Want to know the key to storage happiness? It’s analytics. Yeah, it’s that simple
Never has the phrase 'Jack of all trades' been more apt
What are you looking for in a new storage system? Performance, capacity, efficiency, data services? Well, from my point of view you should be looking for analytics first! The right analytics tool can easily save you money, time, and make your job easier.
Jack of all trades, master of the infrastructure
It’s not only about storage, no matter what your job. When it comes to IT infrastructures, nowadays you’ll likely need some sort of analytics to help you manage more and better. There are many reasons why:
- Most SysAdmins are jacks of all trades now, and they need to have all the components of their infrastructure under control without spending too much time on it.
- Business requires IT to be pro-active and give more answers, faster.
- It is becoming really complicated doing any form of capacity planning: measuring trends, calculating capacity growth and giving the right sizing for new applications. The old Excel file we used for years had to take into account too many variables to be realistic.
Infrastructures are different but, depending primarily on size, having a correct view of what is going on inside is quite a common problem ... and it is fundamental when it comes to understanding if the entire stack works as expected.
It’s not only about troubleshooting
Statements such as: “I don’t actually know what I can move to as a secondary storage system”, ”You’ll never guess what developers have built around a network shared volume”, or “I don’t exactly know what happens at 11pm, but that particular VM goes nuts!” are just some examples that explain how difficult it is getting the right information when you have to make a decision. And they are all decisions that usually involve spending more money or using more time.
Not all analytics were born equal
IT infrastructure analytics is not new. Some form of it has always been available. But it has evolved considerably and in many ways.
First of all, we now have many more resources to perform a lot more detailed analysis. This means that the number of collected data pints (logs, sensors, etc) are much greater than in the past, improving accuracy, and quantity, of metrics to monitor. But there is much more.
If you look in detail at all the various implementations you can easily see that there are two big areas of interest: storage infrastructure analytics and stored-data analytics. In practice, it depends on what you are more interested in: the content or the container.
I’m not saying that there aren’t points of contact between the two but usually, if one vendor does something really good on one end you can’t expect to have a state-of-the-art analytics implementation for the other ... and there are reasons for that.