Tag: "Dedupe"

Efficiency vs. Optimization


“Storage Efficiency” has become a big topic over the past 12 months.  There are a number of new technologies that have come out in the last few years that are helping to deal with storage growth.  We all know that data is the root of the decisions that drive business today.  The more data you have, hopefully, the better decisions you can make to drive your business to success.  The question is, “what is the value (and hence the cost) of the infrastructure to create that success?”  What we do know is that the ability to put more data in a highly efficient footprint can give your company a competitive edge.  There are five technologies that can help an IT organization create an efficient storage infrastructure.  These are:

 

1)      Tiering

2)      Virtualization

3)      Thin Provisioning

4)      Compression

5)      Deduplication

It is also important to point out that there are some semantics when talking about storage efficiency, specifically between efficiency and optimization technologies.  I think it is useful to attempt to define these as they lead us to picking the right solutions for what we are trying to accomplish.  For the purpose of this post, efficiency will relate to making existing capacity more useful and optimization will mean making more capacity out of existing capacity.

Using these definitions, technologies such as Tiering, Virtualization and Thin Provisioning are efficiency technologies.  These technologies help to utilize the existing capacity that you have.

Tiering is technology that is used on about 10% of your data or less.  It is used to move data that requires higher performance to flash storage.  Good tiering technology analyzes data access patterns and moves the most active data to the highest performing disk.  It doesn’t really change the amount of physical capacity that is required; it just changes what type of capacity is required and allows IT to make sure data is operating as fast and efficiently as possible.

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Data Protection, Retention and Archive Starts with Data Value


 It feels good to open up the blogging again to new topics, especially ones I am intimately familiar with.  (But have no fear, there will be references to primary storage optimization / compression.)

This weekend I had an interesting conversation with my Dad.  We were discussing backup.  My dad basically runs IT for the State of Maine.  The State of Maine uses CommVault backup software.  So I posed the question to him, “What would it take for you to rip out CommVault and replace it with another solution.  He thought about it for a moment and replied “I wouldn’t”.  His answer came down to a couple of reasons.

First was the expense.  It’s not just about buying the new software, it would be training people to run the new software and it would be about throwing away the massive investment they have in their existing product as well as converting all the years of backup takes created with one software to the new software.  This is one of the biggest things vendors forget when trying to sell a customer on their backup software.

Second was the fact that, feature for feature, the top 5 traditional backup software products are not really that different from one another.  Sure, I do agree that some products have features that others don’t, and others products have features that work better than others, but in reality, the delta is so small and the workarounds are so simple it doesn’t really matter.  Unless your replacing traditional backup software with an evolutionary source based data deduplication software (which is only applicable for some environments) there is no advantage to switching software.

The challenge is if Data Protection is still one of the biggest and most expensive pain points within IT, how do the problems get resolved if replacing the software controlling it all is too costly to change?

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Real-time Compression “Meets Minimum”


IBM's Ed Walsh, Director of Storage Efficiency sits down with Steve Duplessie, Founder of ESG to talk about how IBM Real-time Compression sets the bar for doing storage optimization in NAS. At the end of the day, if you can do compression in real time, without sacrificing performance and the transparency of the implementation, then why wouldn't you - given the savings you can get over traditional compression.

We all know compression is not new and it is coming as a standard feature in a number of storage systems. The issue is, each of these technologies has a significant impact on performance - both primary storage performance as well as the performance on all of the back end operations such as backups, replication etc...

IBM's Real-time Compression doesn't have any of these limitations - listen to Ed to hear more.

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Key Competitive Advantages to IBM Real-time Compression


It still baffles me when there is so much information available for people to learn about any topic and it is not used.  Many times people just tend to rely on the information provided by their employer (which in many cases is just competitive FUD).  This video was the result of reading an email between IBM and one of their key partners on the competitive knowledge of each others products.

