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WordPress sent me an email with overall stats for 2010 and I thought I’d share a few things I noticed.

First, thank you to all of my readers as well as those who have linked to and otherwise shared my posts with others.  I know that many of my peer bloggers have much higher numbers than I, but I still think 22,000 views is pretty respectable.

For 2010, my most popular post was Resiliency vs Redundancy: Using VPLEX for SQL HA.  The top 5 posts are listed here..

1

Resiliency vs Redundancy: Using VPLEX for SQL HA June 2010

2

EMC CLARiiON and Celerra Updates – Defining Unified Storage May 2010
1 comment

3

NetApp and EMC: Real world comparisons October 2009
10 comments

4

While EMC users benefit from Replication Manager, NetApp users NEED SnapManager June 2010
25 comments

5

NetApp and EMC: Replication Management Tools Comparison June 2010
2 comments

You may notice a theme here.  First, Midrange Storage is HOT, and any comparisons between EMC and it’s competitors seem to get more attention compared to most other topics. Note #3 was written in 2009 and it’s the 3rd most viewed post on my blog in 2010. A secondary theme in these top 5 posts might be disaster recovery as well since most of these posts have DR concepts in the content as well.

Looking at search engine results the it looks like emc flare 30, clariion, and mirrorview network qos requirements were the hottest terms.  The MirrorView one is pretty specific so I may do some blogging on that topic in the future.

With these stats in mind, I’ll keep working to hone my blogging skills through 2011 and sharing as much real-world information as I can, especially as I work with my customers to implement solutions.  One thing I’ll do is try and provide the comparisons people seem to be interested in, but focusing on the advantages of products, while steering clear of negativity as much as possible.

Welcome to 2011!  It’s going to be fun!

My recent post about Compression vs Dedupe, which was sparked by Vaughn’s blog post about NetApp’s new compression feature, got me thinking more about the use of de-duplication and compression at the same time.  Can they work together?  What is the resulting effect on storage space savings?  What if we throw encryption of data into the mix as well?

What is Data De-Duplication?

De-duplication in the data storage context is a technology that finds duplicate patterns of data in chunks of blocks (sized from 4-128KB or so depending on implementation), stores each unique pattern only once, and uses reference pointers in order to reconstruct the original data when needed.  The net effect is a reduction in the amount of physical disk space consumed.

What is Data Compression?

Compression finds very small patterns in data (down to just a couple bytes or even bits at a time in some cases) and replaces those patterns with representative patterns that consume fewer bytes than the original pattern.  An extremely simple example would be replacing 1000 x “0”s with “0-1000”, reducing 1000 bytes to only 6.

Compression works on a more micro level, where de-duplication takes a slighty more macro view of the data.

What is Data Encryption?

In a very basic sense, encryption is a more advanced version of compression.  Rather than compare the original data to itself, encryption uses an input (a key) to compute new patterns from the original patterns, making the data impossible to understand if it is read without the matching key.

Encryption and Compression break De-Duplication

One of the interesting things about most compression and encryption algorithms is that if you run the same source data through an algorithm multiple times, the resulting encrypted/compressed data will be different each time.  This means that even if the source data has repeating patterns, the compressed and/or encrypted version of that data most likely does not.  So if you are using a technology that looks for repeating patterns of bytes in fairly large chunks 4-128KB, such as data de-duplication, compression and encryption both reduce the space savings significantly if not completely.

I see this problem a lot in backup environments with DataDomain customers.  When a customer encrypts or compresses the backup data before it gets through the backup application and into the DataDomain appliance, the space savings drops and many times the customer becomes frustrated by what they perceive as a failing technology.  A really common example is using Oracle RMAN or using SQL LightSpeed to compress database dumps prior to backing up with a traditional backup product (such as NetWorker or NetBackup).

Sure LightSpeed will compress the dump 95%, but every subsequent dump of the same database is unique data to a de-duplication engine and you will get little if any benefit from de-duplication.   If you leave the dump uncompressed, the de-duplication engine will find common patterns across multiple dumps and will usually achieve higher overall savings.  This gets even more important when you are trying to replicate backups over the WAN, since de-duplication also reduces replication traffic.

It all depends on the order

The truth is you CAN use de-duplication with compression, and even encryption.  They key is the order in which the data is processed by each algorithm.  Essentially, de-duplication must come first.  After data is processed by de-duplication, there is enough data in the resulting 4-128KB blocks to be compressed, and the resulting compressed data can be encrypted.  Similar to de-duplication, compression will have lackluster results with encrypted data, so encrypt last.

Original Data -> De-Dupe -> Compress -> Encrypt -> Store

There are good examples of this already;

EMC DataDomain – After incoming data has been de-duplicated, the DataDomain appliance compresses the blocks using a standard algorithm.  If you look at statistics on an average DDR appliance you’ll see 1.5-2X compression on top of the de-duplication savings.  DataDomain also offers an encryption option that encrypts the filesystem and does not affect the de-duplication or compression ratios achieved.

EMC Celerra NAS – Celerra De-Duplication combines single instance store with file level compression.  First, the Celerra hashes the files to find any duplicates, then removes the duplicates, replacing them with a pointer.  Then the remaining files are compressed.  If Celerra compressed the files first, the hash process would not be able to find duplicate files.

So what’s up with NetApp’s numbers?

