Condusiv Technologies Blog

Condusiv Technologies Blog

Blogging @Condusiv

The Condusiv blog shares insight into the issues surrounding system and application performance—and how I/O optimization software is breaking new ground in solving those issues.

Why Faster Storage May NOT Fix It

by Rick Cadruvi, Chief Architect 20. September 2018 04:58

 

With all the myriad of possible hardware solutions to storage I/O performance issues, the question that people are starting to ask is something like:

         If I just buy newer, faster Storage, won’t that fix my application performance problem?

 The short answer is:

         Maybe Yes (for a while), Quite Possibly No.

I know – not a satisfying answer.  For the next couple of minutes, I want to take a 10,000-foot view of just three issues that affect I/O performance to shine some technical light on the question and hopefully give you a more satisfying answer (or maybe more questions) as you look to discover IT truth.  There are other issues, but let’s spend just a moment looking at the following three:

1.     Non-Application I/O Overhead

2.     Data Pipelines

3.     File System Overhead

These three issues by themselves can create I/O bottlenecks causing degradation to your applications of 30-50% or more.

Non-Application I/O Overhead:

One of the most commonly overlooked performance issues is that an awful lot of I/Os are NOT application generated.  Maybe you can add enough DRAM and go to an NVMe direct attached storage model and get your application data cached at an 80%+ rate.  Of course, you still need to process Writes and the NVMe probably makes that a lot faster than what you can do today.  But you still need to get it to the Storage.  And, there are lots of I/Os generated on your system that are not directly from your application.  There’s also lots of application related I/Os that are not targeted for caching – they’re simply non-essential overhead I/Os to manage metadata and such.  People generally don’t think about the management layers of the computer and application that have to perform Storage I/O just to make sure everything can run.  Those I/Os hit the data path to Storage along with the I/Os your application has to send to Storage, even if you have huge caches.  They get in the way and make your Application specific I/Os stall and slow down responsiveness.

And let’s face it, a full Hyper-Converged, NVMe based storage infrastructure sounds great, but there are lots of issues besides the enormous cost with that.  What about data redundancy and localization?  That brings us to issue # 2.

Data Pipelines: 

Since your data is exploding and you’re pushing 100s of Terabytes, perhaps Petabytes and in a few cases maybe even Exabytes of data, you’re not going to get that much data on your one server box, even if you didn’t care about hardware/data failures.  

Like it or not, you have an entire infrastructure of Servers, Switches, SANs, whatever.  Somehow, all that data needs to get to and from the application and wherever it is stored.  And if you add Cloud storage into the mix, it gets worse. At some point the data pipes themselves become the limiting factor.  Even with Converged infrastructures, and software technologies that stage data for you where it is supposedly needed most, data needs to be constantly shipped along a pipe that is nowhere close to the speed of access that your new high-speed storage can handle.  Then add lots of users and applications simultaneously beating on that pipe and you can quickly start to visualize the problem.

If this wasn’t enough, there are other factors and that takes us to issue #3.

File System Overhead:

You didn’t buy your computer to run an operating system.  You bought it to manipulate data.  Most likely, you don’t even really care about the actual application.  You care about doing some kind of work.  Most people use Microsoft Word to write documents.  I did to draft this blog.  But I didn’t really care about using Word.  I cared about writing this blog and Word was something I had, I knew how to use and was convenient for the task.  That’s your application, but manipulating the data is your real conquest.  The application is a tool to allow you to paint a beautiful picture of your data, so you can see it and accomplish your job better.

