Proven Techniques for Effective Kubernetes Disaster Recovery

DR requires updating the DR cluster as the primary data and metadata change. This can be accomplished by using cluster linking.

Only through careful planning, automation, documentation, and repeated testing of a DR plan can enterprises reduce recovery time to minutes and return apps to functionality.

Backup and Restore

Most businesses have mission-critical applications that need nearly 100% uptime. Backup and restore provides a safety net for these applications and the infrastructure behind them to continue operating during an unplanned outage. This is a critical component of any disaster recovery (DR) plan.

Backup and restore is one of the kubernetes disaster recovery best practices that involves capturing data from primary infrastructure and creating copies that can be used to recover applications in the event of a disaster or cyberattack. Many different back-ups and restore solutions are available, typically based on an organization’s scalability, data security, and physical distance (required between the production infrastructure and the backup location) requirements.

Kubernetes clusters have many moving parts, so choosing a solution that can provide granular restores to specific namespaces or containers within the cluster is important. An application-aware solution is also key – it will capture in-process transitions and save the state of applications at any given time, ensuring they are ready to resume operations after recovery. To enable rapid recovery, creating a secondary disaster recovery cluster in a different region or cloud than your primary is important. 


The ability to reroute traffic from a damaged server or network connection to another functioning component to avoid disruption and maintain operations. This is a critical capability, especially for mission-critical systems that can’t afford to experience even short periods of downtime.

The most common form of failover involves a cluster of servers, or nodes, connected by software and physical cables to provide either high availability (HA) or continuous availability (CA). These nodes are proactively monitored for failures or slowdowns, and the workload is automatically transferred to other nodes through a process known as failover.

With the advent of virtualization, servers, and other computing hardware can be configured with multiple paths and redundant components to improve failover reliability further. Some systems are designed to detect an alteration in the heartbeat signal of one server and take over immediately, allowing for a very short period of downtime. Other systems, called automated with manual approval configurations, alert a technician or data center and require them to initiate the switchover manually.


Cluster Linking makes it possible to replicate data from one cluster to another. For example, if you have a DR site, you can use Cluster Linking to make it available to your downstream Kubernetes clients, keeping them up-to-date with the latest data.

Suppose you want to enable a complete disaster recovery scenario. In that case, you should configure both your original and DR clusters to allow your consumers and producers to switch from the original to the DR cluster without interruption. This requires enabling consumer offset sync on the cluster link and ensuring that your applications can tolerate a little lagged data when you fail over to the DR cluster.

To enable this, you should create a cluster link with a service account with READ access to all of the topics on your original cluster (including mirrors). Then, create a new service account on your DR cluster with < DR-CLI-api-key> and < DR-CLI-api-secret> that uses those same keys.

Next, you should configure the mirror topics on your DR cluster to sync with the original Kafka topics so that when you failover, your applications will see the same data that they would have seen on the original cluster. You can do this by examining the /links/[link-name]/mirrors/topic-name>/ mirror_lags array and looking at the values under last_source_fetch_offset.

Replicating Data

Data replication copies the same data to multiple locations, on-premises, or across the cloud. This is useful for creating backups, enhancing scalability, and improving organizational reliability. It also ensures that all stakeholders can access organizational data whenever necessary, regardless of the geographic location or system.

The replication process can take place synchronously or asynchronously. A synchronous replication will copy data to all replica servers simultaneously. In contrast, an asynchronous replication will copy data to the replica servers after the source has already copied it.

Disaster recovery is one of the most important aspects of a successful IT environment. It ensures that the production applications are accessible in case of an outage or a disaster. Without a disaster recovery solution, your applications could experience high downtime and lose important data.

Kubernetes has a built-in disaster recovery mechanism provides a highly available and redundant environment for your production applications. Kubernetes clusters can be replicated to other locations on the same network, another region, or even the cloud. When you replicate a cluster, you will create a DR cluster that contains an up-to-date copy of the data and metadata from the primary cluster.

However, implementing a disaster recovery plan is complex and requires many resources to be effective. The DR process depends on automated backups, the implementation of infrastructure at the DR site, and procedures that are well-documented and tested regularly. In addition, maintaining bandwidth and an architecture capable of supporting data copies increases costs.

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