What is Kubernetes?
Kubernetes, often abbreviated as K8s, is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications. As businesses increasingly adopt cloud computing, Docker containers, and microservices architectures, Kubernetes has become a leading solution for running applications reliably across servers and cloud environments. It helps IT teams improve application availability, simplify infrastructure management, automate updates and recovery, and efficiently scale workloads as demand changes.
Kubernetes has changed the way organizations deploy, scale, and manage containerized applications. By automating scheduling, failover, load balancing, and application deployment, Kubernetes allows developers to run workloads consistently across on-premises infrastructure, private clouds, and public cloud environments.
Understanding Persistent Volumes, Persistent Volume Claims, SAN storage, NAS storage, and cloud storage helps organizations build resilient Kubernetes environments without sacrificing performance or data availability. Nfina provides server, storage, hybrid cloud, and high-availability infrastructure that can support containerized and virtualized workloads across modern data centers.
Ephemeral vs. Persistent Container Storage
Ephemeral storage exists only for the life of a pod or container. It works well for caches, temporary files, processing space, logs that are exported elsewhere, and stateless applications. If the pod is deleted or moved to another node, the data stored locally may disappear.
Persistent storage is designed to survive those lifecycle events. The application can be restarted, recreated, or rescheduled while its underlying data remains available.
This separation is important because Kubernetes treats compute and storage independently. A pod may move from one node to another after a hardware failure or during maintenance. If application data exists only on the original node, the newly created pod may start without the information it needs.
For databases, customer records, application state, shared content, and other critical information, persistent storage should therefore be part of the Kubernetes architecture from the beginning.
Persistent Volumes and Persistent Volume Claims
Persistent Volumes, or PVs, provide Kubernetes with an abstraction layer between applications and physical storage.
A Persistent Volume represents storage available to the cluster. The actual capacity might come from a SAN, NAS system, cloud disk, local SSD, or another storage platform.
A Persistent Volume Claim, or PVC, is an application request for storage. Developers specify requirements such as capacity, access mode, and sometimes performance characteristics. Kubernetes then matches that request with an appropriate Persistent Volume.
This allows developers to request storage without needing to know exactly which physical array, disk, or network path provides for it.
Storage Classes add another level of automation by allowing Kubernetes to dynamically provision storage. Instead of an administrator manually creating every volume, a PVC can trigger creation of a new storage resource based on predefined policies.
A well-designed Kubernetes storage architecture separates application requirements from the underlying infrastructure while still giving administrators control over performance, availability, protection, and capacity.
Block vs. File Storage for Kubernetes
Block and file storage can both support Kubernetes’ persistent workloads, but they serve different application requirements.
Block storage presents raw volumes to a server or container environment. Applications or operating systems create their own filesystem on those volumes. Block storage is commonly used for databases, transactional applications, virtual machines, and other workloads where predictable latency and high IOPS are important.
File storage organizes data into shared folders and files. Multiple applications or users can access the same filesystem through protocols such as NFS or SMB. This makes file storage useful for shared application content, web assets, user files, analytics datasets, and workloads that require several pods to access the same information.
The choice should be driven by the application. A database may perform best with dedicated block storage, while a distributed web application may benefit from a shared file system.
Nfina’s educational overview of storage architecture explains how Nfina-Store supports both block- and file-level storage using a pooled ZFS-based architecture. That flexibility allows a storage platform to support multiple workload types without requiring completely separate systems.
SAN Storage for Kubernetes
A Storage Area Network, or SAN, provides block-level storage over a dedicated or high-speed network. SAN storage is commonly used for performance-sensitive enterprise applications because it can deliver centralized storage with predictable latency and high availability.
For Kubernetes, SAN storage is well suited to stateful workloads such as databases and transactional applications. Persistent Volumes can be created from SAN storage and attached to pods through supported storage drivers.
Centralized SAN infrastructure also separates storage from individual Kubernetes nodes. If one server fails, another node can potentially access the same underlying storage, depending on the application and storage configuration.
SAN architecture should still be sized carefully. Kubernetes environments can generate large numbers of simultaneous storage requests, and performance must be planned around aggregate IOPS, throughput, latency, and network bandwidth rather than the requirements of a single container.
Nfina’s guide to SAN storage provides additional information about block storage, centralized storage networks, performance, scalability, and high-availability architectures.
NAS Storage for Kubernetes
NAS can be particularly useful when multiple Kubernetes pods need simultaneous access to the same files. Applications such as web services, media platforms, content management systems, development environments, and shared data-processing workloads may benefit from this architecture.
NFS is commonly used with Linux-based container environments because it allows multiple systems to mount the same shared filesystem.
NAS also simplifies centralized management because capacity, permissions, snapshots, and protection can be administered from the storage platform instead of independently on every Kubernetes node.