The Operating System (let’s say Windows), is one of a whole stack of tools between you, your application and your data.  Operating Systems have lots of layers of software to manage the flow from your user to the data and back.  Storage is a BLOB of stuff.  Whether it is spinning hard drives, SSDs, SANs, cloud-based storage, or you name it, it is just a canvas where the data can be stored.  One of the first strokes of the brush that will eventually allow you to create that picture you want from your data is the File System.  It brings some basic order.  You can see this by going into Windows File Explorer and perusing the various folders.  The file system abstracts that BLOB into pieces of data in a hierarchical structure with folders, files, file types, information about size/location/ownership/security, etc... you get the idea.  Before the painting you want to see from your data emerges, a lot of strokes need to be placed on the canvas and a lot of those strokes happen from the Operating and File Systems.  They try to manage that BLOB so your Application can turn it into usable data and eventually that beautiful (we hope) picture you desire to draw. 

Most people know there is an Operating System and those of you reading this know that Operating Systems use File Systems to organize raw data into useful components.  And there are other layers as well, but let’s focus.  The reality is there are lots of layers that have to be compensated for.  Ignoring file system overhead and focusing solely on application overhead is ignoring a really big Elephant in the room.

Let’s wrap this up and talk about the initial question.  If I just buy newer, faster Storage won’t that fix my application performance?  I suppose if you have enough money you might think you can.  You’ll still have data pipeline issues unless you have a very small amount of data, little if any data/compute redundancy requirements and a very limited number of users.  And yet, the File System overhead will still get in your way. 

When SSDs were starting to come out, Condusiv® worked with several OEMs to produce software to handle obvious issues like the fact that writes were slower and re-writes were limited in number. In doing that work, one of our surprise discoveries was that when you got beyond a certain level of file system fragmentation, the File System overhead of trying to collect/arrange the small pieces of data made a huge impact regardless of how fast the underlying storage was.  Just making sure data wasn’t broken down into too many pieces each time a need to manipulate it came along provided truly measurable and, in some instances, gave incredible performance gains. 

Then there is that whole issue of I/Os that have nothing to do with your data/application. We also discovered that there was a path to finding/eliminating the I/Os that, while not obvious, made substantial differences in performance because we could remove those out of the flow, thus allowing the I/Os your application wants to perform happen without the noise.  Think of traffic jams.  Have you ever driven in stop and go traffic and noticed there aren’t any accidents or other distractions to account for such slowness?  It’s just too many vehicles on the road with you.  What if you could get all the people who were just out for a drive, off the road?  You’d get where you want to go a LOT faster.  That’s what we figured out how to do.  And it turns out no one else is focused on that - not the Operating System, not the File System, and certainly not your application. 

And then you got swamped with more data.  Okay, so you’re in an industry where regulations forced that decision on you.  Either way, you get the point.  There was a time when 1GB was more storage than you would ever need.  Not too long ago, 1TB was the ultimate.  Now that embedded SSD on your laptop is 1TB.  Before too long, your phone will have 1TB of storage.  Mine has 128GB, but hey I’m a geek and MicroSD cards are cheap.  My point is that the explosion of data in your computing environment strains File System Architectures.  The good news is that we’ve built technologies to compensate for and fix limitations in the File System.

Let me wrap this up by giving you a 10,000-foot view of us and our software.  The big picture is we have been focused on Storage Performance for a very long time and at all layers.  We’ve seen lots of hardware solutions that were going to fix Storage slowness.  And we’ve seen that about the time a new generation comes along, there will be reasons it will still not fix the problem.  Maybe it does today, but tomorrow you’ll overtax that solution as well.  As computing gets faster and storage gets denser, your needs/desires to use it will grow even faster.  We are constantly looking into the crystal ball knowing the future presents new challenges.  We know by looking into the rear-view mirror, the future doesn’t solve the problem, it just means the problems are different.  And that’s where I get to have fun.  I get to work on solving those problems before you even realize they exist.  That’s what turns us on.  That’s what we do, and we have been doing it for a long time and, with all due modesty, we’re really good at it! 

So yes, go ahead and buy that shiny new toy.  It will help, and your users will see improvements for a time.  But we’ll be there filling in those gaps and your users will get even greater improvements.  And that’s where we really shine.  We make you look like the true genius you are, and we love doing it.