Back to my earlier post on Dedupe vs. Compression; what is the deal with NetApp’s dedupe+compression numbers being mostly the same as with compression alone?  Well, I don’t know all of the details about the implementation of compression in ONTAP 8.0.1, but based on what I’ve been able to find, compression could be happening before de-duplication.  This would easily explain the storage savings graph that Vaughn provided in his blog.  Also, NetApp claims that ONTAP compression is inline, and we already know that ONTAP de-duplication is a post-process technology.  This suggests that compression is occurring during the initial writes, while de-duplication is coming along after the fact looking for duplicate 4KB blocks.  Maybe the de-duplication engine in ONTAP uncompresses the 4KB block before checking for duplicates but that would seem to increase CPU overhead on the filer unnecessarily.

Encryption before or after de-duplication/compression – What about compliance?

I make a recommendation here to encrypt data last, ie: after all data-reduction technologies have been applied.  However, the caveat is that for some customers, with some data, this is simply not possible.  If you must encrypt data end-to-end for compliance or business/national security reasons, then by all means, do it.  The unfortunate byproduct of that requirement is that you may get very little space savings on that data from de-duplication both in primary storage and in a backup environment.  This also affects WAN bandwidth when replicating since encrypted data is difficult to compress and accelerate as well.

The more I talk with customers, the more I find that the technical details of how something works is much less important than the business outcome it achieves.  When it comes to storage, most customers just want a device that will provide the capacity and performance they need, at a price they can afford–and it better not be too complicated.  Pretty much any vendor trying to sell something will attempt to make their solution fit your needs even if they really don’t have the right products.  It’s a fact of life, sell what you have.  Along these lines, there has been a lot of back and forth between vendors about dedup vs. compression technology and which one solves customer problems best.

After snapshots and thin provisioning, data reduction technology in storage arrays has become a big focus in storage efficiency lately; and there are two primary methods of data reduction — compression and deduplication.

While EMC has been marketing compression technology for block and file data in Celerra, Unified, and Clariion storage systems, NetApp has been marketing deduplication as the technology of choice for block and file storage savings.  But which one is the best choice?  The short answer is.. it depends.  Some data types benefit most from deduplication while others get better savings with compression.

Currently, EMC supports file compression on all EMC Celerra NS20, 40, 80, 120, 480, 960, VG2, and VG8 systems running DART 5.6.47.x+ and block compression on all CX4 based arrays running FLARE30.x+.  In all cases, compression is enabled on a volume/LUN level with a simple check box and processing can be paused, resumed, and disabled completely, uncompressing the data if desired.  Data is compressed out-of-band and has no impact on writes, with minimal overhead on reads.  Any or all LUN(s) and/or Filesystem(s) can be compressed if desired even if they existed prior to upgrading the array to newer code levels.

With the release of OnTap 8.0.1, NetApp has added support for in-line compression within their FAS arrays.  It is enabled per-FlexVol and as far as I have been able to determine, cannot be disabled later (I’m sure Vaughn or another NetApp representative will correct me if I’m wrong here.)  Compression requires 64-bit aggregates which are new in OnTap 8, so FlexVols that existed prior to an upgrade to 8.x cannot be compressed without a data migration which could be disruptive.  Since compression is inline, it creates overhead in the FAS controller and could impact performance of reads and writes to the data.

Vaughn Stewart, of NetApp, expertly blogged today about the new compression feature, including some of the caveats involved, and to me the most interesting part of the post was the following graphic he included showing the space savings of compression vs. dedup for various data types.

Image Credit: Vaughn Stewart, NetApp

The first thing that struck me was how much better compression performed over deduplication for all but one data type (Virtualization will usually fare well because in a typical environment there are many VMs with the same operating system files).  In fact, according to NetApp, deduplication achieves very little savings, if any, for the majority of the data types here.
 
The light green bar indicates savings with both dedupe AND compression enabled on the same dataset.  In 5 out of 9 cases, dedup adds ZERO savings over compression alone.  I can’t help but wonder why anyone would enable dedup on those data types if they already had compression, since both features use storage array CPU resources to find and compress or dedup data.  I am aware that in some cases, dedup can improve performance on NetApp systems due to dedup-aware cache, but I also believe that any performance gain is directly related to the amount of duplication in the data.  Using this chart, virtualization is really the only place where dedup seems particularly effective and hence the only place where real performance gains would likely present themselves.
 
The challenge for NetApp customers will be getting their data into a configuration that supports compression due to the 64-bit aggregate requirement, lack of an easy and non-disruptive LUN migration feature (DataMotion appears to only support iSCSI and NFS and requires several additional licenses), and no way to convert an aggregate from 32-bit to 64-bit.  Once compression has been enabled, if there is truly no way to disable it, any resulting performance impact will be very difficult to rectify.
 
On the other hand, any EMC customer with current maintenance can upgrade their NS or CX4 array to newer versions of DART or FLARE, and compression can be enabled on any existing data after the fact.  If performance becomes an issue for a particular dataset once compressed, the data can be uncompressed later.  Both operations are completely non-disruptive and run in the background.  While block compression only works on LUNs in a virtual pool, as opposed to a traditional RAID group, enabling compression on a normal LUN will automatically migrate the LUN into a virtual pool, perform zero-page reclaim, followed by compression, and the entire process is completely non-disruptive to the application.  Oh, and compressed data can still be tiered with FASTVP across SSD, FC, and SATA disk and/or benefit from up to 2TB of FASTCache.
 
