IBM Storwize V7000 RtC: “Freshly Squeezed” Revisited

Back in 2012 after IBM announced Real-time Compression (RtC) for Storwize disk systems I covered the technology in a post entitled “Freshly Squeezed“. The challenge with RtC in practice turned out to be that on many workloads it just couldn’t get the CPU resources it needed, and I/O rates were very disappointing, especially in its newly-released un-tuned state,

We quickly learned that lesson and IBM’s Disk Magic was an essential tool to warn us aboout unsuitable workloads. Even in August 2013 when I was asked at the Auckland IBM STG Tech Symposium “Do you recommend RtC for general use?” My answer was “Wait until mid 2014”.

Now that the new V7000 (I’m not sure we’re supposed to call it Gen2, but that works for me) is out, I’m hoping that time has come.

The New V7000: I was really impressed when we announced the new V7000 in May 2014 with it’s 504 disk drives, faster CPUs, 2 x RtC (Intel Coleto Creek comms encryption processor) offload engines per node canister, and extra cache resources (up to 64GB RAM per node canister, of which 36GB is dedicated to RtC) but having been caught out in 2012, I wanted to see what Disk Magic had to say about it before I started recommending it to people. That’s why this post has taken until now to happen – Disk Magic 9.16.0 has just been released.

Coleto Creek RtC offload engine:Coleto Creek

After a quick look at Disk Magic I almost titled this post “Bigger, Better, Juicier than before” but I felt I should restrain myself a little, and there are still a few devils in the details.

50% Extra: I have been working on the conservative assumption of getting an extra 50% nett space from RtC across an entire disk system if little was known about the data. It is best to run IBM’s Comprestimator so you can get a better picture if you have access to do that however.

Getting an extra 50% is the same as setting Capacity Magic to use 33% compression. Until now I believed that this was a very conservative position, but one thing I really don’t enjoy is setting an expectation and then being unable to deliver on it.

Easy Tier: The one major deficiency in Disk Magic 9.16.0 is that you can’t model Easy Tier and RtC in the same model. That is pretty annoying since on the new V7000 you will almost certainly want both. So unfortunately that means Disk Magic 9.16.0 is still a bit of a waste of time in testing most real-life configurations that include RtC and the real measure will have to wait until the next release due in August 2014.

What you can use 9.16.0 however is to validate the performance of RtC (without Easy Tier) and look at the usage on the new offload engines. What I found was that the load on the RtC engines is still very dependent on the I/O size.

I/O Size: When I am doing general modelling I used to use 16KB as a default size since that is the kind of figure I had generally seen in mixed workload environments, but in more recent times I have gone back to using the default of 4KB since the automatic cache modelling in Disk Magic takes a lot of notice of the I/O size when deciding how random the workload is likely to be. Using 4KB forces Disk Magic to assume that the workload is very random, and that once again builds in some headroom (all part of my under-promise+over-deliver strategy). If you use 16KB, or even 24KB as I have seen in some VMware environments, then Disk Magic will assume there are a lot of sequential I/Os and I’m not entirely comfortable with the huge modeled performance improvement you get from that assumption. (For the same reason these days I tend to model Easy Tier using the ‘Intermediate’ setting rather than the default/recommended ‘High Skew’ setting.)

However, using a small I/O size in your Disk Magic modelling has the exact opposite effect when modelling RtC. RtC runs really well when the I/O size is small, and not so well when the I/O size is large. So my past conservative practice of modelling a small I/O size might not be so conservative when it comes to RtC.

Different Data Types: In the past I have also tended to build Disk Magic models with one server, this is because my testing showed that having several servers or a single server gave the same result. All Disk Magic cared about was the number of I/O requests coming in over a given number of fibres. Now however we might need to take more careful account of data types and focus less on the overall average I/O size and more on the individual workloads and which are suitable for RtC and which are not.

50% Busy: And just as we should all be aware that going over 50% busy on a dual controller system is a recipe for problems should we lose a controller for any reason (and faults are also more likely to happen when the system is being pushed hard) similarly going over 50% busy on your Coleto Creek RtC offload engines would also lead to problems if you lose a controller.

I always recommend that you use all 4 compression engines +extra cache on each dual controller V7000 and now I’m planning to work on the assumption that, yes I can get 1.5:1 compression overall, but that is more likely to come from 50% being without compression and 50% being at 2:1 compression and my Disk Magic models will reflect that. So I still expect to need 66% physical nett to get to 100% target, but I’m now going to treat each model as being made up of at least two pools, one compressed and one not.

Transparent Compression: RtC on the new Gen2 V7000 is a huge improvement over the Gen1 V7000. The hardware has been specifically designed to support it, and remember that it is truly transparent and doesn’t lose compression over time or require any kind of batch processing. That all goes to make it a very nice technology solution that most V7000 buyers should take advantage of.


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