Storage Pooling

Storage pooling is a technique used in distributed data storage systems to aggregate multiple storage devices into a single, unified storage resource. This approach enhances resource utilization, improves scalability, and simplifies management by abstracting physical storage infrastructure into a logical storage pool.

Traditional storage architectures often rely on dedicated storage devices assigned to specific applications or workloads, leading to inefficiencies in resource allocation and potential underutilization. Storage pooling addresses these challenges by combining storage resources from multiple nodes into a shared pool, allowing dynamic allocation based on demand.

Key characteristics of storage pooling include:

  • Resource Aggregation: Multiple physical storage devices, such as HDDs, SSDs, or NVMe drives, are combined into a single logical storage entity.
  • Dynamic Allocation: Storage capacity can be allocated dynamically to workloads based on usage patterns and demand.
  • Improved Efficiency: By eliminating the constraints of static storage assignments, storage pooling optimizes resource utilization and reduces wasted capacity.
  • Scalability: Additional storage devices or nodes can seamlessly integrate into the storage pool without disrupting operations.
  • Simplified Management: Centralized control and monitoring enable streamlined administration of storage resources.
  • Security Options: Storage pools can define NVMe-oF security settings (DH-HMAC-CHAP authentication and TLS/PSK encryption) that are automatically applied to all volumes created within the pool. See NVMe-oF Security for details.

Important

Due to dual-layer virtualization (front storage is virtualized separately from back storage), simplyblock is able to achieve true consolidation of entire cluster resources into a single storage pool.

This means that there is no physical limit on how to carve logical volumes from that pool. For example, if a total pool is 2 PB in size, a single volume can be sized 2 PB or 10,000 small volumes can be created. Also it means that capacity and total performance of a pool scales linearly when the pool is expanded.

As this characteristic is conflicting with the benefits of data locality, simplyblock still applies the principles of data locality. This is implemented as a best-effort manner and without damaging performance of parts of volumes through localized bottlenecks.