I admit that there is a place for deduplication as well as compression in reducing the footprint of customer data.  However, based on what I’ve seen in my career as an IT professional, and with my customers in my current role at EMC, there are more use cases for compression than there are for deduplication when it comes to primary data, whether SAN or NAS.  Either way, if I was using a new technology for the first time on a particular data set, whether compression or deduplication, I would definitely want a backout plan in case the drawbacks outweight the benefits.

Apart from “The Cloud”, “Unified Storage” is the other big buzzword in the storage industry of late.  But what exactly is Unified Storage?

Mirriam-Webster defines unify as “to make into a unit or coherent whole

So how does this apply to storage systems?  If you look at marketing messages by EMC, NetApp, and other vendors you’ll find that they all use the term in different ways in order to fit nicely with the products they have.  Based on what I see, there are generally two different approaches.

Single HW/SW Stack Approach:

Some vendors want you to believe that the only way it can be called Unified Storage is if the same physical box and software stack provides all protocols and features, even if management of the single system is not perfectly cohesive.

NetApp’s FAS storage systems are an example of this strategy.  A single filer provides all services whether SAN or NAS, IP or FiberChannel.  However, a single HA cluster is actually managed as two separate systems, each cluster node is managed independently using independent FilerView instances and there are separate tools (NetApp System Manager, Operations Manager, Provisioning Manager, Protection Manager) that can bring all of the filer heads into one view.  Disks are captive to a specific filer head in a cluster and moving disks and/or volumes between filer heads is not seamless.

Single Point of Management Approach:

Others approach it more holistically and figure that as long as the customer manages it as a single system, it qualifies as “Unified”, even if there may be disparate hardware and software components providing the different services.  After all, once it’s installed you don’t really go in the datacenter to physically look at the hardware very often.

EMC’s Unified Storage (which is a combination of Celerra NAS and Clariion Block storage systems) is an example of this.  In a best-of-breed approach, EMC allows the Clariion backend to do what it does best, block storage via FC or IP, while the Celerra, which is purpose built for NAS, provides CIFS/NFS services while leveraging the disk capacity, processors, cache, and other features of the Clariion as a kind of offload engine.  Regardless of which services you use, all parts of the solution are managed from a single Unisphere instance, including other Clariions and/or Celerras in the environment.  Unisphere launches from any Clariion or Celerra management port, and regardless of which device you launch it from, all systems are manageable together.

Which approach is better?

I see advantages and disadvantages to both approaches, as a former admin of both NetApp and EMC storage, I feel that while NetApp’s hardware and software stack is unified, their management stack is decidedly un-unified.  EMC’s Unified storage is physically “integrated” to work together as a system, but the unifying feature is the management infrastructure built-in with Unisphere.

There are other advantages to EMCs approach as well.  For example, if a particular workload seems to hammer the CPUs on the NAS but the backend is not a bottleneck, more Celerra datamovers can be added to take advantage of the same backend disks and improve front end performance.  Likewise, the backend can be augmented as needed to improve performance, increase capacity, etc without having to scale up the front end NAS head.  With the NetApp approach, if your CPU or cache is stressed, you need to deploy more FAS systems (in pairs for HA) along with any required disks for that new system to store data.

Both approaches work, and both have their merits, but what do customers really want?

In my opinion, most customers don’t really care *how* the hardware works, so long as it DOES WORK, and is easy to manage.  In the grand scheme of things, if I, as an admin, can provision, replicate, snapshot, and clone storage across my entire environment, regardless of protocol,  from a “single pane of glass”, that is a strong positive.

EMC Unisphere makes it easy to do just that and it launches right from the array with no separate installation or servers required.  Unisphere can authenticate against Active Directory or LDAP and has role-based-administration built in.  And since Unisphere launches from any Clariion Storage processor or Celerra Control Station, there’s no single point of failure for storage management either.

So what do you think customers want?  If you are a customer, what do YOU want?

(Warning: This is a long post…)

You have a critical application that you can’t afford to lose:

So you want to replicate your critical applications because they are, well, critical.   And you are looking at the top midrange storage vendors for a solution.  NetApp touts awesome efficiency, awesome snapshots, etc while EMC is throwing considerable weight behind it’s 20% Efficiency Guarantee.  While EMC guarantees to be 20% more efficient in any unified storage solution, there is perhaps no better scenario than a replication solution to prove it.

I’m going to describe a real-world scenario using Microsoft Exchange as the example application and show why the EMC Unified platform requires less storage, and less WAN bandwidth for replication, while maintaining the same or better application availability vs. a NetApp FAS solution.  The example will use a single Microsoft Exchange 2007 SP2 server with ten 100GB mail databases connected via FibreChannel to the storage array.  A second storage array exists in a remote site connected via IP to the primary site and a standby Exchange server is attached to that array.