Nfina NAS systems support protocols including NFS and SMB along with storage protection technologies such as snapshots, RAID, encryption, data check summing, and high-availability clustering.
SAN vs. NAS for Container Workloads
SAN storage is generally appropriate when applications need dedicated block devices, predictable latency, and high transaction performance. Databases and other I/O-intensive stateful workloads frequently fall into this category.
NAS storage is usually better when multiple containers must share the same filesystem. It simplifies file sharing and can eliminate the need to maintain duplicate copies across different nodes.
Many Kubernetes environments use both. A database tier may run on SAN-backed Persistent Volumes while application servers share configuration files or media through NAS.
Nfina’s Unified Storage solutions provide both block and file storage options, including SAN, NAS, all-flash, hybrid, and expansion platforms. This allows organizations to match storage architecture to individual Kubernetes workloads instead of forcing every application onto the same storage type.
Cloud Storage for Kubernetes
Cloud block storage behaves similarly to a traditional SAN volume and is commonly used with cloud-hosted databases and stateful applications. Cloud file services provide shared filesystems, while object storage is well suited to large amounts of unstructured information such as images, logs, backups, and analytics datasets.
The primary advantages of cloud storage include scalability and rapid provisioning. Kubernetes can dynamically request new capacity without waiting for physical hardware.
However, cloud storage introduces other considerations. Persistent storage charges, snapshots, data transfers, performance tiers, geographic replication, and egress fees can make long-term costs difficult to predict.
Hybrid architectures can provide a useful balance. Performance-sensitive or regulated workloads can remain on-premises while cloud resources provide additional capacity, backup, disaster recovery, or temporary compute resources.
Stateful Applications and Databases
Stateful applications maintain information between sessions, making persistent storage essential.
Databases such as PostgreSQL, MySQL, MongoDB, and other relational or NoSQL platforms are common examples. Their data must remain intact even if a Kubernetes pod is restarted or moved to another node.
Kubernetes StatefulSets provide additional controls for these workloads by maintaining stable identities and storage relationships across pod restarts.
Storage performance becomes particularly important for databases because storage latency can directly influence query response times and transaction performance.
Capacity planning should include database growth, logs, temporary files, replicas, snapshots, and backups rather than only the current database size.
Organizations should also consider high availability at both the application and storage layers. Multiple Kubernetes nodes provide limited protection if they all depend on a storage system with a single point of failure.
Storage Performance and Scalability
Kubernetes can create highly dynamic storage workloads. Containers may scale rapidly, multiple pods may access storage at the same time, and automated deployments can create sudden increases in I/O demand.
Administrators should monitor IOPS, throughput, latency, queue depth, network utilization, and storage capacity alongside CPU and memory utilization.
Storage should also scale independently when possible. An organization may need additional storage capacity without needing more Kubernetes compute nodes, or it may require additional compute without increasing stored data.
Nfina shared storage architectures allow centralized capacity to be expanded separately from compute resources, helping organizations avoid purchasing unnecessary server resources simply to obtain more storage.
Backup and Disaster Recovery for Kubernetes
Persistent storage solves the problem of keeping data after a pod disappears, but persistence is not the same as backup.
If ransomware encrypts a Persistent Volume or a user accidentally deletes important application data, Kubernetes may faithfully preserve the corrupted or deleted state.
A proper Kubernetes backup strategy should protect persistent data along with application configuration, cluster resources, databases, and supporting infrastructure.
Snapshots can provide frequent recovery points, while geographically separate backups protect against storage or site failures. Immutable copies add protection against ransomware by preventing selected recovery points from being changed during their retention period.
Recovery procedures should also be tested. Restoring a storage volume does not guarantee that the application will operate correctly. Administrators should verify databases, application dependencies, permissions, network services, and Kubernetes configuration.
Nfina’s storage platforms support snapshots, clones, rollback, and on-site or off-site data protection. Its broader backup and disaster recovery infrastructure can also provide geographically redundant recovery options for critical business workloads.
Choosing Kubernetes Storage
There is no single best Kubernetes storage technology for every workload.
Ephemeral storage is appropriate for temporary information. Persistent Volumes provide durable storage for stateful applications. SAN systems can support high-performance block workloads, while NAS provides convenient shared file access. Cloud storage adds flexibility and geographic reach.
The strongest architecture may combine several of these options.
Application teams should define required capacity, access modes, latency, IOPS, throughput, availability, backup frequency, Recovery Point Objective, and Recovery Time Objective before selecting the underlying storage platform.
Nfina designs server and storage infrastructure around virtualization, containerization, private cloud, hybrid cloud, backup, and high-availability requirements. Organizations evaluating persistent storage for Kubernetes can schedule a conversation with Nfina to discuss SAN, NAS, shared storage, and hybrid cloud architecture for their environment.