Imagine a conveyer belt in a manufacturing unit, wherein different components are traveling at a specified time and in specified quantity to help build a quality finished product. Now, what will happen if all of a sudden – at one juncture – many components get dumped on the conveyer belt at once? How would the process be handled then? The complexity of a storage array is not much different, especially with the number of applications and workloads increasing with every day passing. Now the question for you is: what to do? Does this call for an investment in a number of storage arrays (one per application or workload) and thus an increased complexity for storage or datacenter admins? Or would it be better to invest in one single storage array and ensure it is powerful enough to handle whatever is thrown in its way, without impacting the demands from users? Apart from much other functionality in a respective storage array, this is where cache becomes important.
So what is cache?
A cache here can be referred as a bucket wherein data can be held for some time while it is on its way to getting stored on disk or while it is passed on to the user (as per case). This becomes important because in either of the scenarios it will help shorten your time to access that data and will invariably improve the input and output. It makes a direct impact on application performance. Considering that almost every second workload is dependent upon I/O operations, this functionality can be definitely leveraged upon.
And what are the various types of cache?
From a storage perspective, there are two main classifications for cache:
- Storage cache: A small quantity but high performing buffer which is placed near the CPU. This is a straight-forward approach and helps reducing the time taken to access the data by reducing CPU cycles, hence less wait for the user.
- Flash cache: A repository which is created by storing data temporarily on high performing SSDs, so that your requests can be addressed more quickly. This makes sense when workloads are more and heavier and are moving towards petabytes.
And this helps in?
Business has to grow, competitors are many and customers only so few. If you have to appeal to customers, you have to make sure that you understand what they want and what their preferences are. You also have to understand any trends that can be established and leveraged on. This is where analytics come into play. But then again analyzing data is not an easy task. There will be many and often simultaneous requests to read through a data set. Cache gives you the buffer to store and access data which is important and has to be analyzed by more than one user at a given point in time.
With the wave of digitalization setting in, you have to make sure that you have room for database / commercial transactions, which are used concurrently by hundreds of users at one time. The ideal example would be a payment gateway or an ATM machine. These transactions, which are often referred to as OLTP, are fast and accurate but thrive on availability, speed and recoverability. An additional buffer within your storage array will give you the speed, flexibility and timeliness to address these transactions all at once.
Storage caching is thus a technology that helps address any shortfalls of a traditional storage array. It can give you the flexibility and speed of a powerful storage array, at the same time it can also give you a cost-effective solution. Having said that, it is important to invest in a storage array which is based on a caching mechanism that makes sense for your business.