Kubernetes has become the de-facto container orchestration tool and continues to dominate the container orchestration landscape. Kubernetes storage is a complex but essential part of any stateful application and ensures data persistence across clusters. Understanding the best practices of Kubernetes storage can positively affect your deployment strategies.
This article is a companion to our Kubernetes persistent volume tutorial. In this article, we’ll look at techniques and best practices for optimizing Kubernetes storage. We’ll explore everything you need to build a robust, scalable solution, from data security and backup strategies to picking suitable storage classes.
Recap of Challenges and Benefits of Kubernetes (K8s) Storage
Kubernetes is extremely powerful in orchestrating and managing thousands of containerized applications. However, there are complexities involved in Kubernetes storage.
- Configuring StorageClasses and PersistentVolumeClaims can be complex when dealing with multiple storage backends while ensuring compatibility with the on-prem storage.
- Managing StatefulSets and handling storage class migration without data loss in distributed setups is challenging.
- Choosing the correct type of storage abstraction (PV, PVC, StorageClass) is critical, and implementing and maintaining CSI drivers for various storage systems is difficult.
- Providing and managing fine-grained access controls and setting resource quotas, especially in a multi-setup, requires careful planning.
- Backing up your data is critical, and implementing robust backup solutions, including snapshots and incremental backups, especially with distributed storage, isn’t straightforward.
We’ve also listed the Top 10 Tips for Running Databases on Kubernetes to help you understand how to run databases on Kubernetes.
Why It’s Important to Know the Best Practices for Kubernetes Storage
As organizations rely on containerized applications, managing Kubernetes storage effectively is critical. Learning about the best practices for Kubernetes storage will help you navigate the complex landscape of Kubernetes storage.
- Implementing best practices helps you implement proven storage solutions and processes that can withstand increased load and scale effectively.
- Following industry best practices also helps you optimize costs by choosing and implementing industry-leading storage management solutions and practices.
By understanding and implementing industry best practices, you can solve your current challenges and future-proof your storage solution. Let us explore Kubernetes storage best practices.
6 Best Practices for Kubernetes Storage
Implementing Kubernetes Dynamic Volume Storage
What is Dynamic Volume Provisioning?
Dynamic provisioning automates Kubernetes’ creation of storage volumes on demand without any manual intervention, thus saving time and effort and making the process less error-prone. To leverage its full potential, you must follow the best practices that ensure optimum performance.
Recommendations for Dynamic Volume Provisioning
To leverage dynamic volume provisioning to its full extent, it’s important to follow best practices that are tailored for dynamic environments. Here we share tips for setting up and configuring dynamic provisioning along with resource optimization tips.
- Use Persistent Volume Claims (PVC) to provision dynamic volumes. This abstracts the underlying storage details and simplifies storage management.
- Include PVC in container configuration, however, never include Persistent volumes(PV) as it will tightly couple the container to a node.
- Define an appropriate reclaim policy depending on your available resources to minimize storage costs once the pods are deleted.
- Leverage storage class parameters to tailor the behavior of your dynamic volumes. This includes setting replication factors, encryption, and provisioning policies.
- Always have a default StorageClass, as PVCs that don’t specify any StorageClass will fail.</li>
Important Benchmarks and Metrics for Dynamic Volume Provisioning
Implementing dynamic volume provisioning for Kubernetes requires validating support and compatibility with various storage backends, Kubernetes storage classes, and automation APIs. In addition, monitoring key metrics such as provisioning speed, IOPS, latency, throughput, and resource utilization is crucial.
How to Optimize Kubernetes Storage for Scalability
Why is Scalability Important for Kubernetes Storage?
Your workload’s growing demands will require scaling your resources. At the same time, your storage must also be scalable. This means that your storage solution must also be able to grow in capacity and performance to meet growing demands. So when your application scales by adding more pods and nodes to handle the increasing traffic, the storage must also dynamically add additional volumes and distribute the storage load effectively.
