Data Virtualisation is More Than Just Migration for Primary Data

Disclaimer: I recently attended Storage Field Day 10.  My flights, accommodation and other expenses were paid for by Tech Field Day. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.

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Before I get started, you can find a link to my raw notes on Primary Data’s presentation here. You can also see videos of the presentation here. I’ve seen Primary Data present at SFD7 and SFD8, and I’ve typically been impressed with their approach to Software-Defined Storage (SDS) and data virtualisation generally. And I’m also quite a fan of David Flynn‘s whiteboarding chops.

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Data Virtualisation is More Than Just Migration

Primary Data spent  some time during their presentation at SFD10 talking about Data Migration vs Data Mobility.

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[image courtesy of Primary Data]

Data migration can be a real pain to manage. It’s quite often a manual process and is invariably tied to the capabilities of the underlying storage platform hosting the data. The cool thing about Primary Data’s solution is that it offers dynamic data mobility, aligning “data’s needs (objectives) with storage capabilities (service levels) through automated mobility, arbitrated by economic value and reported as compliance”. Sounds like a mouthful, but it’s a nice way of defining pretty much what everyone’s been trying to achieve with storage virtualisation solutions for the last decade or longer.

What I like about this approach is that it’s a data-centric, rather than employing a storage platform focused approach. Primary Data supports “anything that can be presented to Linux as a block device”, so the options to deploy this stuff are fairly broad. Once you’ve presented your data to DSX, there’s some smart service level objectives (SLOs) that can be applied to the data. These can be broken down into the categories of protection, performance, and price/penalty:

Protection

  • Durability
  • Availability
  • Recoverability – Security
  • Priority
  • Sovereignty

Performance

  • IOPS / Bandwidth / Latency – Read / Write
  • Sustained / Burst

Price / Penalty

  • Per File
  • Per Byte
  • Per Operation

Access Control can also be applied to your data. With Primary Data, “[e]very storage container is a landlord with floorspace to lease and utilities available (capacity and performance)”.

 

Further Reading and Final Thoughts

I like the approach to data virtualisation that Primary Data have taken. There are a number of tools on the market that claim to fully virtualise storage and offer mobility across platforms. Some of them do it well, and some focus more on the benefits provided around ease of migration from one platform to another.

That said, there’s certainly some disagreement in the market place on whether Primary Data could be considered a fully-fledged SDS solution. Be that as it may, I really like the focus on data, rather than silos of storage. I’m also a big fan of applying SLOs to data, particularly when it can be automated to improve the overall performance of the solution and make the data more accessible and, ultimately, more valuable.

Primary Data has a bunch of use cases that extend beyond data mobility as well, including deployment options ranging from Hyperconverged, software-defined NAS and clustering across existing storage platforms. Primary Data want to “do for storage what VMware did for compute”. I think the approach they’ve taken has certainly gotten them on the right track, and the platform has matured greatly in the last few years.

If you’re after some alternative (and better thought out) posts on Primary Data, you can read Jon‘s post here. Max also did a good write-up here, while Chris M.Evans did a nice preview post on Primary Data that you can find here.

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  1. Pingback: Storage Field Day 10 – Wrap-up and Link-o-rama | penguinpunk.net

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