  

 

Big Data Boom Brings Promises, Problems

by Dawn Richcreek 7. September 2018 04:40

By 2020, an estimated 43 trillion gigabytes of data will have been created—300 times the amount of data in existence fifteen years earlier. The benefits of big data, in virtually every field of endeavor, are enormous. We know more, and in many ways can do more, than ever before. But what of the challenges posed by this “data tsunami”? Will the sheer ability to manage—or even to physically house—all this information become a problem?

Condusiv CEO Jim D’Arezzo, in a recent discussion with Supply Chain Brain, commented that “As it has over the past 40 years, technology will become faster, cheaper, and more expansive; we’ll be able to store all the data we create. The challenge, however, is not just housing the data, but moving and processing it. The components are storage, computing, and network. All three need to be optimized; I don’t see any looming insurmountable problems, but there will be some bumps along the road.”

One example is healthcare. Speaking with Healthcare IT News, D’Arezzo noted that there are many new solutions open to healthcare providers today. “But with all the progress,” he said, “come IT issues. Improvements in medical imaging, for instance, create massive amounts of data; as the quantity of available data balloons, so does the need for processing capability.”

Giving health-care providers—and professionals in other areas—the benefits of the data they collect is not always easy. In an interview with Transforming Data with Intelligence, D’Arezzo said, “Data center consolidation and updating is a challenge. We run into cases where organizations do consolidation on a ‘forklift’ basis, simply dumping new storage and hardware into the system as a solution. Shortly thereafter, they often discover that performance has degraded. A bottleneck has been created that needs to be handled with optimization.”

The news is all over it. You are experiencing it. Big data. Big problems. At Condusiv®, we get it.  We’ve seen users of our I/O reduction software solutions increase the capability of their storage and servers, including SQL servers, by 30% to 50% or more. In some cases, we’ve seen results as high as 10X initial performance—without the need to purchase a single box of new hardware. The tsunami of data—we’ve got you covered.

If you’re interested in working with a firm that can reduce your two biggest silent killers of SQL performance, request a demo with an I/O performance specialist now.

If you want to hear why your heaviest workloads are only processing half the throughput they should from VM to storage, view this short video.

How to make NVMe storage even faster

by Spencer Allingham 4. September 2018 07:21

This is a blog to complement a vlog that I posted a few weeks ago, in which I demonstrated how to use the intelligent RAM caching technology found in the V-locity® software from Condusiv® Technologies to improve the performance that a computer can get from NVMe flash storage. You can view this video here:

 

 A question arose from a couple of long-term customers about whether the use of the V-locity software was still relevant if they started utilizing very fast, flash storage solutions. This was a fair question!

The V-locity software is designed to reduce the amount of unnecessary storage I/O traffic that actually has to go out and be processed by the underlying disk storage layer. It not only reduces the amount of I/O traffic, but it optimizes that which DOES have to go out to disk, and moreover, it further reduces the workload on the storage layer by employing a very intelligent RAM caching strategy.

So, given that flash storage, whilst not only becoming more prevalent in today’s compute environments, can process storage I/O traffic VERY fast when compared to its spinning disk counterparts, and is capable of processing more I/Os per Second (IOPS) than ever before, the very sensible question was this:


"Can the use of Condusiv's V-locity software provide a significant performance increase when using very fast flash storage?"


As I was fortunate to have recently implemented some flash storage in my workstation, I was keen to run an experiment to find out.


SPOILER ALERT: For those of you who just want to have

the question answered, the answer is a resounding YES!

The test showed beyond doubt that with Condusiv’s V-locity software installed, your Windows computer has the ability to process significantly more I/Os per Second, process a much higher throughput of data, and allow the storage I/O heavy workloads running in computers the opportunity to get significantly more work done in the same amount of time – even when using very fast flash storage.

 

For those of you true ‘techies’ that are as geeky as me, read on, and I will detail the testing methodology and results in more detail. 

The storage that I now had in my workstation (and am still happily using!) was a 1 terabyte SM961 POLARIS M.2-2280 PCI-E 3.0 X 4 NVMe solid state drive (SSD).

