Kubernetes Disaster Recovery

Automate Your Kubernetes Disaster Recovery

A critical component of a successful Kubernetes DR strategy starts with planning,  testing, and documenting procedures, with a goal to automate wherever possible. In a Kubernetes world, traditional tooling can lead to a manual approach to DR. It is important to automate processes to reduce the recovery time to a minimum and restore apps functionality within minutes.

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What is Disaster Recovery?

Disaster recovery (DR) is an organization's ability to respond to and recover from an event that negatively affects business operations. The goal of DR methods is to enable the organization to regain use of critical systems and IT infrastructure as soon as possible after a disaster occurs.

Application Protection

A Kubernetes application has to backup all Kubernetes control plane data stored in /etcd, all namespaces, and all persistent volumes that hold critical business data.

Automated Workflow Import and Restore

Using policy-driven automation to manage how backups are restored simplifies disaster recovery allowing developers and operations to lower risk and simplify execution.

Kubernetes DR Readiness

Fully automated failovers and app redeploys are the ultimate goal, and can make the difference shifting from hours or days to minutes for recovery.

Rafay Disaster Recovery Features

With Rafay, enterprises leverage an integrated platform for backup and disaster recovery of the Kubernetes control plane and application data across data centers, public clouds, and remote/edge locations. Platform and operations teams need an easy-to-use, scalable, and secure solution for backup/restore, disaster recovery, and migration of Kubernetes applications. In many cases, these teams have to build, integrate and support their own backup and restore capability. With Rafay's Backup and Restore Service, enterprises:

Centrally configure, automate and operationalize disaster recovery (DR)

Eliminate manual handling of backup credentials for enhanced security

Leverage easy to use workflows for creating and managing backups for the entire fleet of clusters

Have flexible controls to specify what data to include and exclude as part of the backup

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Sample K8s Operations POC Test Plan

Customize this plan for your K8s Operations POC

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Kubernetes CD FAQs:

How do I recover my Kubernetes cluster?

Rafay enables Automation Workflows for Backup & Restore of your Kubernetes clusters with reduced operational complexity. Leverage one step workflows to restore data from backups during disaster recovery events. Enabling backup for a cluster is as simple as enabling a toggle. The Backup agent will be automatically deployed to the cluster and configured with required backup credentials.

What is the difference between backup and disaster recovery?

The concepts of backup and disaster recovery are quite distinct. A Backup process makes copies of data, applications, configurations and critical information multiple times on a periodical basis and requires a restore process in order to retrieve whenever it is required. A Disaster Recovery process has the objective of quickly reestablishing access to applications, data, and IT resources after an outage.

What is RTO and RPO in disaster recovery?

Two essential indicators to consider as part of a disaster recovery plan are Recovery Time Objective (RTO) and Recovery Point Objective (RPO). RTO is the length of downtime you can allow before recovery, and RPO is the amount of data you can afford to lose.

What happens if ETCD goes down?

In the event of a ETCD failure, running workloads may continue operating, however the Kubernetes cluster cannot make any changes to its state given it won’t have where to register this. No new pods can be enabled or scheduled until the etcd cluster is recovered.

What if Kubernetes master goes down?

The master Kubernetes node controls all the worker nodes of a cluster. It is recommended that a cluster is set up with a multi-master architecture to ensure that if one master node fails, any other master node can ensure that your cluster continues to work smoothly. On a single-master architecture, if the master node fails it will not be possible to create new services, pods, etc. and the cluster might fail.