers-alpha-4544.md>)

Original publisher: [Read original article](<https://kubernetes.io/blog/2026/05/01/kubernetes-v1-36-feature-pod-level-resource-managers-alpha/>)

Author: Kevin Torres Martinez

Published: 2026-05-01T18:35:00Z

Content type: article

Language: en

Sources: [Kubernetes Blog](<https://devfeed.tech/sources/kubernetes-blog.md>)

Topics: [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [Containers](<https://devfeed.tech/topics/containers.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>)

Tags: [backup](<https://devfeed.tech/tags/backup.md>), [containers](<https://devfeed.tech/tags/containers.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [database](<https://devfeed.tech/tags/database.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [latency](<https://devfeed.tech/tags/latency.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [performance](<https://devfeed.tech/tags/performance.md>), [resource](<https://devfeed.tech/tags/resource.md>), [resources](<https://devfeed.tech/tags/resources.md>)

## AI overview

Kubernetes v1.36 introduces alpha support for pod-level resource managers. The feature extends Topology, CPU, and Memory Managers from per-container allocation to pod-level resource specifications, enabling hybrid allocation models for performance-sensitive workloads while preserving NUMA alignment.

## Source excerpt

Kubernetes v1.36 introduces Pod-Level Resource Managers as an alpha feature, bringing a more flexible and powerful resource management model to performance-sensitive workloads. This enhancement extends the kubelet's Topology, CPU, and Memory Managers to support pod-level resource specifications (.spec.resources), evolving them from a strictly per-container allocation model to a pod-centric one. Why do we need pod-level resource managers? When running performance-critical workloads such as machine learning (ML) training, high-frequency trading applications, or low-latency databases, you often need exclusive, NUMA-aligned resources for your primary application containers to ensure predictable performance. However, modern Kubernetes pods rarely consist of just one container. They frequently include sidecar containers for logging, monitoring, service meshes, or data ingestion. Before this feature, this created a trade-off, to get NUMA-aligned, exclusive resources for your main application, you had to allocate exclusive, integer-based CPU resources to every container in the pod. This might be wasteful for lightweight sidecars. If you didn't do this, you forfeited the pod's Guaranteed Quality of Service (QoS) class entirely, losing the performance benefits. Introducing pod-level resource managers Enabling pod-level resources support for the resource managers (via the PodLevelResourceManagers and PodLevelResources feature gates) allows the kubelet to create hybrid resource allocation models. This brings flexibility and efficiency to high-performance workloads without sacrificing NUMA alignment. Real-world use cases Here are a few practical scenarios demonstrating how this feature can be applied, depending on the configured Topology Manager scope: 1. Tightly-coupled database (Topology manager's pod scope) Consider a latency-sensitive database pod that includes a main database container, a local metrics exporter, and a backup agent sidecar. When configured with the pod Topol