 

 Is it as fast as it’s made out to be? Well, in this engineer’s opinion – OMG YES!

 

It makes one hell of a difference, when compared to spinning disk drives. This is in part because it’s connected to the computer via a PCI Express (PCIe) bus, as opposed to a SATA bus. The bus is what you connect your disk to in the computer, and different types of buses have different capabilities, such as the speed at which data can be transferred. SATA-connected disks are significantly slower than today’s PCIe-connected storage using an NVMe device interface. There is a great Wiki about this here if you want to read more: 

https://en.wikipedia.org/wiki/NVM_Express

 

To give you an idea of the improvement though, consider that the Advanced Host Controller Interface (AHCI) that is used with the SATA connected disks has one command queue, in which it can process 32 commands. That’s up to 32 storage requests at a time, and that was okay for spinning disk technology, because the disks themselves could only cope with a certain number of storage requests at a time.

NVMe on the other hand doesn’t have one command queue, it has 65,535 queues. AND, each of those command queues can themselves accommodate 65,536 commands. That’s a lot more storage requests that can be processed at the same time! This is really important, because flash storage is capable of processing MANY more storage requests in parallel than its spinning disk cousins. Quite simply NVMe was needed to really make the most of what flash disk hardware can do. You wouldn’t put a kitchen tap (faucet) on the end of a fire hose and expect the same amount of water to flow through it, right? Same principle!

As you can probably tell, I’m quite excited by this boost in storage performance. (I’m strange like that!) And, I know I’m getting a little off topic (apologies), so back to the point!

I had this SUPER-FAST storage solution and needed to prove one way or another if Condusiv’s V-locity software could increase the ability of my computer to process even more workload.

Would my computer be able to process more storage I/Os per Second?

Would my computer be able to process a larger amount of storage I/O traffic (megabytes) every second?

 

Testing Methodology

To answer these questions, I took a virtual machine, and cloned it so that I had two virtual machines that were as identical as I could make them. I then installed Condusiv’s V-locity software on both and disabled V-locity on one of the machines, so that it would process storage I/O traffic, just as if V-locity wasn’t installed.

To generate a storage I/O traffic workload, I turned to my old friend IOMETER. For those of you who might not know IOMETER, this is a software utility originally designed by Intel, but is now open source and available at SourceForge.net. It is designed as an I/O subsystem measurement tool and is great for generating I/O workloads of different types (very customizable!), and measure how quickly that I/O workload can be processed. Great for testing networks or in this case, how fast you can process storage I/O traffic.

I configured IOMETER on both machines with the type of workload that one might find on a typical SQL database server. I KNOW, I know, there is no such thing as a ‘typical’ SQL database, but I wanted a storage I/O profile that was as meaningful as possible, rather than a workload that would just make V-locity look good. Here is the actual IOMETER configuration:

Worker 1 – 16 kilobyte I/O requests, 100% random, 33% Write / 67% Read

Worker 2 – 64 kilobyte I/O requests, 100% random, 33% Write / 67% Read

Test Results

V-locity Disabled

 

V-locity Enabled

 

Summary

 

 

Conclusion

 

In this lab test, the presence of V-locity reduced the average amount of time required to process storage I/O requests by around 65%, allowing a great amount of storage I/O requests to be processed per second and a greater amount of data to be transferred.

To prove beyond doubt that it was indeed V-locity that caused the additional storage I/O traffic to be processed, I stopped the V-locity service. This immediately ‘turned off’ all of the RAM caching and other optimization engines that V-locity was providing, and the net result was that the IOPS and throughput dropped to normal as the underlying storage had to start processing ALL of the storage traffic that IOMETER was generating.

What value is there to reducing storage I/O traffic?

The more you can reduce storage I/O traffic that has to go out and be processed by your disk storage, the more storage I/O headroom you are handing back to your environment for use by additional workloads. It means that your current disk storage can now cope with:

·       - More computers sharing the storage. Great if you have a Storage Area Network (SAN) underpinning your virtualized environment, for example. More VMs running!

