2017-02-07 14:01:02 +00:00
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# Overview
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Distributed system such as Kubernetes are designed to be resilient to the
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failures. More details about Kubernetes High-Availability (HA) may be found at
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[Building High-Availability Clusters](https://kubernetes.io/docs/admin/high-availability/)
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To have a simple view the most of parts of HA will be skipped to describe
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Kubelet<->Controller Manager communication only.
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By default the normal behavior looks like:
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1. Kubelet updates it status to apiserver periodically, as specified by
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`--node-status-update-frequency`. The default value is **10s**.
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2020-02-26 12:46:28 +00:00
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2. Kubernetes controller manager checks the statuses of Kubelet every
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2017-02-07 14:01:02 +00:00
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`–-node-monitor-period`. The default value is **5s**.
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2018-09-30 03:31:57 +00:00
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3. In case the status is updated within `--node-monitor-grace-period` of time,
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2017-02-07 14:01:02 +00:00
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Kubernetes controller manager considers healthy status of Kubelet. The
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default value is **40s**.
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2020-02-26 12:46:28 +00:00
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> Kubernetes controller manager and Kubelet work asynchronously. It means that
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2017-02-07 14:01:02 +00:00
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> the delay may include any network latency, API Server latency, etcd latency,
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> latency caused by load on one's master nodes and so on. So if
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> `--node-status-update-frequency` is set to 5s in reality it may appear in
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> etcd in 6-7 seconds or even longer when etcd cannot commit data to quorum
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> nodes.
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2019-12-04 15:22:57 +00:00
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## Failure
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2017-02-07 14:01:02 +00:00
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Kubelet will try to make `nodeStatusUpdateRetry` post attempts. Currently
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`nodeStatusUpdateRetry` is constantly set to 5 in
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[kubelet.go](https://github.com/kubernetes/kubernetes/blob/release-1.5/pkg/kubelet/kubelet.go#L102).
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Kubelet will try to update the status in
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2018-09-04 11:17:05 +00:00
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[tryUpdateNodeStatus](https://github.com/kubernetes/kubernetes/blob/release-1.5/pkg/kubelet/kubelet_node_status.go#L312)
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2017-02-07 14:01:02 +00:00
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function. Kubelet uses `http.Client()` Golang method, but has no specified
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timeout. Thus there may be some glitches when API Server is overloaded while
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TCP connection is established.
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So, there will be `nodeStatusUpdateRetry` * `--node-status-update-frequency`
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attempts to set a status of node.
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At the same time Kubernetes controller manager will try to check
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`nodeStatusUpdateRetry` times every `--node-monitor-period` of time. After
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2021-01-08 15:20:53 +00:00
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`--node-monitor-grace-period` it will consider node unhealthy. Pods will then be rescheduled based on the
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[Taint Based Eviction](https://kubernetes.io/docs/concepts/scheduling-eviction/taint-and-toleration/#taint-based-evictions)
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timers that you set on them individually, or the API Server's global timers:`--default-not-ready-toleration-seconds` &
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``--default-unreachable-toleration-seconds``.
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2017-02-07 14:01:02 +00:00
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Kube proxy has a watcher over API. Once pods are evicted, Kube proxy will
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notice and will update iptables of the node. It will remove endpoints from
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services so pods from failed node won't be accessible anymore.
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2019-12-04 15:22:57 +00:00
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## Recommendations for different cases
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2017-02-07 14:01:02 +00:00
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## Fast Update and Fast Reaction
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2021-06-21 17:36:51 +00:00
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If `--node-status-update-frequency` is set to **4s** (10s is default).
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2017-02-07 14:01:02 +00:00
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`--node-monitor-period` to **2s** (5s is default).
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`--node-monitor-grace-period` to **20s** (40s is default).
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2021-01-08 15:20:53 +00:00
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`--default-not-ready-toleration-seconds` and ``--default-unreachable-toleration-seconds`` are set to **30**
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(300 seconds is default). Note these two values should be integers representing the number of seconds ("s" or "m" for
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seconds\minutes are not specified).
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2017-02-07 14:01:02 +00:00
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In such scenario, pods will be evicted in **50s** because the node will be
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2021-01-08 15:20:53 +00:00
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considered as down after **20s**, and `--default-not-ready-toleration-seconds` or
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``--default-unreachable-toleration-seconds`` occur after **30s** more. However, this scenario creates an overhead on
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etcd as every node will try to update its status every 2 seconds.
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2017-02-07 14:01:02 +00:00
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If the environment has 1000 nodes, there will be 15000 node updates per
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minute which may require large etcd containers or even dedicated nodes for etcd.
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> If we calculate the number of tries, the division will give 5, but in reality
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> it will be from 3 to 5 with `nodeStatusUpdateRetry` attempts of each try. The
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2018-09-19 08:47:58 +00:00
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> total number of attempts will vary from 15 to 25 due to latency of all
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2017-02-07 14:01:02 +00:00
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> components.
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## Medium Update and Average Reaction
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2021-06-21 17:36:51 +00:00
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Let's set `--node-status-update-frequency` to **20s**
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2021-01-08 15:20:53 +00:00
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`--node-monitor-grace-period` to **2m** and `--default-not-ready-toleration-seconds` and
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``--default-unreachable-toleration-seconds`` to **60**.
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2017-02-07 14:01:02 +00:00
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In that case, Kubelet will try to update status every 20s. So, it will be 6 * 5
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= 30 attempts before Kubernetes controller manager will consider unhealthy
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status of node. After 1m it will evict all pods. The total time will be 3m
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before eviction process.
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Such scenario is good for medium environments as 1000 nodes will require 3000
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etcd updates per minute.
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> In reality, there will be from 4 to 6 node update tries. The total number of
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> of attempts will vary from 20 to 30.
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## Low Update and Slow reaction
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2021-06-21 17:36:51 +00:00
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Let's set `--node-status-update-frequency` to **1m**.
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2021-01-08 15:20:53 +00:00
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`--node-monitor-grace-period` will set to **5m** and `--default-not-ready-toleration-seconds` and
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``--default-unreachable-toleration-seconds`` to **60**. In this scenario, every kubelet will try to update the status
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every minute. There will be 5 * 5 = 25 attempts before unhealthy status. After 5m,
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2017-02-07 14:01:02 +00:00
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Kubernetes controller manager will set unhealthy status. This means that pods
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will be evicted after 1m after being marked unhealthy. (6m in total).
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> In reality, there will be from 3 to 5 tries. The total number of attempt will
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> vary from 15 to 25.
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There can be different combinations such as Fast Update with Slow reaction to
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satisfy specific cases.
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