[zh] Sync administer-cluster/memory-manager.md
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windsonsea
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---
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title: WindowsCPUAndMemoryAffinity
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content_type: feature_gate
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_build:
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list: never
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render: false
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stages:
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- stage: alpha
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defaultValue: false
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fromVersion: "1.32"
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---
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<!--
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Add CPU and Memory Affinity support to Windows nodes with [CPUManager](/docs/tasks/administer-cluster/cpu-management-policies/#windows-support),
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[MemoryManager](/docs/tasks/administer-cluster/memory-manager/#windows-support)
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and topology manager.
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-->
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使用 [CPUManager](/zh-cn/docs/tasks/administer-cluster/cpu-management-policies/#windows-support)、
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[MemoryManager](/zh-cn/docs/tasks/administer-cluster/memory-manager/#windows-support)
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和拓扑管理器，为 Windows 节点提供 CPU 和内存亲和性支持。
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@ -1,7 +1,7 @@
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---
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title: 使用 NUMA 感知的内存管理器
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content_type: task
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min-kubernetes-server-version: v1.21
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min-kubernetes-server-version: v1.32
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weight: 410
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---
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@ -13,7 +13,7 @@ reviewers:
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- derekwaynecarr
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content_type: task
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min-kubernetes-server-version: v1.21
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min-kubernetes-server-version: v1.32
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weight: 410
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-->
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@ -64,8 +64,8 @@ To align memory resources with other requested resources in a Pod spec:
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- CPU 管理器应该被启用，并且在节点（Node）上要配置合适的 CPU 管理器策略，
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参见[控制 CPU 管理策略](/zh-cn/docs/tasks/administer-cluster/cpu-management-policies/)；
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- 拓扑管理器要被启用，并且要在节点上配置合适的拓扑管理器策略，参见
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[控制拓扑管理器策略](/zh-cn/docs/tasks/administer-cluster/topology-manager/)。
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- 拓扑管理器要被启用，并且要在节点上配置合适的拓扑管理器策略，
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参见[控制拓扑管理器策略](/zh-cn/docs/tasks/administer-cluster/topology-manager/)。
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<!--
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Starting from v1.22, the Memory Manager is enabled by default through `MemoryManager`
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@ -87,9 +87,9 @@ in order to enable the Memory Manager feature.
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这样内存管理器特性才会被启用。
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<!--
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## How Memory Manager Operates?
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## How does the Memory Manager Operate?
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-->
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## 内存管理器如何运作？
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## 内存管理器如何运作？ {#how-does-the-memory-manager-operate}
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<!--
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The Memory Manager currently offers the guaranteed memory (and hugepages) allocation
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@ -101,19 +101,19 @@ prepare and deploy a `Guaranteed` pod as illustrated in the section
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-->
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内存管理器目前为 Guaranteed QoS 类中的 Pod 提供可保证的内存（和大页面）分配能力。
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若要立即将内存管理器启用，可参照[内存管理器配置](#memory-manager-configuration)节中的指南，
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之后按[将 Pod 放入 Guaranteed QoS 类](#placing-a-pod-in-the-guaranteed-qos-class)
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节中所展示的，准备并部署一个 `Guaranteed` Pod。
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之后按[将 Pod 放入 Guaranteed QoS 类](#placing-a-pod-in-the-guaranteed-qos-class)节中所展示的，
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准备并部署一个 `Guaranteed` Pod。
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<!--
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The Memory Manager is a Hint Provider, and it provides topology hints for
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the Topology Manager which then aligns the requested resources according to these topology hints.
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It also enforces `cgroups` (i.e. `cpuset.mems`) for pods.
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On Linux, it also enforces `cgroups` (i.e. `cpuset.mems`) for pods.
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The complete flow diagram concerning pod admission and deployment process is illustrated in
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[Memory Manager KEP: Design Overview][4] and below:
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-->
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内存管理器是一个提示驱动组件（Hint Provider），负责为拓扑管理器提供拓扑提示，
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后者根据这些拓扑提示对所请求的资源执行对齐操作。
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内存管理器也会为 Pods 应用 `cgroups` 设置（即 `cpuset.mems`）。
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在 Linux 上，内存管理器也会为 Pod 应用 `cgroups` 设置（即 `cpuset.mems`）。
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与 Pod 准入和部署流程相关的完整流程图在[Memory Manager KEP: Design Overview][4]，
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下面也有说明。
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@ -183,6 +183,21 @@ NUMA 节点的分组，从而扩展内存容量。解决这个问题的详细描
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中。同时，关于 NUMA 分组是如何管理的，你还可以参考文档
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[Memory Manager KEP: Simulation - how the Memory Manager works? (by examples)][1]。
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<!--
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### Windows Support
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-->
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### Windows 支持 {#windows-support}
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{{< feature-state feature_gate_name="WindowsCPUAndMemoryAffinity" >}}
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<!--
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Windows support can be enabled via the `WindowsCPUAndMemoryAffinity` feature gate
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and it requires support in the container runtime.
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Only the [BestEffort Policy](#policy-best-effort) is supported on Windows.
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-->
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Windows 支持可以通过 `WindowsCPUAndMemoryAffinity` 特性门控来启用，
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并且需要容器运行时的支持。在 Windows 上，仅支持 [BestEffort 策略](#policy-best-effort)。
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<!--
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## Memory Manager configuration
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-->
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@ -208,13 +223,15 @@ node stability (section [Reserved memory flag](#reserved-memory-flag)).
