To recap, below you will find the previous articles:

• ThinIO facts and figures, Part 1: VDI and Ram caching.
• ThinIO facts and figures, Part 2: The Bootstorm chestnut.

Off topic note:

two years ago at an E2EVC event, the concept behind ThinIO was born with just a mad scientist idea amongst peers.

If you are lucky enough to be attending E2EVC this weekend, David and I will be there presenting ThinIO and maybe, just maybe there will be an announcement. Our session is on Saturday at 15:30 so pop by, you won’t be disappointed.

Back on topic:

So here’s a really interesting blog post. Remote Desktop Services (XenApp / XenDesktop hosted shared) or whatever you like to call it. RDS really presents a fun caching platform for us, as it allows us to deal with a much higher IO volume and achieve deeper savings.

We’ve really tested the heck out of this platform for how we perform on Microsoft RDS, Horizon View RDS integration and Citrix XenSplitPersonality with Machine Creation Services.

The figures we are sharing today are based on the following configuration and load test:

• Citrix XenDesktop 7.6
• Windows Server 2012 r2
• Citrix User Profile Manager.
• 16gb of Ram.
• 4 vCpu.
• LoginVSI 4.1 medium workload 1 hour test.
• 10 users.
• VMFS 5 volume.

Fun figures!

Diving straight in, lets start by looking at the volume of savings across three cache types.

Reviewing the details for a moment:

Running repetitive tests of at least 3 per cache type, we found even at the lowest entry point we would support (50mb per user) we saw phenomenal savings of over 70% on write IO.

No pressure no diamonds!

To put that into perspective, at a 512 MB cache for 10 users, our cache reached maximum capacity at the second user login. With 8 users still left to login, cache full and still an hours worth of load testing left, our ThinIO technology was under serious pressure.

This is key to why ThinIO is such a great solution. We won’t just perform great until we fill our cache, we don’t require architecture changes or care about your storage type, we have no lead times or install days, we will carry on to work with what is available to use, to take a large ammount of pressure off storage IOPS and data throughput.

With the figures above, you can see just how well the intelligence behind our cache can scale even when it faces such a steep workload.

Below you will find a breakdown of each test:

512 MB cache:

Breaking down into the figures, on the 512mb cache test, it’s clear to see just how well ThinIO deals with the tiniest of caches:

When we side by side this with our baseline averages, you can see we take a huge chunk out of that Spiky login pattern and continue to  reduce the steady state IO as the test continues:

So lets move up and see how we get on!

1024 mb cache:

Doubling up our cache size we see a great increase in both read and write savings as you’d expect.

With 100mb of cache per user, and the average user profile in the test 3 times that size. We are still under pressure. As we will natively favour optimisations to write IO over read, you’ll see the bulk of improvements happen in write when we’re under pressure as illustrated in this test:

With more cache available during the peak IO point, we make further savings on write:

2048 mb cache:

and at our recommended value of 200mb per user in Remote Desktop Services, the results are phenomenal! With this size, even still below the 300mb mark per user profile, the read IO gets a really good boost and the write IO saving well over the 95% mark!

And the side by side comparison is every bit as good as the savings illustrated above, reducing that peak bursty IO to just 41 IOPS:

But there’s more! 

As i pointed out in the previous blog, IOPS are just one side of the story. A reduction of data throughput to the disk is also a big benefit when it comes to storage optimisation, and as you can see we make a big difference:

Wrap up:

So there you have it, with ThinIO, a simple, in VM solution, you can you seriously reduce your IO footprint, boost user performance and achieve greater storage density per virtual machine or on Remote Desktop Services technology.

In the mean time:

If you would like a chance to test ThinIO pre-release, find access to the public beta below. Thank you for your time and happy testing!

Test, test, review and tune. Rinse and repeat!

We’ve spent months load testing, tuning, fixing and retesting ThinIO. And for the first time we’re going to start talking about the dramatic results ThinIO can have on storage scalability and user perceived performance.

