63f77b5264
Change-Id: I85d9847e98ccc3382a51d10dadb9fb8535d0b704 Signed-off-by: Suzana Fernandes <Suzana.Fernandes@windriver.com>
54 lines
2.3 KiB
ReStructuredText
54 lines
2.3 KiB
ReStructuredText
.. WARNING: Add no lines of text between the label immediately following
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.. and the title.
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.. _kubernetes-memory-manager-policies-3de9d87855bc:
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==================================
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Kubernetes Memory Manager Policies
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==================================
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Kubernetes memory manager policies manage memory allocation for pods with a
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focus on |NUMA| topology and performance optimization. You can define the
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policy using the kube-memory-mgr-policy host label via |CLI|, with the supported
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values.
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The **kube-memory-mgr-policy** host label supports the values ``none`` (default)
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and ``static``.
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For example:
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.. code-block:: none
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~(keystone)admin)$ system host-lock worker-1
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~(keystone)admin)$ system host-label-assign --overwrite worker-1 kube-memory-mgr-policy=static
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~(keystone)admin)$ system host-unlock worker-1
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Setting to static, the policy ensures NUMA-aware memory allocation for
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guaranteed |QoS| pods, reserving memory to meet their requirements and reduce
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latency. Memory for system processes can also be reserved using the
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``--reserved-memory`` flag, enhancing node stability. For the ``BestEffort``
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and ``Burstable`` pods, no memory is reserved, and the default topology hints
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are used.
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This approach enables better performance for workloads that require predictable
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memory usage, but requires careful configuration to ensure compatibility with
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system resources.
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For configuration options and detailed examples, consult the Kubernetes
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documentation at `https://kubernetes.io/docs/tasks/administer-cluster/memory-manager/ <https://kubernetes.io/docs/tasks/administer-cluster/memory-manager/>`__.
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-----------
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Limitations
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-----------
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The interaction between the ``kube-memory-mgr-policy=static`` policy and the
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topology manager policy ``restricted`` can cause pods not to be scheduled or
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started, even when there is sufficient memory available. This is due to the
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restrictive design of the NUMA-aware memory manager, which prevents the same
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|NUMA| node from being used for both single and multi-NUMA allocations. It is
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important that you understand the implications of these memory management
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policies and configure your systems accordingly to avoid unexpected failures.
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For detailed configuration options and examples, refer to the Kubernetes
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documentation at https://kubernetes.io/docs/tasks/administer-cluster/memory-manager/. |