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Linked In Storage Discussion on Storage Efficiency


Great conversation on Linked In about deduplication and compression for storage efficiency in the Data Storage Professionals Group.  Help the storage community answer this question:

Does anyone has any experience in NAS de-duplication at filesystem level, like NetApps. Does it really work? I concerns/limitations?

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Top 10 Reasons Real-time Compression Provides Extraordinary Storage Efficiency


Over the past few weeks I have witnessed the proverbial mudslinging that takes place in the blogosphere when marketing feathers are ruffled.  Most recently I was reading Rich Anderson of The StorageSavvy Blog.  The article was "Compression better than Dedup?  NetApp Confirms!"

I have to agree with Rich on many fronts.  First, "When all you have is a hammer, everything is a nail."  Rich points out vendors have to sell "what's in the bag" so it is conceivable that all problems look like they can be solved with their solution.  If you look back over the last few years NTAP has always had a "me too" reputation.  Whatever the industry has, they have one too and its better.  For the last few years, while competing against Storwize, they have pulled the EMC tactic of trying to stall a market by saying, "We have optimization for primary storage with deduplication."   The reality is, you can't use it in real time, it is a resource hog, and again Rich mentions, the only use case it works well on in primary storage is VMware (and that is ONLY IF the customer stores their data outside the .vmdk file otherwise compression is much better).  Now that NTAP has compression their story has changed saying that compression on primary storage is better for most use cases.  Duh!  The folks at Storwize (now IBM Real-time Compression) have been saying that for years.  Why, deduplication is great for repetitive data sets, i.e. backup, not primary storage.  There just isn't that much repetitive data in primary storage.  Again, NTAP is trying to stall the market saying they have "in-line" compression for primary storage.  Sorry guys, not good enough.  In-line is NOT Real-time.  Rich also points out that the key characteristics of storage for customers are capacity and performance.  Patrick Rogers of NTAP has said publically that compression WILL indeed impact performance and that they even have a tool that will tell you how much performance will be impacted.  While NTAP may say compression is "free", we all know nothing worth having in life is free, you get what you pay for.  If you need the performance to do compression you are going to have to perform a major upgrade to  your filer in order to just be able to perform compression let alone try to do compression in real time.  No real savings there.

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The Storage Network


With the impending name change to the "Storwize" product, the marketing folks at the old "Storwize" are at it again with their "viral video" campaign.  Not sure how many of you have seen the movie or even the trailer to "The Social Network" that grossed $23M in the US brining it to #1 in the box office last week .  Its a story of a guy that started in college with an idea and turned it into something big.  Much like Storwize - an idea that started with only a few in Israel and has now been acquired by IBM for multi millions of dollars and will become a key part to IBM's overall "Storage Efficiency" strategy.  This new trailer "The Storage Network" highlights too may realities of today's data management issues.  Hope you enjoy it.

Video created by MediaBoss Studios

(BTW: In case you didn't get it Storwize is now IBM Real-time Compression)!

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A Blueprint for Primary Storage Optimization


During the past three to four months the storage industry has seen a spike in the number of reports, white papers and news articles surrounding the evolution of primary storage technology, capacity optimization (it is 2010’s Hottest Storage Technology).

The reason this technology is getting a lot of ‘air play’ these days is due to the fact that this technology is so critical to help control the growth and costs of storage.  In 2010 the EMC sponsored IDC Report The Digital Universe Decade - Are You Ready? was release and stated that:

  • In 2009, amid the “Great Recession,” the amount of digital information grew 62% over 2008 to 800 billion gigabytes (0.8 Zettabytes).
  • The amount of digital information created annually will grow by a factor of 44 from 2009 to 2020…

The folks at Wikibon also released an info graph that exposes the true explosion of data.