Basic Assumptions:

  • 100GB per database, 1 database per storage group, 1 storage group per LUN, 130GB LUNs
  • 50GB Log LUNs, ensure enough space for extra log creation during maintenance, etc
  • 10% change rate per day average
  • Nightly backup truncates logs as required
  • Best Practices followed by all vendors
  • 1500 users (Heavy Users 0.4IOPS), 10% of users leverage Blackberry (BES Server = 4X IOPS per user)
  • Approximate IOPS requirement for Exchange: 780IOPS for this server.
  • EMC Solution: 2 x EMC Unified Storage systems with SnapView/SANCopy and Replication Manager
  • NetApp Solution: 2 x NetApp FAS Storage systems with SnapMirror and SnapManager for Exchange
  • RPO: 4 hours (remote site replication update frequency)

Based on those assumptions we have 10 x 130GB DB LUNs and 10 x 50GB Log LUNs and we need approximately 780 host IOPS 50/50 read/write from the backend storage array.

Disk IOPS calculation: (50/50 read/write)

  • RAID10, 780 host IOPS translates to 1170 disk IOPS (r+w*2)
  • RAID5, 780 host IOPS translates to 1950 disk IOPS (r+w*4)
  • RAIDDP is essentially RAID6 so we have about 2730 disk IOPS (r + w*6)

Note: NetApp can create sequential stripes on writes to improve write performance for RAIDDP but that advantage drops significantly as the volumes fill up and free space becomes fragmented which is extremely likely to happen after a few months or less of activity.

Assuming 15K FiberChannel drives can make 180 IOPS with reasonable latencies for a database we’d need:

  • RAID10, Database 6.5 disks (round up to 8), using 450GB 15K drives =  1.7TB usable (1 x 4+4)
  • RAID5, 10.8 disks for RAID5 (round up to 12), using 300GB 15K drives = 2.8TB usable (2 x 5+1)
  • RAID6/DP, 15.1 disks for RAID6 (round up to 16), using 300GB 15K drives = 3.9TB usable (1 x 14+2)

Log writes are highly cachable so we generally need fewer disks; for both the RAID10 and RAID5 EMC options we’ll use a single RAID1 1+1 raid group with 2 x 600GB 15K drives.  Since we can’t do RAID1 or RAID10 on NetApp we’ll have to use at least 3 disks (1 data and 2 parity) for the 500GB worth of Log LUNs but we’ll actually need more than that.

Picking a RAID Configuration and Sizing for snapshots:

For EMC, the RAID10 solution uses fewer disks and provides the most appropriate amount of disk space for LUNs vs. the RAID5 solution.  With the NetApp solution there really isn’t another alternative so we’ll stick with the 16 disk RAID-DP config.  We have loads of free space but we need some of that for snapshots which we’ll see next.  We also need to allocate more space to the Log disks for those snapshots.

Since we expect about 10% change per day in the databases (about 10GB per database) we’ll double that to be safe and plan for 20GB of changes per day per LUN (DB and Log).

NetApp arrays store snapshot data in the same volume (FlexVol) as the application data/LUN so you need to size the FlexVol’s and Aggregates appropriately.  We need 200GB for the DB LUNs and 200GB for the Log LUNs to cover our daily change rate but we’re doubling that to 400GB each to cover our 2 day contingency.  In the case of the DB LUNs the aggregate has more than enough space for the 400GB of snapshot data we are planning for but we need to add 400GB to the Log aggregate as well so we need 4 x 600GB 15K drives to cover the Exchange logs and snapshot data.

EMC Unified arrays store snapshot data for all LUNs in centralized location called the Reserve LUN Pool or RLP.  The RLP actually consists of a number of LUNs that can be used and released as needed by snapshot operations occurring across the entire array.  The RLP LUNs can be created on any number of disks, using any RAID type to handle various IO loads and sizing an RLP is based on the total change rate of all simultaneously active snapshots across the array.  Since we need 400GB of space in the Reserve LUN Pool for one day of changes, we’ll again be safe by doubling that to 800GB which we’ll provide with 6 dedicated 300GB 15K drives in RAID10.

At this point we have 20 disks on the NetApp array and 16 disks on the EMC array.  We have loads of free space in the primary database aggregate on the NetApp but we can’t use that free space because it’s sized for the IOPS workload we expect from the Exchange server.

In order to replicate this data to an alternate site, we’ll configure the appropriate tools.

EMC:

  1. Install Replication Manager on a server and deploy an agent to each Exchange server
  2. Configure SANCopy connectivity between the two arrays over the IP ports built-in to each array
  3. In Replication Manager, Configure a job that quiesces Exchange, then uses SANCopy to incrementally update a copy of the database and log LUNs on the remote array and schedule for every 4 hours using RM’s built in scheduler.

NetApp:

  1. Install SnapManager for Exchange on each Exchange server
  2. Configure SnapMirror connectivity betweeen the two arrays over the IP ports built-in to each array
  3. In SnapManager, Configure a backup job that quiesces Exchange and takes a Snapshot of the Exchange DBs and Logs, then starts a SnapMirror session to replicate the updated FlexVol (including the snapshot) to the remote array.  Configure a schedule in Windows Task Manager to run the backup job every 4 hours.

Both the EMC and NetApp solutions run on schedule, create remote copies, and everything runs fine, until...

Tuesday night during the weekly maintenance window, the Exchange admins decide to migrate half of the users from DB1, to DB2 and DB3 and half of the users from DB4, to DB5 and DB6.  About 80GB of data is moved (25GB to each of the target DBs.)  The transactions logs on DB1 and DB4 jump to almost 50GB, 35GB each on DB2, DB3, DB5, and DB6.

