An essential part of building a system is ensuring it will chug along without hiccups. The fewer outages there are, the happier your customers and your team will be.
Kubernetes has powerful scaling and self-healing capabilities, but with so many interconnected components, it’s not easy to keep it working properly.
Any disruption or failure can have severe consequences, such as service downtime and data loss, so having a well-designed disaster recovery plan is crucial. It will dictate how well your system will recover in the event of a hardware or network failure, human error or natural disaster affecting your data center.
This guide will walk you through some common disaster recovery strategies for Kubernetes applications, so you are better equipped to create a reliable backup and restore system.
Disaster Recovery Planning
Disaster recovery planning involves assessing potential risk and disaster scenarios, defining recovery objectives and establishing a dedicated team to manage the disaster recovery process when there's a mishap.
Assessing Risk and Potential Disaster Scenarios
The process starts with identifying potential risks (hardware failures, network outages, etc.) and then evaluating each scenario’s likelihood and potential impact. You can then prioritize recovery measures based on potential severity and frequency. This way you can allocate more resources to higher-impact, higher-probability risks in the DR planning process.
Defining Recovery Objectives
A disaster recovery plan's effectiveness can be assessed using clear recovery objectives that are aligned with your business requirements and regulatory obligations. The three most important objectives are:
Determine the recovery time objective (RTO), or the longest period you can tolerate being without your apps or data.
Define the recovery point objective (RPO), or the maximum data loss you can afford in a disaster. RPO represents the point in time at which data must be recovered to ensure minimal data loss.
Evaluate maximum tolerable downtime (MTD), or the longest period of downtime before you fail to achieve your service level agreement (SLA) and get the system back up and running.
For example, if your RTO is one hour, RPO one day and MTD four hours, you should aim to have your applications and services restored within one hour of a disaster, retrieve data going back at least one day with minimal data loss and make sure the system is fully operational within four hours to comply with your SLA.
How critical different applications are is another important consideration. Your DR plan must ensure the most business-critical components get restored ahead of the auxiliary ones.
Establishing a Disaster Recovery Team
Having a dedicated, centralized team ready to activate and manage the DR process is crucial. It should be a cross functional team, whose members can establish communication channels for efficient coordination during a disaster. In addition to members who are capable of executing the recovery process the team should have a designated person who can keep stakeholders well informed.
Backup and Recovery
Containers are fundamentally different from virtual machines. This means the DR plan for Kubernetes looks different from the more traditional methods. With Kubernetes, the focus is on making sure your cluster components are restored and your application contains the logic and data it needs.
To better understand Kubernetes backup and recovery, let’s take a closer look at the various cluster and application backup processes.
Cluster Backup
Backing up a Kubernetes cluster involves backing up the components (API objects) and configuration (state stored in etcd) of the cluster. This helps maintain cluster state and the metadata that’s necessary to rebuild the cluster and restore its functionality.
Backing Up etcd Data
etcd is a key-value store that stores Kubernetes cluster data, such as the state of pods, services and deployments. The database can endure hardware failures and sustain up to (N-1)/2 total permanent failures for an N-member cluster. However, if there are more permanent failures, you can use the etcd member's keyspace snapshot to facilitate the backup.
For example, you can store an `$ENDPOINT` state in the `snapshot.db` file with the following command:
$ ETCDCTL_API=3 etcdctl --endpoints $ENDPOINT snapshot save snapshot.dbThis process can be automated using a cron job to store recent backups. You can learn more about backing up an etcd cluster in the official documentation.
Backing Up API Objects
API objects, such as deployment configurations and access controls, also define the desired state of your applications and services. You can back these up by exporting their definitions using the Kubernetes API, kubectl or third-party tools and scripts. You must store these backups securely, as they will be required during the restore phase.
An example Bash script for backing up all the objects looks like this:
for n in $(kubectl get -o=name pvc,configmap,secret,ingress,service,serviceaccount,statefulset,hpa,job,deployment,cronjob)
do
mkdir -p $(dirname $n)
kubectl get -o=yaml $n > $n.yaml
doneRestoring etcd Data
Once the backup is complete, you can restore things from the previous backup if things go wrong.
For example, in the event of a disaster you can restore etcd data from the backup. This involves deploying a new etcd cluster and restoring the data using the earlier snapshots or backups for a single cluster with the following command:
$ ETCDCTL_API=3 etcdctl --endpoints 10.2.0.9:2379 snapshot restore snapshotdbAfter restoring from your snapshot, you should be able to start an etcd service with the new data directories while also serving the keyspace provided by the snapshot.
Recreating API Objects
Once the etcd data is restored, you can recreate the API objects using the object backups. Apply the exported definitions or manifests to recreate the desire