Kubernetes deployments present numerous benefits for enterprises looking to upgrade their infrastructure and transition to a cloud-native architecture. However, the very features that make Kubernetes appealing to developers and CIOs can also introduce challenges regarding backup and disaster recovery (DR).
While traditional monolithic applications and virtual machines (VMs) are relatively straightforward to back up and integrate into a disaster recovery plan—provided it’s executed meticulously—the dynamics of Kubernetes and containers are fundamentally different. Disaster recovery strategies must adapt accordingly.
### Why is Disaster Recovery Important for Kubernetes?
As the adoption of containers and Kubernetes in production environments grows, these systems increasingly handle critical data and essential business processes. Organizations must safeguard the data and diverse microservices that constitute a Kubernetes-based application, ensuring they can recover them both accurately and promptly.
IT teams must ensure that all vital components of a Kubernetes deployment are incorporated into the disaster recovery plan. This entails more than just securing persistent storage with standard and immutable backups; organizations need to protect the entire cluster, its components, and associated data to enable seamless restoration. Rigorous testing of these recovery strategies is also essential.
### Challenges of Kubernetes Disaster Recovery
Implementing disaster recovery for Kubernetes clusters involves identifying and safeguarding cluster components and configurations. Additionally, data volumes present a unique challenge. With Kubernetes increasingly utilizing persistent storage, the task can be somewhat simplified. However, DR teams must be aware of where Kubernetes applications store data, which may span local, cloud, and hybrid storage environments.
According to Gartner analyst Tony Iams, container applications possess attributes conducive to disaster recovery and business continuity, despite the complexities involved. He notes, “The inherent portability and immutability of containers simplify the consistent replication of a complete application stack across various locations. Utilizing continuous integration/continuous deployment (CI/CD) processes, containerized applications can be quickly rebuilt and delivered wherever necessary, whether at a secondary site or to restore a primary site following a failure.”
### Risks in Kubernetes Environments That DR Needs to Address
Kubernetes faces risks similar to any enterprise technology setup, including hardware failures, software issues—particularly within the underlying Linux OS—power outages, network failures, physical catastrophes, and cyber threats like ransomware.
However, the inherent flexibility and distributed nature of containers may expose applications to single points of failure, and distributed architectures can amplify the effects of hardware outages. For instance, organizations can easily replicate an entire virtual machine or create an immutable snapshot, capturing everything needed for application continuity. In contrast, Kubernetes applications involve more intricate dependencies.
Iams emphasizes that the way containerized applications manage storage poses a particular risk. Unlike traditional applications that rely on the host OS’s file system, “containers persist data using volumes that write data to storage outside the container’s local file system.” Therefore, when working within Kubernetes clusters, IT teams must ensure that manifests and policy configurations are backed up, and that containers can reattach to their storage post-restore.
### Essential Elements of a DR Plan for Kubernetes
Effective disaster recovery planning for Kubernetes environments typically requires a more granular approach than that for traditional applications. Organizations can minimize downtime and data loss by recovering specific Kubernetes components instead of entire clusters. Each element of a Kubernetes setup can have its own recovery point and recovery time objectives (RPO/RTO).
This necessitates that IT teams maintain a comprehensive and current understanding of their Kubernetes components and the business processes they support. Similar to conventional DR plans, prioritizing the services requiring expedited restoration is crucial. Questions to consider include:
1. Which Kubernetes-based applications are critical to business operations and should be restored first?
2. Which Kubernetes services and dependencies can facilitate the quickest recovery of those containers?
When executed well, this strategy can enable organizations to bring applications back online, potentially with reduced functionality, faster than if they relied on complete cluster restoration. The specific approach will likely vary based on the organization’s maturity and risk tolerance.
“Currently, cloud-native and traditional infrastructure engineers have differing perspectives on the best approach to this challenge,” points out Iams. “Cloud-native engineers emphasize redeployment methods via CI/CD workflows, whereas traditional strategies rely on backup and recovery tools for Kubernetes applications and data protection.” The analyst firm suggests utilizing an application-centric approach when the organization is equipped for it.
### Infrastructure Requirements for Kubernetes DR
Kubernetes’ versatility can facilitate application recovery, whether from on-premises hardware, the cloud, or even between different cloud providers. DR specialists must verify that the necessary resources are in place, including compute capacity for running Kubernetes clusters and adequate storage for recovering persistent volumes. Appropriate network resources are also crucial.
For application recovery, if IT teams have employed an application-centric GitOps approach, they can utilize tools like ArgoCD or Flux CD. Alternatively, using specialized vendor solutions for Kubernetes, such as Kasten, Trilio, CloudCasa, or Cohesity (which has acquired Veritas’ data protection assets), is advised. Companies like Commvault and Rubrik also extend support for containers and cloud-native applications.
These “Kubernetes-aware” tools integrate with clusters, comprehending how these clusters constitute an application and how to restore them in the event of an outage.