On the NetApp array, the 50GB log LUNs already have about 10GB of snapshot data stored and as the migration is happening, new snapshot data is tracked on all 6 of the affected DB and Log LUNs.  The 25GB of new data plus the 10GB of existing data exceeds the 20GB of free space in the FlexVol that each LUN is contained in and guess what…  Exchange chokes because it can no longer write to the LUNs.

There are workarounds: First, you enable automatic volume expansion for the FlexVols and automatic Snapshot deletion as a secondary fallback.  In the above scenario, the 6 affected FlexVols autoextend to approximately 100GB each equaling 300GB of snapshot data for those 6 LUNs and another 40GB for the remaining 4 LUNs.  There is only 60GB free in the aggregate for any additional snapshot data across all 10 LUNs.  Now, SnapMirror struggles to update the 1200GB of new data (application data + snapshot data) across the WAN link and as it falls behind more data changes on the production LUNs increasing the amount of snapshot data and the aggregate runs out of space.  By default, SnapMirror snapshots are not included in the “automatically delete snapshots” option so Exchange goes down.  You can set a flag to allow SnapMirror owned snapshots to be automatically deleted but then you have to resync the databases from scratch.  In order to prevent this problem from ever occurring, you need to size the aggregate to handle >100% change meaning more disks.

Consider how the EMC array handles this same scenario using SANCopy.  The same changes occur to the databases and approximately 600GB of data is changed across 12 LUNs (6 DB and 6 Log).  When the Replication Manager job starts, SANCopy takes a new snapshot of all of the blocks that just changed for purposes of the current update and begins to copy those changed blocks across the WAN.

EMC Advantages:

  • SANCopy/Inc is not tracking the changes that occur AS they occur, only while an update is in process so the Reserve LUN Pool is actually empty before the update job starts.  If you want additional snapshots on top of the ones used for replication, that will increase the amount of data in the Reserve LUN Pool for tracking changes, but snapshots are created on both arrays independently and the snapshot data is NOT replicated.  This nuance allows you to have different snapshot schedules in production vs. disaster recovery for example.
  • Because SANCopy/Inc only replicates the blocks that have changed on the production LUNs, NOT the snapshot data, it copies only half of the data across the WAN vs SnapMirror which reduces the time out of sync.  This translates to lower WAN utilization AND a better RPO.
  • IF an update was occurring when the maintenance took place, the amount of data put in the Reserve LUN pool would be approximately 600GB (leaving 200GB free for more changed data).  More efficient use of the Snapshot pool and more flexibility.
  • IF the Reserve LUN Pool ran out of space, the SANCopy update would fail but the production LUNs ARE NEVER AFFECTED.  Higher availability for the critical application that you devoted time and money to replicate.
  • Less spinning disk on the EMC array vs. the NetApp.

EMC has several replication products available that each act differently.  I used SANCopy because, combined with Replication Manager, it provides similar functionality to NetApp SnapMirror and SnapManager.  MirrorView/Async has the same advantages as SANCopy/Incremental in these scenarios and can replicate Exchange, SQL, and other applications without any host involvement.

Higher Application availability, lower WAN Utilization , Better RPO, Fewer Spinning Disks, without even leveraging advanced features for even better efficiency and performance.

Yesterday, In his blog posted entitled “Myth Busting: Storage Guarantees“, Vaughn Stewart from NetApp blogged about the EMC 20% Guarantee and posted a chart of storage efficiency features from EMC and NetApp platforms to illustrate his point.  Chuck Hollis from EMC called it “chartsmithing” in comment but didn’t elaborate specifically on the charts deficiencies.  Well allow me to take that ball…

As presented, Vaughn’s chart (below) is technically factual (with one exception which I’ll note), but it plays on the human emotion of Good vs Bad (Green vs Red) by attempting to show more Red on EMC products than there should be.

The first and biggest problem is the chart compares EMC Symmetrix and EMC Clariion dedicated-block storage arrays with NetApp FAS, EMC Celerra, and NetApp vSeries which are all Unified storage systems or gateways.  Rather than put n/a or leave the field blank for NAS features on the block-only arrays, the chart shows a resounding and red NO, leading the reader to assume that the feature should be there but somehow EMC left it out.

As far as keeping things factual, some of the EMC and NetApp features in this chart are not necessarily shipping today (very soon though, and since it affects both vendors I’ll allow it here).  And I must make a correction with respect to EMC Symmetrix and Space Reclamation, which IS available on Symm today.

I’ve taken the liberty of massaging Vaughn’s chart to provide a more balanced view of the feature comparison.  I’ve also added EMC Celerra gateway on Symmetrix to the comparison as well as an additional data point which I felt was important to include.

I’ve included some footnotes in the chart to explain some of the results but I’ll explain a little here as well.

1.) I removed the block only EMC configuration devices because the NetApp devices in the comparison are Unified systems.

2.) I removed the SAN data row for Single Instance storage because Single Instance (identical file) data reduction technology is inherently NAS related.

3.) Zero Space Reclamation is a feature available in Symmetrix storage.  In Clariion, the Compression feature can provide a similar result since zero pages are compressible.

I left the 3 different data reduction techniques as individually listed even though the goal of all of them is to save disk space.  Depending on the data types, each method has strengths and weaknesses.

