History of Hierarchical Storage Management
Having multiple storage tiers is not a new thing. Actually history of hierarchical storage management (HSM) goes quite far. It was actually first implemented by IBM on their mainframe computer platforms to reduce to the cost of data storage, and to simplify the process to get data from slower media. Idea was to that the actual user would not need to know where the data was actually stored and how to get it back – with HSM the computer would retrieve the asked data automatically.
Historically HSM was somewhat buried when world went from 1st platform to 2nd platform (Client-Server, PC-era). Quite soon many organizations realised they still had application needs for centralized storage platforms and so the storage area networks (SAN) was pretty much born. After server virtualization exploded need for high performance storage organizations realized that, again, it was too expensive to run all application data in one high performance storage tier or it was just too difficult to move data between isolated storage tiers. Tiering, or HSM, was actually born again.
Many storage vendors implemented somekind of tiering system. Some implemented system monitoring actual hot blocks and then migrated those hot blocks between slower and faster tier or 3-tier (SSD, SAS and SATA). Comparing these systems only difference was typically size of the block moved and frequency of moving blocks. This was approach for IBM, EMC and HDS (and many others also), just few to name. There was no big problem with this approach since it solved many problems but in many cases it just reacted too slow to performance needs. With proper design this works very well.
Other vendors implemented tiering based on caching. Every storage system has cache (read and write) but these vendors approach for tiering was implementing method to add high performance disks (SSD) to extend size of the cache. This reacts very fast to changes and typically doesn’t need any tuning. However this approach doesn’t allow you to pin application data to selected tier so proper design is critical.
All flash storage changed the game
Late 2000 all flash storage systems moved very high performance applications from tiered storage to pure flash platform. Price of the flash was very high and typically you had one all flash system per application. Few years later all flash systems actually replaced spinning disks and tiered storage pretty much on most of the organizations since pricing of the flash became affordable and implementation of efficiency technologies (deduplication and compression) meant you could put more data on same disk capacity which actually dropped the gigabyte pricing quite close to high performance spinning disks (10/15k SAS drives).
Suddenly you didn’t need any tiering since all flash systems gave you enough performance to run all your applications but this introduced isolated silos and moving from 2nd platform to 3rd platform means very dramatical growth in data amounts.
Living in the world of constant data growth
Managing unstructured data continues to be a challenge for most of the organizations. When Enterprise Strategy Group surveys IT managers about their biggest overall storage challenges, growth and management of unstructured data comes out at or near the top of the list most of the time.
And that challenge isn’t going away. Data growth is accelerating, driven by a number of factors:
The Internet of Things
We now have to deal with sensor data generated by everything. Farmers are putting health sensors on livestock so they can detect issues early on, get treatment and stop illness from spreading. They’re putting sensors in their fields to understand how much fertilizer or water to use, and where. Everything from your refrigerator to your thermostat will be generating actionable data in the not too distant future.
Bigger, much richer files
Those super-slow motion videos we enjoy during sporting events are shot at 1,000 frames per second with 2 MB frames. That means 2 GB of capacity is required for every second of super-slow motion video captured. And it’s not all about media and entertainment; think about industry-specific use cases leveraging some type of imaging, such as healthcare, insurance, construction, gaming and anyone using video surveillance.
More data capture devices
More people are generating more data than ever before. The original Samsung Galaxy S smartphone had a 5 megapixel camera, so each image consumed 1.5 MB of space compressed (JPEG) or 15 MB raw. The latest Samsung smartphone takes 16 megapixel images, consuming 4.8 MB compressed/48 MB raw storage — thats a 3 fold increase in only few years.
Enterprise Data Lake is 2017 version of tiered storage
Tiered storage, as it used to be implemented, has born again with next generation of old idea. In modern world tiering is solving problems related to massive data growth. More and more production data is going to All Flash arrays but since only 10-30% of actual data is really hot organizations must implement somekind of secondary storage vision to be able move cold data from still expensive primary storage to much cheaper secondary storage.
The secondary storage today is object based storage to response fast pace of data growth and data locality problems of IoT. Organizations are going to use this same object storage platform for their Internet of Things needs and also maybe place to hold their production application data backups.