 

·       - More users accessing and manipulating the shared storage. The more users you have, the more storage I/O traffic is likely to be generated.

·       - Greater CPU utilization. CPU speeds and processing capacity keeps increasing. Now that the processing power is typically much more than typical needs, V-locity can help your applications become more productive and use more of that processing power by not having to wait so much on the disk storage layer.

 

If you can achieve this without having to replace or upgrade your storage hardware, it not only increases the return on your current storage hardware investment, but also might allow you to keep that storage running for a longer period of time (if you’re not on a fixed refresh cycle).

Sweat the storage asset!

(I hate that term, but you get the idea)

When you do finally need to replace your current storage, perhaps it won’t be as costly as you thought because you’re not having to OVER-PROVISION the storage as much, to cope with all of the excess, unnecessary storage traffic that Condusiv’s V-locity software can eliminate.

I typically see a storage traffic reduction of at least 25% at customer sites.

AND, I haven’t even mentioned the performance boost that many workloads receive from the RAM caching technology provided by Condusiv’s V-locity software. It is worth remembering that as fast as today’s flash storage solutions are, the RAM that you have in your computers is faster! The greater the percentage of read I/O traffic that you can satisfy from RAM instead of the storage layer, the better performing those storage I/O-hungry applications are likely to be.

What type of applications benefit the most?

In the real world, V-locity is not a silver-bullet for all types of workloads, and I wouldn’t insult your intelligence by saying that it was. If you have some workloads that don’t generate a great deal of storage I/O traffic, perhaps a DNS server, or DHCP server, well, V-locity isn’t likely to make a huge difference. That’s my honest opinion as an IT Engineer.

HOWEVER, if you are using storage I/O-hungry applications, then you really should give it a try.

Here are just some examples of the workloads that thousands of V-locity customers are ‘performance-boosting’ with Condusiv’s I/O reduction and RAM caching technologies:

  • -Database solutions such as Microsoft SQL Server, Oracle, MySQL, SQL Express, and others.
  • -Virtualization solution such as Microsoft Hyper-V and VMware.
  • -Enterprise Resource Planning (ERP) solutions like Epicor.
  • -Business Intelligence (BI) solutions like IBM Cognos.
  • -Finance and payroll solutions like SAGE Accounting.
  • -Electronic Health Records (EHR) solutions, such as MEDITECH 
  • -Customer Relationship Management (CRM) solutions, such as Microsoft Dynamics.
  • -Learning Management Systems (LMS Solutions.
  • -Not to mention email servers like Microsoft Exchange AND busy file servers.

 

 

Do you use any of these in your IT environment?

 

There are case studies on the Condusiv web site for all of these workload types (and more), here:

http://www.condusiv.com/knowledge-center/case-studies/default.aspx

 

Try it for yourself

You can experience the full power of Condusiv’s V-locity software for yourself, in YOUR Windows environment within a couple of minutes. Just go to www.condusiv.com/try and get a copy of the fully-featured 30-day trialware. You can check the dashboard reporting after a week or two and see just how much storage I/O traffic has been eliminated, and more importantly, how much storage time has been saved by doing do.

It really is that simple!

You don’t even need to reboot to make the software work. There is no disruption to live running workloads; you can just install and uninstall at will, and it only takes a minute or so.


You will typically start seeing results just minutes after installing.

I hope that this has been interesting and helpful. If you have any questions about the technologies within V-locity or have any questions about testing, feel free to email me directly at sallingham@condusiv.co.uk.

 

I will be delighted to hear from you!

 

 

Financial Sector Battered by Rising Compliance Costs

by Dawn Richcreek 15. August 2018 08:39

Finance is already an outlier in terms of IT costs. The industry devotes 10.5% of total revenue to IT—and on average, each financial industry IT staffer supports only 15.7 users, the fewest of any industry.