One question, if a bug in OnTap causes a vSeries to lose access to the disk on a Symmetrix during an online Enginuity upgrade, who do you call?  How would you know ahead of time if EMC hasn’t validated vSeries on Symmetrix like EMC does with many other operating systems/hosts/applications in eLab?

The goal if my post here really is to show how the same data can be presented in different ways to give readers a different impression.  I won’t get into too much as far as technical differences between the products, like how comparing FAS to Symmetrix is like comparing a box truck to a freight train, or how fronting an N+1 loosely coupled clustered, global cached, high-end storage array with a midrange dual-controller gateway for block data might not be in a customer’s best interest.

What do you think?

This is a follow up to my recent post NetApp and EMC: Replication Management Tools Comparison, in which I discussed the differences between EMC Replication Manager and NetApp SnapManager.

————

As a former customer of both NetApp and EMC, and now as an employee of EMC, I noticed a big difference between NetApp and EMC as far as marketing their replication management tools. As a customer, EMC talked about Replication Manager several times and we purchased it and deployed it. NetApp made SnapManager a very central part of their sales campaign, sometimes skipping any discussion of the underlying storage in favor of showing off SnapManager functionality. This is an extremely effective sales technique and NetApp sales teams are so good at this that many people don’t even realize that other vendors have similar, and in my opinion EMC has better, functionality.  One of the reasons for this difference in marketing strategy is that NetApp users NEED SnapManager, while EMC users do not always need Replication Manager.

The reason why is both simple and complex…

EMC storage arrays (Clariion, Symmetrix, RecoverPoint, Invista) all have one technology in common that NetApp Filers do not–Consistency Groups. A consistency group allows the storage system to take a snapshot of multiple LUNs simultaneously, so simultaneous in fact that all of the snapshots are at the exact same point in time down to the individual write. This means that, without taking any applications offline and without any orchestration software, EMC storage arrays can create crash-consistent copies of nearly any kind of data at any time.

The EMC Whitepaper “EMC CLARiiON Database Storage Solutions: Oracle 10g/11g with CLARiiON Storage Replication Consistency” downloadable from EMC’s website has the following explanation of consistency groups in general…

“…Consistent replication operates on multiple LUNs as a set such that if the replication action fails for one member in the set, replication for all other members of the set are canceled or stopped.  Thus the contents of all replicated LUNs in the set are guaranteed to be identical point-in-time replicas of their source and dependent-write consistency is maintained…”

“…With consistent replication, the database does not have to be shut down or put into “hot backup mode.”  Replicates created with SnapView or MV/S (or MV/A, Timefinder, SRDF, Recoverpoint, etc) consistency operations, without first quiescing or halting the application, are restartable point-in-time replicas of the production data and guaranteed to be dependent-write consistent.”

Consistency is important for any application that is writing to multiple LUNs at the same time such as SQL database and log volumes. SnapManager and Replication Manager actually prepare the application by quiescing the database during the snapshot creation process. This process creates “application-consistent” copies which are technically better for recovery compared with “storage-consistent” copies (also known as crash-consistent copies).

So, while I will acknowledge that quiescing the database during a snapshot/replication operation provides the best possible recovery image, that may not be realistic in some scenarios.  The first issue is that the actual operation of quiescing, snapping, checking the image, then pushing an update to a remote storage array takes some time.  Depending on the size of the dataset, this operation can take from several minutes to several hours to complete.  If you have a Recovery Point Objective (RPO) of 5 minutes or less, using either of these tools is pretty much a non-starter.

Another issue is one of application support.  EMC Replication Manager and NetApp SnapManager have very wide support for the most popular operating systems, filesystems, databases, and applications, they certainly don’t support every application.  A very simple example is a Novell Netware file server with a NSS pool/volume spanning multiple LUNs.  Neither NetApp nor EMC have support for Novell Netware in their replication management tools.  While you can certainly replicate all of the LUNs with NetApp SnapManager, SnapManager has no consistency technology built-in to keep the LUNs write-order consistent.  The secondary copy will appear completely corrupt to the Netware server if a recovery is attempted.  Through the use of consistency groups with MirrorView/Async, the replication of each LUN is tracked as a group and all of the LUNs are write-order consistent with each other, keeping the filesystem itself consistent.  You would need to have either array-level consistency technology, or support for Netware in the replication management tool in order to replication such a server..  Unfortunately, NetApp provides neither.

You may have complex applications that consist of Oracle and SQL databases, NTFS filesystems, and application servers running as VMs.  Using array-based consistency groups, you can replicate all of these components simultaneously and keep them all consistent with each other.  This way you won’t have transactions that normally affect two databases end up missing in one of the two after a recovery operation, even if those databases are different technologies (Oracle and MySQL, or PostgreSQL for example).

EMC Storage arrays provide consistency group technology for Snapshots and Replication in Clariion and Symmetrix storage arrays.  In fact, with Symmetrix, consistency groups can span multiple arrays without any host software.  By comparison, NetApp Filers do not have consistency group technology in the array.  Snapshots are taken (for local replicas and for SnapMirror) at the FlexVolume level.  Two FlexVolumes cannot be snapped consistently with each other without SnapManager.