Configuring Kubernetes Storage for Scalability
With effective scalability rules, your application will be responsive and active during peak load times. Let’s look at some best practices, tips, and tricks for optimizing Kubernetes storage for scalability.
- Use dynamic volume provisioning to automatically provision storage volumes as needed to reduce manual intervention and enable seamless scalability.
- If you already have a Horizontal Pod Autoscalar (HPA) configured, tweak/combine it with your storage strategy to ensure your application can handle varying loads.
- Deploy your storage workloads on different nodes for better resource utilization and prevent bottlenecks and single points of failure.
- Monitor and tweak resource quotas and limits to ensure that storage is distributed evenly across your workloads.
Important Benchmarks and Metrics for Scalability
Optimizing Kubernetes storage for scalability means constantly monitoring various metrics, including storage capacity utilization, throughput at peak loads, and the performance impact of adding new nodes and volumes. Reviewing these metrics periodically will help maintain your solution’s performance and reliability.
How to Optimize Kubernetes Storage for Fast Performance
Customers today want their applications to be fast and responsive. Since most applications have storage backing them, ensuring your storage is optimized for performance is crucial. This will ensure that your application runs smoothly and efficiently.
Performance Tuning Techniques
Here are a few tips and best practices for optimizing your storage for faster performance.
- Choose storage classes like SSD-based solutions as they offer faster performance, such as higher IOPS and low latency, and are suitable for applications that require rapid data access.
- For high-performance workloads, choose local persistent volumes over network-attached storage. These don’t incur network overhead and thus provide better performance.
- Implement caching strategies like in-memory or storage-level caches to speed up data retrieval and reduce overloading your primary storage.
- For extremely high-performance workloads like AI workloads, use NVME disks over regular SSDs, with better throughput at low latencies. All Pure Storage solutions leverage NVMe storage to unlock the full potential of flash memory.
- If you have performance-critical workloads, it’s suggested that you have dedicated storage for them to avoid contention with other applications and provide reliable performance.
Important Benchmarks and Metrics for Fast Performance
When you optimize your storage for better performance, you also need to track important metrics like IOPS, read and write latencies, and throughput. Further, depending on the underlying storage types, you’d need to have some additional configuration to check your system’s responsiveness at peak loads.
Security Best Practices
Implementing security best practices is necessary to prevent unauthorized access and security breaches, whether for your application or data. Hundreds of businesses are affected by vulnerabilities in their applications; most of the time, it’s a data breach. Let us look at some of the best practices for protecting Kubernetes data.
- Implement data encryption at rest and in transit. Ensure all the storage volumes are encrypted, you use Kubernetes secrets to store sensitive information, and you use secured protocols to transfer data.
- Enable fine-grained access control using Role-Based Access Control (RBAC), Zero Trust, and other control mechanisms to limit access to your storage volumes and minimize unauthorized access.
- Define and configure network policies to control traffic between your application and storage workloads. This will help you limit access to your storage volumes and other workloads and prevent unauthorized access.
- Implement a mechanism to rotate your encryption keys and secrets periodically. This will reduce the risk of unauthorized access due to compromised credentials.
- Enable monitoring, logging, and alerting mechanisms to track various events, such as access and modification requests. This will help you create an audit trail while ensuring compliance with multiple regulations.
When you implement these best practices, you must regularly track the effectiveness of your access control mechanisms, encryption, and compliance with policies and regulations to fortify your Kubernetes storage solution against threats.
Backup and Disaster Recovery
Organizations focus on scalability and flexibility and protect their applications from failure or downtime. This is where backup and Kubernetes disaster recovery strategies come into play. Here are some best practices, tips, and tricks for creating an effective Kubernetes backup strategy for your solution.
- Implement automated, regular backups for all your critical data. In addition, implement incremental backups that will reduce the overhead and improve the efficiency of your backup process.