All over the world, financial services companies are facing skyrocketing compliance costs. Almost half the respondents to a recent Accenture survey of compliance officers in 13 countries said they expected 10% to 20% increases, and nearly one in five are expecting increases of more than 20%.

Much of this is driven by international banking regulations. At the beginning of this year, the Common Reporting Standard went into effect. An anti-tax-evasion measure signed by 142 countries, the CRS requires financial institutions to provide detailed account information to the home governments of virtually every sizeable depositor.

Just to keep things exciting, the U.S. government hasn’t signed on to CRS; instead we require banks doing business with Americans to comply with the Foreign Account Tax Compliance Act of 2010. Which requires—surprise, surprise—pretty much the same thing as CRS, but reported differently.

And these are just two examples of the compliance burden the financial sector must deal with. Efficiently, and within a budget. In a recent interview by ValueWalk entitled “Compliance Costs Soaring for Financial Institutions,” Condusiv® CEO Jim D’Arezzo said, “Financial firms must find a path to more sustainable compliance costs.”

Speaking to the site’s audience (ValueWalk is a site focused on hedge funds, large asset managers, and value investing) D’Arezzo noted that finance is already an outlier in terms of IT costs. The industry devotes 10.5% of total revenue to IT, more than government, healthcare, retail, or anybody else. It’s also an outlier in terms of IT staff load; on average, each financial industry IT staffer supports only 15.7 users, the fewest of any industry. (Government averages 37.8 users per IT staff employee.)

To ease these difficulties, D’Arezzo recommends that the financial industry consider advanced technologies that provide cost-effective ways to enhance overall system performance. “The only way financial services companies will be able to meet the compliance demands being placed on them, and at the same time meet their efficiency and profitability targets, will be to improve the efficiency of their existing capacity—especially as regards I/O reduction.”

At Condusiv, that’s our business. We’ve seen users of our I/O reduction software solutions increase the capability of their storage and servers, including SQL servers, by 30% to 50% or more. In some cases, we’ve seen results as high as 10X initial performance—without the need to purchase a single box of new hardware.

If you’re interested in working with a firm that can reduce your two biggest silent killers of SQL performance, request a demo with an I/O performance specialist now.

 

For an explanation of why your heaviest workloads are only processing half the throughput they should from VM to storage, view this short video.

 

A Deep Dive Into The I/O Performance Dashboard

by Howard Butler 2. August 2018 08:36

While most users are familiar with the main Diskeeper®/V-locity®/SSDkeeper™ Dashboard view which focuses on the number of I/Os eliminated and Storage I/O Time Saved, the I/O Performance Dashboard tab takes a deeper look into the performance characteristics of I/O activity.  The data shown here is similar in nature to other Windows performance monitoring utilities and provides a wealth of data on I/O traffic streams. 

By default, the information displayed is from the time the product was installed. You can easily filter this down to a different time frame by clicking on the “Since Installation” picklist and choosing a different time frame such as Last 24 Hours, Last 7 Days, Last 30 Days, Last 60 Days, Last 90 Days, or Last 180 Days.  The data displayed will automatically be updated to reflect the time frame selected.

 

The first section of the display above is labeled as “I/O Performance Metrics” and you will see values that represent Average, Minimum, and Maximum values for I/Os Per Second (IOPS), throughput measured in Megabytes per Second (MB/Sec) and application I/O Latency measured in milliseconds (msecs). Diskeeper, V-locity and SSDkeeper use the Windows high performance system counters to gather this data and it is measured down to the microsecond (1/1,000,000 second).

While most people are familiar with IOPS and throughput expressed in MB/Sec, I will give a short description just to make sure. 