There are a couple workarounds for NetApp users–you can snapshot an aggregate, but that is not recommended by NetApp for most customers, or you can put multiple LUNs in the same FlexVol, but that still limits you to 16TB of data including snapshot reserve space, and both options violate best practices for database designs of keeping data and logs in separate spindles for recovery.  Even with these workarounds, you cannot gain LUN consistency across the two controllers in an HA Filer pair, something the CLARiiON does natively, and can help for load balancing IO across the storage processors.

In general, I recommend that EMC customers use EMC Replication Manager and NetApp customers use SnapManager for the applications that are supported, and for most scenarios.  But when RPO’s are short, or the environment falls outside the support matrix for those tools, consistency groups become the best or only option.

Incidentally, with EMC RecoverPoint, you get the best of both worlds.  CDP or near-CDP replication of data using consistency groups for zero or near-zero RPOs plus application-consistent bookmarks made anytime the database is quiesced.  Recovery is done from the up-to-the-second version of the data, but if that data is not good for any reason, you can roll back to another point in time, including a point-in-time when the database was quiesced (a bookmark).

So, while EMC has, in Replication Manager, an equivalent offering to NetApp’s SnapManager, EMC customers are not required to use it, and in some cases they can achieve better results using array-based consistency technologies.

I started this post before I started working for EMC and got sidetracked with other topics.  Recent discussions I’ve had with people have got me thinking more about orchestration of data protection, replication, and disaster recovery, so it was time to finish this one up…

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Prior to me coming to work for EMC, I was working on a project to leverage NetApp and EMC storage simultaneously for redundancy.  I had a chance to put various tools from EMC and NetApp into production and have been able to make some observations with respect to some of the differences.  This is a follow up my previous NetApp and EMC posts…

NetApp and EMC: Real world comparisons
NetApp and EMC: Startup and First Impressions
NetApp and EMC: ESX and Exchange 2007 CCR
NetApp and EMC: Exchange 2007 Replication

Specifically this post is a comparison between NetApp SnapManager 5.x and EMC Replication Manager 5.x.  First, here’s a quick background on both tools based on my personal experience using them.

Description

EMC Replication Manager (RM) is a single application that runs on a dedicated “Replication Manager Server.”  RM agents are deployed to the hosts of applications that will be replicated.  RM supports local and remote replication features in EMC’s Clariion storage array, Celerra Unified NAS, Symmetrix DMX/V-Max, Invista, and RecoverPoint products.  With a single interface, Replication Manager lets you schedule, modify, and monitor snapshot, clone, and replication jobs for Exchange, SQL, Oracle, Sharepoint, VMWare, Hyper-V, etc.  RM supports Role-Based authentication so application owners can have access to jobs for their own applications for monitoring and managing replication.  RM can manage jobs across all of the supported applications, array types, and replication technologies simultaneously.  RM is licensed by storage array type and host count. No specific license is required to support the various applications.

NetApp SnapManager is actually a series of applications designed for each application that NetApp supports.  There are versions of SnapManager for Exchange, SQL, Sharepoint, SAP, Oracle, VMWare, and Hyper-V.  The SnapManager application is installed on each host of an application that will be replicated, and jobs are scheduled on each specific host using Windows Task Scheduler.  Each version of SnapManager is licensed by application and host count.  I believe you can also license SnapManager per-array instead of per-host which could make financial sense if you have lots of hosts.

Commonality

EMC Replication Manager and NetApp SnapManager products tackle the same customer problem–provide guaranteed recoverability of an application, in the primary or a secondary datacenter, using array-based replication technologies.  Both products leverage array-based snapshot and replication technology while layering application-consistency intelligence to perform their duties.  In general, they automate local and remote protection of data.  Both applications have extensive CLI support for those that want that.

Differences

  • Deployment
    • EMC RM – Replication Manager is a client-server application installed on a control server.  Agents are deployed to the protected servers.
    • NetApp SM – SnapManager is several applications that are installed directly on the servers that host applications being protected.
  • Job Management
    • EMC RM – All job creation, management, and monitoring is done from the central GUI. Replication Manager has a Java based GUI.
    • NetApp SM – Job creation and monitoring is done via the SnapManager GUI on the server being protected.  SnapManager utilizes an MMC based GUI.
  • Job Scheduling
    • EMC RM – Replication Manager has a central scheduler built-in to the product that runs on the RM Server.  Jobs are initiated and controlled by the RM Server, the agent on the protected server performs necessary tasks as required.
    • NetApp SM – SnapManager jobs are scheduled with Windows Task Scheduler after creation.  The SnapManager GUI creates the initial scheduled task when a job is created through the wizard.  Modifications are made by editing the scheduled task in Windows task scheduler.

So while the tools essentially perform the same function, you can see that there are clear architectural differences, and that’s where the rubber meets the road.  Being a centrally managed client-server application, EMC Replication Manager has advantages for many customers.

Simple Comparison Example: Exchange 2007 CCR cluster
(snapshot and replicate one of the two copies of Exchange data)

With NetApp SnapManager, the application is installed on both cluster nodes, then an administrator must log on to the console on the node that hosts the copy you want to replicate, and create two jobs which run on the same schedule.  Job A is configured to run when the node is the active node, Job B is configured to run when the node is passive.  Due to some of the differences in the settings, I was unable to configure a single job that ran successfully regardless of whether the node was active or passive.  If you want to modify the settings, you either have to edit the command line options in the Scheduled Task, or create a new job from scratch and delete the old one.