- Ensure your backups are stored in different nodes, preferably in various locations, to safeguard against region-based disasters.
- Perform regular checksum tests on your backups to ensure they are correct and valid.
- Implement backup retention policies to keep the backups for a specific duration, depending on your business and regulatory requirements.
- Continuously monitor your backup operations to ensure they do not fail. Test your backup and disaster recovery processes periodically to ensure they are current.
Regular snapshots and backups protect against data loss, while storing them in different geographical locations protects against regional failures.
Testing Restore Procedures
Testing restore procedures ensures you can quickly and reliably recover data when needed. By following these practices, you can maintain data integrity and ensure business continuity during unexpected disruptions.
- Ensure that backups are complete and not corrupt by validating the checksum. Also verify that all the data needed for a successful restore is present.
- Periodically perform restore operations to ensure that the entire application state can be recovered based on the RPO.
- Simulate disaster recovery scenarios by inducing cluster/node failures and execute the restore procedures to test the effectiveness and speed of recovery.
- Automate restore testing using tools to test and verify restore procedures.
Data Storage and Management
None of your scalability or performance optimization tips will be effective if you don’t properly store and manage your data. This also affects the ability of your application to handle growing data requirements. Here are some best practices to manage your data well.
- Organize your data into different storage classes depending on its importance, access frequency, and criticality. To improve the maintainability of your data, you can also create and maintain different namespaces.
- Define and enforce data retention policies to manage your data. Implement jobs and automation to delete unnecessary and outdated data to free up space periodically.
- Implement dynamic storage provisioning to automate allocating storage resources, reducing human interference and streamlining the process.
- Implement techniques like checksums and data validation to regularly check your data’s integrity and consistency and prevent any data loss due to corruption.
- Lastly, periodically review your data storage and management processes to ensure they align with your evolving business requirements.
Handling Storage Failures and Alerts
Effective storage and management require monitoring various metrics and proactively handling any storage failures and alerts. Continuous monitoring can preempt issues and avoid failures, thus helping with seamless operations. Below are some tips to handle storage failures and alerts.
- Implement monitoring tools to track the health of your storage and performance metrics and alerts are configured for all critical issues like low storage and high latency.
- Create alert thresholds for triggering alerts based on metrics like storage capacity, IOPS, etc.according to your application and storage requirements.
- Create incident plans and set up automated mechanisms to respond to common alerts related to auto-scaling or triggering failover processes.
- Periodically test your incident response plans for different failure scenarios and ensure your tests evolve as your storage environment evolves.
Optimize Your Kubernetes Storage with Portworx
The best practices discussed throughout this blog post provide a comprehensive approach to managing storage on Kubernetes. However, implementing all of these best practices is not straightforward. This is where Portworx can help.
As a leading provider of storage solutions, Portworx simplifies the implementation of these best practices to make your Kubernetes storage robust, secure, and scalable. It further abstracts the complexity of detailing directly with Kubernetes storage and provides options to deploy it to your cluster or Portworx’s platform.
Portworx offers solutions to help you manage and optimize your Kubernetes storage:
- Portworx Enterprise provides storage and data management services for containers in the cloud, on-premises, or in hybrid environments. It acts as a software-defined layer that abstracts data storage and aggregates them into a virtual pool. It also helps with uptime, automated capacity management, resource optimization and redundancy.
- Portworx Enterprise also allows for encrypting Kubernetes data, and includes features like RBAC to allow better control over data access.
- Autopilot capabilities within Portworx Enterprise helps optimize your Kubernetes storage for scalability through rule-based optimization and management. It also reduces costs by provisioning storage only when needed.
- Portworx Backup provides backup and restore services for your stateless and stateful data solutions.
These services are part of the Portworx Platform, a multi-cloud-ready platform for running mission-critical applications in production using a fully integrated solution for managing and optimizing storage, data recovery, security, and automated capacity management.