IOPS is the number of I/Os completed in 1 second of time.  This is a measurement of both read and write I/O operations.  MB/Sec is a measurement that reflects the amount of data being worked on and passed through the system.  Taken together they represent speed and throughput efficiency.  One thing I want to point out is that the Latency value shown in the above report is not measured at the storage device, but instead is a much more accurate reflection of I/O response time at an application level.  This is where the rubber meets the road.  Each I/O that passes through the Windows storage driver has a start and completion time stamp.  The difference between these two values measures the real-world elapsed time for how long it takes an I/O to complete and be handed back to the application for further processing.  Measurements at the storage device do not account for network, host, and hypervisor congestion.  Therefore, our Latency value is a much more meaningful value than typical hardware counters for I/O response time or latency.  In this display, we also provide meaningful data on the percentage of I/O traffic- which are reads and which are writes.  This helps to better gauge which of our technologies (IntelliMemory® or IntelliWrite®) is likely to provide the greatest benefit.

The next section of the display measures the “Total Workload” in terms of the amount of data accessed for both reads and writes as well as any data satisfied from cache. 

 

A system which has higher workloads as compared to other systems in your environment are the ones that likely have higher I/O traffic and tend to cause more of the I/O blender effect when connected to a shared SAN storage or virtualized environment and are prime candidates for the extra I/O capacity relief that Diskeeper, V-locity and SSDkeeper provide.

Now moving into the third section of the display labeled as “Memory Usage” we see some measurements that represent the Total Memory in the system and the total amount of I/O data that has been satisfied from the IntelliMemory cache.  The purpose of our patented read caching technology is twofold.  Satisfy from cache the frequently repetitive read data requests and be aware of the small read operations that tend to cause excessive “noise” in the I/O stream to storage and satisfy them from the cache.  So, it’s not uncommon to see the “Data Satisfied from Cache” compared to the “Total Workload” to be a bit lower than other types of caching algorithms.  Storage arrays tend to do quite well when handed large sequential I/O traffic but choke when small random reads and writes are part of the mix.  Eliminating I/O traffic from going to storage is what it’s all about.  The fewer I/Os to storage, the faster and more data your applications will be able to access.

In addition, we show the average, minimum, and maximum values for free memory used by the cache.  For each of these values, the corresponding Total Free Memory in Cache for the system is shown (Total Free Memory is memory used by the cache plus memory reported by the system as free).  The memory values will be displayed in a yellow color font if the size of the cache is being severely restricted due to the current memory demands of other applications and preventing our product from providing maximum I/O benefit.  The memory values will be displayed in red if the Total Memory is less than 3GB.

Read I/O traffic, which is potentially cacheable, can receive an additional benefit by adding more DRAM for the cache and allowing the IntelliMemory caching technology to satisfy a greater amount of that read I/O traffic at the speed of DRAM (10-15 times faster than SSD), offloading it away from the slower back-end storage. This would have the effect of further reducing average storage I/O latency and saving even more storage I/O time.

Additional Note: For machines running SQL Server or Microsoft Exchange, you will likely need to cap the amount of memory that those applications can use (if you haven’t done so already), to prevent them from ‘stealing’ any additional memory that you add to those machines.

It should be noted the IntelliMemory read cache is dynamic and self-learning.  This means you do not need to pre-allocate a fixed amount of memory to the cache or run some pre-assessment tool or discovery utility to determine what should be loaded into cache.  IntelliMemory will only use memory that is otherwise, free, available, or unused memory for its cache and will always leave plenty of memory untouched (1.5GB – 4GB depending on the total system memory) and available for Windows and other applications to use.  As there is a demand for memory, IntelliMemory will release memory from it’s cache and give this memory back to Windows so there will not be a memory shortage.  There is further intelligence with the IntelliMemory caching technology to know in real time precisely what data should be in cache at any moment in time and the relative importance of the entries already in the cache.  The goal is to ensure that the data maintained in the cache results in the maximum benefit possible to reduce Read I/O traffic. 

So, there you have it.  I hope this deeper dive explanation provides better clarity to the benefit and internal workings of Diskeeper, V-locity and SSDkeeper as it relates to I/O performance and memory management.

You can download a free 30-day, fully functioning trial of our software and see the new dashboard here: www.condusiv.com/try

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