High availability is automatically enabled on MicroK8s for clusters with three or more nodes.
A highly available Kubernetes cluster is a cluster that can withstand a failure on any one of its components and continue serving workloads without interruption. There are three components necessary for a highly available Kubernetes cluster:
- There must be more than one node available at any time.
- The control plane must be running on more than one node so that losing a single node would not render the cluster inoperable.
- The cluster state must be in a datastore that is itself highly available.
This documentation describes the steps needed to form an HA cluster in MicroK8s and to check its state.
To achieve HA, you will need:
- To install a 1.19+ version of MicroK8s
- At least three nodes. For testing on a single machine, please see the documentation for installing on LXD
On Linux, you can install any 1.19+ by specifying a channel:
sudo snap install microk8s --classic --channel=1.19/stable
or update an existing installation with:
sudo snap refresh microk8s --classic --channel=1.19/stable
For Windows and macOS, you can update your installation with:
multipass exec microk8s -- sudo snap refresh microk8s --classic --channel=1.19/stable
(see the install docs for Windows and macOS if you need to install MicroK8s.)
As before, install a 1.19+ version of MicroK8s on at least two additional machines (or LXD containers).
Follow the usual procedure for clustering (described in the clustering documentation):
On the initial node, run:
This will output a command with a generated token such as
microk8s join 10.128.63.86:25000/567a21bdfc9a64738ef4b3286b2b8a69. Copy this command and run it from the next node. It may take a few minutes to successfully join.
Repeat this process (generate a token, run it from the joining node) for the third and any additional nodes.
Available with 1.20+
To make MicroK8s failure domain aware associate an integer to each failure domain and update the
/var/snap/microk8s/current/args/ha-conf with it. A restart of MicroK8s in the updated nodes is required (
microk8s.stop; microk8s.start). For example:
echo "failure-domain=42" > /var/snap/microk8s/current/args/ha-conf microk8s.stop microk8s.start
Run the status command:
From MicroK8s version 1.19, this will now inform you of the HA status and the addresses and roles of additional nodes. For example:
microk8s is running high-availability: yes datastore master nodes: 10.128.63.86:19001 10.128.63.166:19001 10.128.63.43:19001 datastore standby nodes: none
All nodes of the HA cluster run the master control plane. A subset of the cluster nodes (at least three) maintain a copy of the Kubernetes dqlite database. Database maintenance involves a voting process through which a leader is elected. Apart from the voting nodes there are non-voting nodes silently keeping a copy of the database. These nodes are on standby to take over the position of a departing voter. Finally, there are nodes that neither vote nor replicate the database. These nodes are called
spare. To sum up, the three node roles are:
voters: replicating the database, participating in leader election
standby: replicating the database, not participating in leader election
spare: not replicating the database, not participating in leader election
Cluster formation, database syncing, voter and leader elections are all transparent to the administrator.
The state of the current state of the HA cluster is shown with:
The output of the HA inspection reports:
- If HA is achieved or not.
- The voter and stand-by nodes.
Since all nodes of the HA cluster run the master control plane the
microk8s * commands are now available everywhere. Should one of the nodes crash we can move to any other node and continue working without much disruption.
Almost all of the HA cluster management is transparent to the admin and requires minimal configuration. The administrator can only add or remove nodes. To ensure the health of the cluster the following timings should be taken into account:
- If the leader node gets “removed” ungracefully, e.g. it crashes and never comes back, it will take up to 5 seconds for the cluster to elect a new leader.
- Promoting a non-voter to a voter takes up to 30 seconds. This promotion takes place when a new node enters the cluster or when a voter crashes.
To remove a node gracefully, first run the
leave command on the departing node:
The node will be marked as ‘NotReady’ (unreachable) in Kubernetes. To complete the removal of the departing node, issue the following on any of the remaining nodes:
microk8s remove-node <node>
In the case we are not able to call
microk8s leave from the departing node, e.g. due to a node crash, we need to call
microk8s remove-node with the
microk8s remove-node <node> --force
Certain add-ons download and “install” client binaries. These binaries will be available only on the node the add-on was enabled from. For example, the helm client that gets installed with
microk8s enable helm will be available only on the node the user issued the
microk8s enable command.
If you have an existing cluster, you have to refresh all nodes to at least v1.19, for example:
sudo snap refresh microk8s --channel=1.19/stable
You then need to enable HA clustering on the master node:
microk8s enable ha-cluster
Any machines which are already nodes in a cluster will need to exit and rejoin
in order to establish HA.
To do so, cycle through the nodes to drain, remove, and rejoin them:
microk8s kubectl drain <node> --ignore-daemonsets
On the node machine, force it to leave the cluster with:
Then enable HA with
microk8s enable ha-cluster and re-join the node to the cluster with a
microk8s add-node and
microk8s join issued on the master and node respectively.
MicroK8s ships the upstream Kubernetes so an etcd HA setup is also possible, see the upstream documentation on how this can be achieved: Kubernetes HA topology docs
The etcd approach is more involved and outside the scope of this document. Overall you will need to maintain your own etcd HA cluster. You will then need to configure the API server and flannel to point to that etcd. Finally you will need to provide a load balancer in front of the nodes acting as masters and configure the workers to reach the masters through the load-balanced endpoint.