Block Storage Considerations When Designing a Data Center
Recent trends in big data have affected organizations at all levels, and as a result, many companies are looking to redesign or expand their data centers to accommodate the increased quantity of data and meet the performance needs of end users.
When designing a data center, whether virtualized or not, high-performance storage should be a key consideration. Unfortunately, because it is difficult to gain visibility into the ways applications access and use block sizes, optimizing a data center for block storage is often left to guesswork.
The Basics of Block Storage
Block storage is composed of block sizes or, simply put, chunks of data. Each block size has its own address, but there is no additional metadata to provide more context on what data is within a given block. Because block storage is accessed directly by the operating system, it performs well for structured database storage, random read/write loads and virtual machine file systems and volumes.
However, because there can be multiple applications supporting multiple workloads, each application creates its own unique workload. In this environment, it is difficult to determine the optimal block storage capacity because there is low visibility into block size for each input/output being sent or received.
Why Block Storage Matters
The biggest risk is that if block storage isn’t optimized to block size, there will be vulnerabilities in storage performance, particularly if the storage system isn’t designed to handle a large block input/output. The size and quantity of blocks also affects the processing power and bandwidth required on servers and networks, both of which can further degrade performance.
According to Data Center Knowledge, to keep performance reliable and deliver input/output in a timely manner, it’s crucial to know that 30 percent of the blocks are 64KB in size and to understand how they are distributed over time and how latencies or other attributes of blocks of various sizes relate to each other.
Block Storage in the Cloud
Much of the data accessed by applications now exists in the cloud, so data storage needs to be optimized for cloud environments. Though cloud storage is used to manage data as objects, it now incorporates methods such as block storage to make it easy to provision storage, especially when consistency is needed for real-time systems, such as databases that require continual input/output.
Designed With Performance in Mind
Optimizing for block storage can be challenging, but insight into how applications are using blocked data should be part of the design process for any data center, whether virtual or physical. When in doubt about how to measure and calculate block storage, enterprises should reach out to a knowledgeable consultant who can provide storage techniques and software tools that will optimize block storage.