add workload placement docs

This commit is contained in:
Seth Jennings
2017-08-15 11:14:01 -05:00
committed by Zach Corleissen
parent 35dc007365
commit 5b4ef96268
2 changed files with 146 additions and 0 deletions
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@@ -140,6 +140,7 @@ toc:
- docs/tasks/administer-cluster/cpu-memory-limit.md
- docs/tasks/administer-cluster/out-of-resource.md
- docs/tasks/administer-cluster/reserve-compute-resources.md
- docs/tasks/administer-cluster/cpu-management-policies.md
- docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods.md
- docs/tasks/administer-cluster/declare-network-policy.md
- title: Install Network Policy Provider
@@ -0,0 +1,145 @@
---
title: Control CPU Management Policies on the Node
---
* TOC
{:toc}
Kubernetes keeps many aspects of how pods execute on nodes abstracted
from the user. This is by design.  However, some workloads require
stronger guarantees in terms of latency and/or performance in order to operate
acceptably.  The kubelet provides methods to enable more complex workload
placement policies while keeping the abstraction free from explicit placement
directives.
## CPU Management Policies
By default, the kubelet uses [CFS quota](https://en.wikipedia.org/wiki/Completely_Fair_Scheduler)
to enforce pod CPU limits.  When the node runs many CPU bound pods,
the workload can move to different CPU cores depending on
whether the pod is throttled and which CPU cores are available at
scheduling time.  Many workloads are not sensitive to this migration and thus
work fine without any intervention.
However, in workloads where CPU cache affinity and scheduling latency
significantly affect workload performance, the kubelet allows alternative CPU
management policies to determine some placement preferences on the node.
Enable these management policies with the `--cpu-manager-policy` kubelet
option.  There are two supported policies:
* `none`: the default, which represents the existing scheduling behavior
* `static`: allows pods with certain resource characteristics to be
granted increased CPU affinity and exclusivity on the node.
### None policy
The `none` policy explicitly enables the existing default CPU
affinity scheme, providing no affinity beyond what the OS scheduler does
automatically.  Limits on CPU usage for
[Guaranteed pods](/docs/tasks/configure-pod-container/quality-service-pod)
are enforced using CFS quota.
### Static policy
The `static` policy allows containers in `Guaranteed` pods with integer CPU
`requests` access to exclusive CPUs on the node.  This exclusivity is enforced
using the [cpuset cgroup controller](https://www.kernel.org/doc/Documentation/cgroup-v1/cpusets.txt).
**Note:** System services such as the container runtime and the kubelet itself can continue to run on these exclusive CPUs.  The exclusivity only extends to other pods.
{: .note}
This policy manages a shared pool of CPUs that initially contains all CPUs in the
node minus any reservations by the kubelet `--kube-reserved` or
`--system-reserved` options. CPUs reserved by these options are taken, in
integer quantity, from the initial shared pool in ascending order by physical
core ID.  This shared pool is the set of CPUs on which any containers in
`BestEffort` and `Burstable` pods run. Containers in `Guaranteed` pods with fractional
cpu `requests` also run on CPUs in the shared pool. Only containers that are
both part of a `Guaranteed` pod and have integer CPU `requests` are assigned
exclusive CPUs.
**Note:** When reserving CPU with `--kube-reserved` or `--system-reserved` options, it is advised to use *integer* CPU quantities.
{: .note}
As `Guaranteed` pods whose containers fit the requirements for being statically
assigned are scheduled to the node, CPUs are removed from the shared pool and
placed in the cpuset for the container.  CFS quota is not used to bound
the CPU usage of these containers as their usage is bound by the scheduling domain
itself. In others words, the number of CPUs in the container cpuset is equal to the integer
CPU `limit` specified in the pod spec.  This static assignment increases CPU
affinity and decreases context switches due to throttling for the CPU bound
workload.
In the event that the shared pool is depleted the kubelet takes two actions:
* Evict all pods that include a container that does not specify a `cpu`
quantity in `requests` as those pods now have no CPUs on which to run.
* Set a `NodeCPUPressure` node condition to `true` in the node status. When
this condition is true, the scheduler will not assign any pod to the node
that has a container which lacks a `cpu` quantity in `requests`.
Consider the containers in the following pod specs:
```yaml
spec:
containers:
- name: nginx
image: nginx
```
This pod runs in the `BestEffort` QoS class because no resource `requests` or
`limits` are specified. It is evicted if shared pool is depleted. It runs
in the shared pool.
```yaml
spec:
containers:
- name: nginx
image: nginx
resources:
limits:
memory: "200Mi"
requests:
memory: "100Mi"
```
This pod runs in the `Burstable` QoS class because resource `requests` do not
equal `limits` and the `cpu` quantity is not specified. It is
evicted if shared pool is depleted. It runs in the shared pool.
```yaml
spec:
containers:
- name: nginx
image: nginx
resources:
limits:
memory: "200Mi"
cpu: "2"
requests:
memory: "100Mi"
cpu: "1"
```
This pod runs in the `Burstable` QoS class because resource `requests` do not
equal `limits`. The non-zero `cpu` quantity in `requests` prevents the
shared pool from depleting. It runs in the shared pool.
```yaml
spec:
containers:
- name: nginx
image: nginx
resources:
limits:
memory: "200Mi"
cpu: "2"
```
This pod runs in the `Guaranteed` QoS class because only `limits` are specified
and `requests` are set equal to `limits` when not explicitly specified. The
`nginx` container is granted 2 exclusive CPUs.