During our extensive testing cycles, we’ve covered:

• Horizon View
• Citrix XenDesktop
• Microsoft RDS

We’ve been seeing very similar, if not identical results when testing against pools on the following storage types too:

• XenServer SR
• VMFS
• NFS
• Microsoft Clustered Shared Volumes

For reference the statistics we’re sharing today are based on VDI via VMware Horizon View 6, these figures are averages across at least three independent tests. All details of the tests that exported these results are covered below.

Testing details:

The VM’s we tested in this particular workload are as follows:

• Testing Method: Login VSI 4.1 Medium Workload
• Operating System: Windows 7 x64 SP1
• System ram: 3gb
• vCPU: 2
• ThinIO cache: 350mb
• Technology:  VMware Horizon View 6
• Test runtime: 1 hour*
• Statistic sample period: 5 seconds.

With that out of the way, lets jump right in!

Storage IO:

The number of IO’s per second is crucially important when dealing with storage; many, many small IO’s sent to sparse locations on disk are a killer to storage technologies, only made worse by certain file systems.

As a storage acceleration and negation technology, were extremely happy with the IO’s reduction we see on the storage:

Even with just 350 MB of ram as a cache, we achieve phenomenal IO reduction.

Storage MB / Sec:

But IO’s are just one part of the puzzle, what about the size of the data requests being sent to the storage?

A true solution to take the pressure off the SAN, improve user performance, and increase storage density needs to tackle both the IO and the throughput problem.

As you can see above, with just 350mb we’re very good at it!

Side by Side Comparison:

So rounded figures are fine so long as the data is trustworthy, but here’s a real preview laid bare for your analysis.

Here’s a direct comparison on NFS and VMFS of taking a standard load test IO pattern and comparing it to an identical test with ThinIO installed in the VM:

VMFS:

NFS:

As you can imagine, we’re extremely proud of what we can achieve with as little as 350mb per desktop.

The beauty of our approach is simplicity, your users can see this benefit not in a matter of weeks, days or even hours. ThinIO can be up and running in minutes, delivering reduced login times, storage acceleration and providing a far deeper density on your current storage.

Wrap up:

So there you have it, we’ll be adding additional blog posts in the coming days looking at Remote Desktop Services / XenApp, intelligent cache management built in and our Read Ahead technology, so check back. In the mean time, if you would like a chance to test ThinIO pre-release, find access to the public beta below. Thank you for your time and happy testing!

* Eight-hour figures and complete statistics are also available, we have nothing to hide and we’d encourage you to get in touch with the ThinScale team and we’ll share them with you.

Warm up your labs or fire up your golden images ladies and gents, we’re delighted to announce ThinIO’s brief public beta will begin today!

This project has taught us some really interesting things about Windows IO, how Windows behaves and how the hypervisor and storage can behave. This project really felt like a David vs. Goliath task as we (members of our community with a desire to simplify this issue) attempted to tackle one of the largest issues in our industry, storage bottlenecks and Windows desktops.

What’s really unique about our approach is there are no hardware lead times, no architecture changes needed and no external dependencies. ThinIO can be installed in seconds and the benefits are seen immediately.

We’ve spent countless hours testing, tuning, retesting and even more tuning. We’re extremely happy with the results. This public beta will serve as an opportunity for you to really kick the tyres and believe the hype in what we’ve built while we’re putting together the final touches to release the product in the coming weeks.

During this time, we found achieving positive and consistent IO negation boils down to a number of items:

• cutting down on the volume of IOPS sent to the storage.
• Reducing the data transferred (MB/sec) to and from the storage.
• Intelligently cutting down on peak IO, such as boot and user logon.

In the coming days we’re going drill down into these categories in more depth. But as a quick overview, here’s a baseline (top) and ThinIO (bottom) session comparison of a Windows 8.1 desktop login, 1 hour Login VSI medium workload and log off with just 350 mb of cache for ThinIO:

Keep an eye out for the coming blog posts, but in the mean time, the ThinIO beta is available to download here now! Go forth and have fun.

Until next time,

A