Kubernetes is becoming increasingly popular among developers looking to deploy stateful apps. K8s users have to confront the issue of what to do with their data. This blog will go through three critical criteria for any deployment: resilience, availability, and data security, and how it all relates to your application state.

 

Why is data protection for Kubernetes so Important? 

 

The adoption of stateful apps on Kubernetes is rapidly increasing, with 78% of organizations already deploying stateful apps on K8s or plan to do so soon, according to the latest 2020 CNCF survey. This trend will continue to accelerate.

Kubernetes makes it simple to deploy stateless apps since they don’t require any storage external to the container runtime or Kubernetes cluster. On the other hand, stateful applications have more complicated data storage demands that are frequently a source of headaches for DevOps teams.

Organizations frequently struggle with Kubernetes when it comes to security, resilience, availability, and data protection for stateful apps in particular. Maintaining resiliency with persistent storage is one of the most significant challenges of utilizing Kubernetes with stateful apps.

Legacy infrastructures were not built with K8s stateful applications in mind, and neither were public clouds. Storage solutions lag behind the rest of cloud infrastructure, and conventional storage technologies are complicated to set up for Kubernetes.

At the same time, more and more businesses are starting to use K8s for stateful apps. The gap between the application and its state widens.

Until we find a solution for extending K8s advantages such as application mobility and seamless high availability to the state, these organizations remain exposed to risks of downtime, data loss, and vendor lock-in.

 

Data protection beyond the container lifespan

 

As organizations deploy more containers, they will produce exponentially more data. Containers are often used for testing and development, so the life of the containers themselves is frequently shorter than the data they produce. That data, however, must be kept and maintained for an extended period after a container is decommissioned or destroyed.

The primary use for stateful applications is, of course, databases, which usually contain the most valuable business data. And so, reconciling these values – the ephemeral nature of containers and the persistence of the data poses a problem, only partly solved by the built-in Kubernetes persistent volume mechanism (i.e., what happens if the data volumes need to be imported on a different cluster, etc.)

 

How can you maximize data protection around K8s?

 

It’s critical to be able to protect and recover an applications’ state without adding more steps, tools, or policies to the already complex DevOps processes.

In order to enhance data protection on Kubernetes, stakeholders must consider a number of variables. The following are five of the most important:

Balance availability and resilience with development speed

One key component in mitigating the risk is allowing users to ‘rewind’ to a previous checkpoint, ensuring a low recovery point objective (RPO). This is not only the least disruptive, but it also provides more versatility and availability than traditional backup since snapshots can be many hours behind live systems, leaving gaps in data protection.

By utilizing native data protection solutions that support K8s, data security and recovery procedures are included directly in the application creation process from the start. Containerized applications’ resiliency can be assured without causing any lagging or slowing down in performance, scale, or agility.

Protect your pipeline

It’s also a good idea to safeguard the technology that creates container images and their configuration, commonly known as the CI/CD pipeline. Configuration scripts (such as Dockerfiles and Kubernetes YAML files), as well as any supporting documentation.

However, an issue that frequently arises is that data protection requirements for systems like build servers and code and artifact repositories that store containers and application releases are neglected. By ensuring that these workloads are kept safe throughout the Continuous Integration and Continuous Delivery process, you ensure that the bulk of the pipeline that generates container images is as well.

Protect persistent application data

Even though container images are transitory, and any file system changes are lost when the running container is deleted, users now have several alternatives for incorporating stateful, persistent storage to containers.

However, solutions like snapshots lack in their ability to provide you with sufficient protection since they always result in data loss of the last hours or days of operation. Plus, they’re usually not available in case an availability zone or entire cloud region goes down.

Try to find a data replication solution that will enable you to bring up your application in a different location and avoid downtime and data loss.

Capture the entire application state, not just persistent data

The main drawback of conventional Kubernetes data protection is that it only protects the persistent data stored in persistent volumes. The problem with adopting such a strategy in Kubernetes is that it generates configuration drift.

For example, suppose you take snapshots of a database application’s persistent volumes on a regular basis. In case there are any modifications, such as new passwords and configurations, ConfigMaps and secrets must be updated as well to preserve the entire application state.

In addition, it might be difficult to recreate your environment on a different cluster just with persistent data.

Look for a solution that captures the whole application state, including pods, secrets, services, deployments, certificates, and ConfigMaps. This will guarantee that no configuration drift occurs during application restorations or rollbacks.

Keep in mind that the data protection solution should protect all components, not just the volumes.

Avoid vendor and region lock-in

Avoiding vendor lock-in is another crucial underlying component in creating a data protection strategy around Kubernetes. A solid data protection policy should allow each organization to move data where the application demands it without relying on any single storage platform or cloud vendor.

When your cloud region is showing signs of malfunction, the best thing is to move your applications elsewhere. If only your data protection solution would allow it (which it usually doesn’t.)

 

Protect your K8s clusters with Statehub

 

When building an effective data protection strategy – and choosing a platform to support it – you must consider the above-mentioned capabilities first.

Every outage or data loss can have a massive impact on your company. However, with native data protection technologies that encourage ‘data protection as code,’ data protection and disaster recovery procedures are integrated from the beginning into the app development lifecycle.

The principles of resilience, availability, and data protection for Kubernetes deployments are extended to your state, empowering you to avoid vendor lock-in while capturing the entire application state, not just persistent data.

When you’re trying to balance flexibility and availability against the need to guarantee fast deployment across corporate apps and services, it’s tough to do without a native data platform built specifically for container platforms like Kubernetes. Statehub is a fully managed service that captures your entire application state so that you can:

  • Have multiple copies of your applications’ data, creating redundancy at any level
  • Share and clone data between any k8s clusters on the public cloud, no matter where they are
  • Neutralize data gravity by establishing a seamless app and data mobility, unconstrained by distance or cloud provider

 

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