Kubernetes Storage: Understanding the Pros and Cons of Stateful Applications

Managing stateful applications with Kubernetes (K8s) is challenging given their data persistence needs, which might scale up as the architecture gets more distributed and complex. However, over time, Kubernetes has also grown as a reliable tool for this task. Not only does K8s offer these applications automation for orchestration, scaling, and deployment, it also brings benefits for security and, more importantly, storage. Kubernetes storage, one of the fundamental components of K8s, is more than equipped to manage stateful data storage and retrieval applications. 

By offering means to store data beyond the lifecycle of its pods, Kubernetes helps stateful applications achieve the long-term storage essential for their functioning. In addition to durability, Kubernetes storage has features for abstracting and handling storage resources, making it easier to deploy these applications into containerized environments. So, let’s look at how K8s achieve this and how its different storage vary in their offerings.

How Kubernetes manages stateful applications

Stateful applications, like MySQL, Redis, and more, need resources to persist data irrespective of whether they are being actively used. This is a challenge for Kubernetes, which is, first and foremost, meant for containerized environments. Orchestrating containers would require K8s to reschedule or even destroy its pods regularly. This means it would need to take care of all the data collected by the stateful applications engaged with that pod. Fortunately, Kubernetes storage has just the right resources to make this happen. Here’s how K8s handles stateful applications: 

• Storage Abstraction: To truly leverage the portability of containerized environments, stateful applications must be decoupled from storage infrastructure. Kubernetes storage offers this decoupling by bringing an abstraction layer between storage resources and applications. As we will discuss later in this blog, these abstractions enable K8s to be free stateful apps that do not have to care about any storage devices or file systems while they scale with the containerized pods.
• Storage Types: Many storage types or solutions within Kubernetes help stateful apps ensure persistent storage, fault tolerance, and support for scalable operations. These solutions offer features like unique network identities, automatic storage provisioning, and integration with cloud storage resources.

Kubernetes storage types

Let’s look at how these storage types hold the required set of features and attributes that would help stateful applications run smoothly with containerized environments managed by Kubernetes.

Persistent volume and persistent volume claim

These manifest the storage abstraction feature of Kubernetes. Persistent Volumes (PV) are essentially APIs that can help provision storage for stateful application clusters. Persistent Volume Claim (PVC) are their user counterparts, through which users request specific storage requirements. Storage provision, therefore, can be done statically by resource admins or as and when required. The apps are, therefore, independent of the underlying physical storage.

Pros:

• Abstraction allows dynamic and flexible storage provisioning for storage resources.
• PVs make the apps more portable by decoupling them from physical storage. This is an essential benefit while working with containerized environments.
• PVs can support many storage classes like NFS, iSCSI, cloud storage, and more.

Cons

• Cluster management is complex and requires specific Kubernetes knowledge.
• Automation capabilities for scaling are only limited to dynamic provisioning.
• Scalability is difficult and practically requires new PV for every size change.

Block storage

Block storage is the ideal candidate for apps that need to fetch and persist large chunks of data, like relational databases. It offers high-performance storage features by breaking the app data into blocks that are easy to read and write.

Pros

• Faster in retrieving or writing the data into storage.
• Best choice for database tools as they require frequent read/write.
• Highly available and fault tolerant to ensure minimal to zero outages.

Cons

• Don’t do well with unstructured data and, therefore, are a bad choice for big data tools.
• Limited to a single Kubernetes pod and therefore can’t be shared
• Being limited to a single pod makes them highly dependent on manual intervention for data migration and other such requirements.

Object storage

Object storage offers scalable storage provisioning for unstructured data. The data here is broken into objects that are quantified units that can store various attributes of the data. This makes object storage a trusted resource for data backups, media files, log files, and more.

Pros

• They are known for their scalability, which makes them ideal for large, unstructured data volumes.
• It also proves to be more cost-effective than block storage, thanks to its ability to store large amounts of data.
• Excellent support for HTTP/HTTPS protocols, which makes it highly accessible.

Cons

• Storing large amounts of unstructured data increases their latency, making them less ideal for transaction processing.
• Object storage lacks built-in file locking, which might raise challenges for data integrity.
• Slow data retrieval makes it a bad choice for storage, as it needs to be accessed frequently.

Network file system (NFS)

NFS comes in two versions. The persistent volume variant works specifically for stateful applications. Once it is mounted, it practically works like a local drive, meeting your storage needs. Unlike block storage, NFS also offers sharing capabilities. 

Pros

• Sharing capabilities to enable working with multiple pods for collaborative apps.
• NFS offers more flexible and portable storage that can migrate between environments.
• NFS can be mounted like a local drive, and it uses very familiar file system semantics that make it easy to use.

Cons

• Being a sharable storage resource, NFS suffers from higher latency, making it a bad choice for performance-sensitive applications.
• Unlike object storage, NFS is difficult to scale due to network limitations.
• Even if it is a shareable resource, NFS offers centralized storage, making it a single point of failure.

Cloud provider volumes

These work best with cloud storage types and are best candidates to work with cloud-native storage tools like AWS EBS, Google Persistent, and more.

Pros

• Ideal option for cloud-native storage
• Highly portable within the specific cloud vendor, it is meant for
• Offer features like automated replication, data snapshots, and more for easy disaster recovery

Cons

• Limited to a specific vendor due to vendor lock-in, cloud provider volumes are not ideal for multi-cloud environments.
• With cloud-native features, cloud provider volumes can get costly very quickly.
• Vendor lock-in makes it less scalable, limiting it to a particular region or zone.

Storageclass

StorageClass helps the user or admin select from the available storage classes based on their requirements for QoS levels, backup policy, and more. The typical attributes for StorageClass include the ID for the provisioner and different parameters with context to storage.

Pros:

• Supporting multiple storage classes like SSD or HDD, StorageClass can help balance storage features with cost benefits.
• StorageClass is highly automation-friendly, which makes it an excellent resource for dynamic provisioning.
• StorageClass also takes policy attributes into account, which makes compliance management easy.

Cons

• Although it allows dynamic provisioning, StorageClass requires careful planning and a good knowledge of storage management.
• Configuring StorageClasses also requires technical skill and may be error-prone if not done right.
• StorageClass can work in multi-cloud environments, but its behavior changes for different cloud vendors.

Conclusion

Kubernetes is one of the most powerful tools enabling modern digital innovations. Its capabilities to handle stateful applications through its storage offerings expand the scope of digital solutions that can engage with it. The tool can help with storage abstraction, making the stateful apps independent of the underlying storage hardware and its properties. With support for various storage types, K8s can help stateful apps bring their potential to distributed environments and serve nuanced business cases across industries.