Information Explosion & Cloud Storage
Via: Wikibon

When you combine storage capacity (and the foot print it takes up) along with the power it takes to run it and cool it as well as the human resource it takes to manage it, you soon realize we cannot keep ‘just adding more cheap disk’ in an effort to manage the storage demands.  High Tech companies with high tech labs are also telling IT that ‘they are out of tricks’ when it comes to the ability to continue deliver disk drive that double capacity every 18 months.  It is for these reasons that primary storage optimization technologies have stepped into the ‘lime light’ as it serves as a means to help control the growth of primary storage including the foot print, power, cooling and man power required to manage it.

However, as we all know in IT, no two environments are the same and what may be good for one may not be good for another.  When looking at primary storage optimization there seem to be a number of available technologies and ways to deploy these technologies and the key question is what is right for ‘my’ environment.

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Marketing, FUD and Doing What You Do Best


Rather than leave a lengthy comment on Tom Cook’s blog post from Friday Compression and Dedupe: Business Value and Data Safety (and from a marketing perspective, Friday’s are bad days to post blogs – especially in the summer) – I thought I would respond here (this may get lengthy as Tom made a number of points which I need comment on).

The first thing I do want to say is that when doing technical marketing; the proper strategy would be to not be on defense but rather take an offensive approach.  However, given the amount of FUD that Tom put in his latest blog post, I have to defend compression to some degree.

Now, I think we can all agree that data compression and data deduplication are two technologies that can complement one another very well.  Avamar (EMC) deduplicates the data at the source and then compresses the data before sending it to the Avamar Data Store gaining tremendous efficiency in network utilization.  ProtecTIER (IBM) compresses the data once it is deduplicated at the target device before it stores the data.  Other solutions also combine compression and data deduplication.

I’d like to comment on some key point Tom made in his piece where he is just blatantly wrong:

1)      Compression identifies redundant data across a very small window, usually 64 KB. – While this may be true for other compression technologies, this is not true for Storwize.  Storwize performs compression where the initial window is not fixed in size at all; it is the resultant write that is fixed in size.  This size is also specifically mapped to the I/O patter of the data being written.  The goal is such that in 1 I/O Storwize can do all the work it needs to on a particular file or LUN and it is for this reason Storwize has no performance penalty.

2)      Compression produces data reduction rates at most 2X for most data types. – Seems Tom needs a lesson in the most common answer in IT – “IT DEPENDS”.  Data compression ratios are 100% tied to the data type.  For a true indication of data compression ratios see Figure 1.

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Gravity Applies to Everyone!


There was an interesting announcement today regarding Permabit who is now providing primary storage optimization through OEMs and having their solution embedded into the storage system.  This further drives home the point of where capacity optimization should live.  I do have a couple of questions however:

1)      What is the performance like?  I see phrases such as “High Performance Data Optimization Software” but don’t see any performance metrics – such as ‘no performance degradation’ for customers utilizing the solution.  Or testing metrics from their ‘partners’ (as it probably isn’t in production yet) – which brings up another question:

2)      Why were none of the ‘design win’ partners quoted in this announcement?

3)      Rehydration – Mr. Floyd states:

Permabit's Floyd claims Albireo can maintain data integrity because data written to disk isn't altered, and the reduction takes place out of the data path. When parallel processing is used, deduped data doesn't have to be rehydrated when it's accessed.

The question is – if it doesn’t need to be rehydrated, then how does the application read it?  I can only assume that Mr. Floyd means the data doesn’t have to be rehydrated on disk, which is fine, the question become: a) how does the application know what the data is? (Ocarina uses an agent to help them understand the data, but this is another thing to manage) and b) What is the performance of the system looking up all of the hash keys to reassemble the data on the fly, so how much more storage resources will this consume?

4)      Back to performance – Permabit states:

When done inline, data will flow to the Albireo library before going to disk. Post-process deduplication will write data to disk first, then scan and eliminate duplicated data. The parallel option sends data to disk while still in memory, and applies updates the same way as post-processing without having to read data off disk. Each method has different amounts of latency and reduction efficiencies.

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