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Memory Manager supports two policies. You can select a policy via a `kubelet` flag `--memory-manager-policy`:
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* `None` (default)
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* `Static`
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* `Static` (Linux only)
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* `BestEffort` (Windows Only)
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-->
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内存管理器支持两种策略。你可以通过 `kubelet` 标志 `--memory-manager-policy`
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来选择一种策略：
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* `None` （默认）
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* `Static`
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* `None`（默认）
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* `Static`（仅 Linux）
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* `BestEffort`（仅 Windows）
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<!--
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#### None policy {#policy-none}
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@ -252,6 +269,38 @@ and does not reserve the memory in the internal [NodeMap][2] object.
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对 `BestEffort` 或 `Burstable` Pod 而言，因为不存在对有保障的内存资源的请求，
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`Static` 内存管理器策略会返回默认的拓扑提示，并且不会通过内部的[节点映射][2]对象来预留内存。
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<!--
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#### BestEffort policy {#policy-best-effort}
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-->
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#### BestEffort 策略 {#policy-best-effort}
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{{< feature-state feature_gate_name="WindowsCPUAndMemoryAffinity" >}}
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<!--
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This policy is only supported on Windows.
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On Windows, NUMA node assignment works differently than Linux.
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There is no mechanism to ensure that Memory access only comes from a specific NUMA node.
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Instead the Windows scheduler will select the most optimal NUMA node based on the CPU(s) assignments.
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It is possible that Windows might use other NUMA nodes if deemed optimal by the Windows scheduler.
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-->
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此策略仅 Windows 上支持。
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在 Windows 上，NUMA 节点分配方式与 Linux 上不同。
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没有机制确保内存访问仅来自特定的 NUMA 节点。
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相反，Windows 调度器将基于 CPU 的分配来选择最优的 NUMA 节点。
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如果 Windows 调度器认为其他 NUMA 节点更优，Windows 可能会使用其他节点。
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<!--
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The policy does track the amount of memory available and requested through the internal [NodeMap][2].
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The memory manager will make a best effort at ensuring that enough memory is available on
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a NUMA node before making the assignment.
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This means that in most cases memory assignment should function as expected.
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-->
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此策略会通过内部的 [NodeMap][2] 跟踪可用和请求的内存量。
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内存管理器将尽力确保在进行分配之前，NUMA 节点上有足够的内存可用。
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这意味着在大多数情况下，内存分配的工作模式是符合预期的。
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<!--
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### Reserved memory flag
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-->
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@ -431,22 +480,35 @@ Here is an example of a correct configuration:
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下面是一个正确配置的示例：
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```shell
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--feature-gates=MemoryManager=true
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--kube-reserved=cpu=4,memory=4Gi
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--system-reserved=cpu=1,memory=1Gi
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--memory-manager-policy=Static
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--reserved-memory '0:memory=3Gi;1:memory=2148Mi'
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```
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<!--
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Prior to Kubernetes 1.32, you also need to add
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-->
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在 Kubernetes 1.32 之前，你还需要添加：
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```shell
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--feature-gates=MemoryManager=true
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```
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<!--
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Let us validate the configuration above:
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1. `kube-reserved + system-reserved + eviction-hard(default) = reserved-memory(0) + reserved-memory(1)`
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1. `4GiB + 1GiB + 100MiB = 3GiB + 2148MiB`
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1. `5120MiB + 100MiB = 3072MiB + 2148MiB`
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1. `5220MiB = 5220MiB` (which is correct)
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-->
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我们对上面的配置做一个检查：
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1. `kube-reserved + system-reserved + eviction-hard(default) = reserved-memory(0) + reserved-memory(1)`
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1. `4GiB + 1GiB + 100MiB = 3GiB + 2148MiB`
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1. `5120MiB + 100MiB = 3072MiB + 2148MiB`
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1. `5220MiB = 5220MiB` （这是对的）
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1. `5220MiB = 5220MiB`（这是对的）
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<!--
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## Placing a Pod in the Guaranteed QoS class
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@ -457,7 +519,7 @@ The Memory Manager provides specific topology hints to the Topology Manager for
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For pods in a QoS class other than `Guaranteed`, the Memory Manager provides default topology hints
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to the Topology Manager.
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-->
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## 将 Pod 放入 Guaranteed QoS 类 {#placing-a-pod-in-the-guaranteed-qos-class}
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## 将 Pod 放入 Guaranteed QoS 类 {#placing-a-pod-in-the-guaranteed-qos-class}
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若所选择的策略不是 `None`，则内存管理器会辨识处于 `Guaranteed` QoS 类中的 Pod。
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内存管理器为每个 `Guaranteed` Pod 向拓扑管理器提供拓扑提示信息。
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@ -535,7 +597,7 @@ became rejected at a node:
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- Pod 状态 - 可表明拓扑亲和性错误
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- 系统日志 - 包含用来调试的有价值的信息，例如，关于所生成的提示信息
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- 状态文件 - 其中包含内存管理器内部状态的转储（包含[节点映射和内存映射][2]）
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- 从 v1.22 开始，[设备插件资源 API](#device-plugin-resource-api)
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- 从 v1.22 开始，[设备插件资源 API](#device-plugin-resource-api)
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可以用来检索关于为容器预留的内存的信息
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<!--
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@ -758,7 +820,7 @@ i.e., in the `"memory"` section of NUMA node `0` (`"free":0`) and NUMA node `1`
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So, the total amount of free "conventional" memory in this group is equal to `0 + 103739236352` bytes.
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-->
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例如，NUMA 分组中空闲的“常规”内存的总量可以通过将分组内所有 NUMA
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节点上空闲内存加和来计算，即将 NUMA 节点 `0` 和 NUMA 节点 `1` 的 `"memory"` 节
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节点上空闲内存加和来计算，即将 NUMA 节点 `0` 和 NUMA 节点 `1` 的 `"memory"` 节
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（分别是 `"free":0` 和 `"free": 103739236352`）相加，得到此分组中空闲的“常规”
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内存总量为 `0 + 103739236352` 字节。
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