Read Ahead, Dead Ahead…

Just a short one to relate an experience and sound a warning about the wonderful modern invention of read ahead cache.

Let me start by quoting an arstechnica post from 2010:

I have this long-running job (i.e. running for MONTHS) which happens to be I/O-bound. I have 8 threads, each of which sequentially reads from an 80GB file, loads it into a specialized database, and then moves on to the next 80GB file. The machine has four CPUs, but the concurrency level was chosen empirically to get the maximum I/O throughput.

Today I was pondering how I could make this job finish before I die, and after some googling around I found you can jack up Linux’s read-ahead buffers to improve sequential reads. Basically it makes the kernel seek less, and slurp in more data before it moves on to the next operation. This is a good trade if you have tons of free memory.

Well, needless to say I was shocked at the improvement this brings. I set the readahead from the default of 256 (== 128KiB) to 65536 (== 32MiB) and the IO jumped way, way up. According to sar, in the ten-minute period before I made the change the input rate was 39.3MiB/s. In the first ten minute falling entirely after I made the change, the input rate was 90.0MiB/s. Output rate (to the database) leaped from 6MiB/s to 20MiB/s. CPU iowait% dropped from 49% to 0% , idle% dropped from 13% to 0%, and user% jumped from 37% to 97%.

In other words, this one simple command changed my workload from IO-bound to CPU-bound. I am using RHEL5, Linux 2.6.18.

blockdev --setra 65536 /dev/md0

Sounds great!

Why not make that the default setting for everything?

So here’s why not.

Without going into customer specific details I can tell you that right here in 2017 some workloads are very random, and truly random reads benefit very little from read ahead cache. In fact what can happen is that the storage just gets jammed up feeding data to the read ahead cache. If every 128 KiB random read gets translated into a 32 MiB read ahead and you start hitting high I/O rates then you can expect latency to go through the roof, and no amount of tuning at the storage end is going to help you.

So, if you’re diagnosing latency problems on a heavy random read workload, remember to ask your server admins about their read ahead settings.


Comprestimator Guesstimator

Hey folks, just a quick post for you based on recent experience of IBM’s NAS Comprestimator utility for Storwize V7000 Unified where it completely failed to predict an outcome that I had personally predicted 100% accurately, based on common sense. The lesson here is that you should read the NAS Comprestimator documentation very carefully before you trust it (and once you read and understand it you’ll realize that there are some situations in which you simply cannot trust it).data-swamp

We all know that Comprestimator is a sampling tool right? It looks at your actual data and works out the compression ratio you’re likely to get… well, kind of…

Let’s look first at the latest IBM spiel at

“The Comprestimator utility uses advanced mathematical and statistical algorithms to perform the sampling and analysis process in a very short and efficient way.”

Cool, advanced mathematical and statistical algorithms – sounds great!

But there’s a slightly different story told on an older page that is somewhat more revealing

“The NAS Compression Estimation Utility performs a very efficient and quick listing of file directories. The utility analyzes file-type distribution information in the scanned directories, and uses a pre-defined list of expected compression rates per filename extension. After completing the directory listing step the utility generates a spreadsheet report showing estimated compression savings per each file-type scanned and the total savings expected in the environment.

It is important to understand that this utility provides a rough estimation based on typical compression rates achieved for the file-types scanned in other customer and lab environments. Since data contained in files is diverse and is different between users and applications storing the data, actual compression achieved will vary between environments. This utility provides a rough estimation of expected compression savings rather than an accurate prediction.

The difference here is that one is for NAS and one is for block, but I’m assuming that the underlying tool is the same. So, what if you have a whole lot of files with no extension? Apparently Comprestimator then just assumes 50% compression.

Below I reveal the reverse-engineered source code for the NAS Comprestimator when it comes to assessing files with no extension, and I release this under an Apache licence. Live Free or Die people.


int main()
printf(“IBM advanced mathematical and statistical algorithms predict the following compression ratio: 50% \n”);
return 0;

enjoy : )



Containers to the left of me, PaaS to the right…

… Here I am stuck in the middle with you (with apologies to Stealers Wheel)

Is Cloud forking? Lean mean Containers on the one hand, and fat rich Platform-as-a-Service on the other? Check out my latest blog post here and find out.


One does not simply do scalable HA NAS

Check out my latest blog post at

One does not simply 5

Ben Corrie on Containers… Live in New Zealand

Tempted as I am to start explaining what containers are and why they make sense, I will resist that urge and assume for now you have all realised that they are a big part of our future whether that be on-premises or Public Cloud-based.

Containers are going to bring as much change to Enterprise IT as virtualization did back in the day, and knowing how to do it well is vital to success.

ViFX is bringing Ben Corrie, Containers super-guru, to New Zealand to help get the revolution moving.

Ben blogged about the potential for containers back in June 2015. Click on his photo for a quick recap:


Register now to hear one of the key architects of change in our industry speak in Auckland and Wellington in April, along with deep dive and demos in a 3 hour session. I would suggest to those further afield that this is also worth flying in from Australia, Christchurch etc.

Auckland 19th April

Wellington 21st April


And since it’s been a while since I finished a post with a link to youtube, here is The Fall doing “Container Drivers“.

Object Storage Infographic

As a  follow-up to my earlier post comparing Object Storage to Block Storage, here’s a quick infographic to remind you of some of the key differences.

Object storage infographic 160321

Treat me like an Object!

Object Storage that is…

By now most of us have heard of Object Storage and the grand vision that life would be simpler if storage spent less time worrying about block placement on disks and walking up and down directory trees, and simply treated files like objects in a giant bucket, i.e. a more abstracted, higher level way to deal with storage.

May latest blog post is all about how Object Storage differs from traditional block and file, and also contains a bit of a drill down on some of the leading examples in the market today.

Head over to for the full post.

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