RAID & Erasure Coding

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RAID stands for redundant array of independent disks. The incoming data is divided or replicated across multiple drives to deliver performance. This used to be the trusted protection available in the traditional storage array world until SDS came.

Advantages of RAID

  • Predictable disk performance based on disks

Disadvantages of RAID

  • High-capacity drive rebuilds can take days or weeks
  • Performance bottlenecks often

RAID 0 – Striping

This raid offers high performance for writes as data is spread across different disks & its spindles, however, has no protection for data against disk failures.

RAID 1 – Mirroring

This raid offers redundant copies of data and high-performance reads. Writes are slower as data needs to be mirrored to peer disks.

RAID 1+0 – Stripe of Mirrors 

Data is striped across all mirrors and this offers high-performance reads and writes.

RAID 4 – Dedicated Parity 

In this raid, one disk is dedicated to parity and this disk offers parity to the data disk should it fail.

RAID 5 – Distributed Parity 

In this raid, parity is distributed across all disks so there is no requirement for a dedicated disk to store parity info.

RAID 6 – Dual Distributed Parity 

This raid offers dual parity protection and parity info is spread across all disks.

Erasure Coding

Erasure coding is similar to RAID but on a per-object level. Data is broken down into fragments and encoded. Should any number of drives fail, all of the nodes in the cluster work in parallel to heal the situation as quickly as possible, so data is fully protected once again. The cluster can be configured to meet any requirements for uptime.

Advantages of Erasure Coding

  • No dedicated drives for parity so consumes less storage
  • Allows for failure of two or more elements in the storage system

Disadvantages of Erasure Coding

  • Parity Calculation is CPU intensive
  • Huge Latency during the rebuild and slow production workloads.

How Erasure Coding Works

The incoming data X1 is split into chunks and spread across nodes. In this example, 2 nodes can fail and data can still be rebuilt.

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By Ash Thomas

Ash Thomas is a seasoned IT professional with extensive experience as a technical expert, complemented by a keen interest in blockchain technology.

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