With EMC Replication Manager, you deploy the agent to both cluster nodes, then in the RM GUI, create a job against the cluster virtual name, not the individual node.  You define which server you want the job to run on in the cluster, and whether the job should run when the node is passive, active, or both.  All logs, monitoring, and scheduling is done in the same RM GUI, even if you have 50 Exchange clusters, or SQL and Oracle for that matter.  Modifying the job is done by right-clicking on the job and editing the properties.  Modifying the schedule is done in the same way.

So as the number of servers and clusters increases in your environment, having a central UI to manage and monitor all jobs across the enterprise really helps.  But here’s where having a centrally managed application really shines…

But what if it gets complicated?

Let’s say you have a multi-tier application like IBM FileNet, EMC Documentum, or OpenText and you need to replicate multiple servers, multiple databases, and multiple file systems that are all related to that single application.  Not only does EMC Replication Manager support SQL and Filesystems in the same GUI, you can tie the jobs together and make them dependent on each other for both failure reporting and scheduling.  For example, you can snapshot a database and a filesystem, then replicate both of them without worrying about how long the first job takes to complete.  Jobs can start other jobs on completely independent systems as necessary.

Without this job dependence functionality, you’d generally have to create scheduled tasks on each server and have dependent jobs start with a delay that is long enough to allow the first job to complete while as short as possible to prevent the two parts of the application from getting too far out of sync.  Some times the first job takes longer than usual causing subsequent jobs to complete incorrectly.  This is where Replication Manager shows it’s muscle with it’s ability to orchestrate complex data protection strategies, across the entire enterprise, with your choice of protection technologies (CDP, Snapshot, Clone, Bulk Copy, Async, Sync) from a single central user interface.

Well, not exactly.  What you really need is a restore solution!

I was discussing this with a colleague recently as we compared difficulties multiple customers are having with backups in general.  My colleague was relating a discussion he had with his customer where he told them, “stop thinking about how to design a backup solution, and start thinking about how to design a restore solution!”

Most of our customers are in the same boat, they work really hard to make sure that their data is backed up within some window of time, and offsite as soon as possible in order to ensure protection in the event of a catastrophic failure.  What I’ve noticed in my previous positions in IT and more so now as a technical consultant with EMC is that (in my experience) most people don’t really think about how that data is going to get restored when it is needed.  There are a few reasons for this:

  • Backing up data is the prerequisite for a restore; IT professionals need to get backups done, regardless of whether they need to restore the data.  It’s difficult to plan for theoretical needs and restore is still viewed, incorrectly, as theoretical.
  • Backup throughput and duration is easily measured on a daily basis, restores occur much more rarely and are not normally reported on.
  • Traditional backup has been done largely the same way for a long time and most customers follow the same model of nightly backups (weekly full, daily incremental) to disk and/or tape, shipping tape offsite to Iron Mountain or similar.

I think storage vendors, EMC and NetApp particularly, are very good at pointing out the distinction between a backup solution and a restore solution, where backup vendors are not quite as good at this.  So what is the difference?

When designing a backup solution the following factors are commonly considered:

  • Size of Protected Data – How much data do I have to protect with backup (usually GB or TB)
  • Backup Window – How much time do I have each night to complete the backups (in hours)
  • Backup Throughput – How fast can I move the data from it’s normally location to the backup target
  • Applications – What special applications do I have to integrate with (Exchange, Oracle, VMWare)
  • Retention Policy – How long do I have to hang on to the backups for policy or legal purposes
  • Offsite storage – How do I get the data stored at some other location in case of fire or other disaster

If you look at it from a restore prospective, you might think about the following:

  • How long can I afford to be down after a failure?  Recovery Time Objective (RTO): This will determine the required restore speed.  If all backups are stored offsite, the time to recall a tape or copy data across the WAN affects this as well.
  • How much data can I afford to lose if I have to restore? Recovery Point Objective (RPO):  This will determine how often the backup must occur, and in many cases this is less than 24 hours.
  • Where do I need to restore the application? This will help in determining where to send the data offsite.

Answer these questions first and you may find that a traditional backup solution is not going to fulfill your requirements.  You may need to look at other technologies, like Snapshots, Clones, replication, CDP, etc.  If a backup takes 8 hours, the restore of that data will most likely take at least 8 hours, if not closer to 16 hours.  If you are talking about a highly transactional database, hosting customer facing web sites, and processing millions of dollars per hour, 8 hours of downtime for a restore is going to cost you tens or hundreds of millions of dollars in lost revenue.

Two of my customers have database instances hosted on EMC storage, for example, which are in the 20TB size range.  They’ve each architected a backup solution that can get that 20TB database backed up within their backup window.  The problem is, once that backup completes, they still have to offsite the backup, and replicate it to their DR site across a relatively small WAN link.  They both use compressed database dumps for backup because, from the DBA’s perspective, dumps are the easiest type of backup to restore from, and the compression helps get 20TB of data pushed across 1gbe Ethernet connections to the backup server.  One of the customers is actually backing up all of their data to DataDomain deduplication appliances already; the other is planning to deploy DataDomain.  The problem in both cases is that, if you pre-compress the backup data, you break deduplication, and you get no benefit from the DataDomain appliance vs. traditional disk.  Turning off compression in the dump can’t be done because the backup would take longer than the backup window allows.  The answer here is to step back, think about the problem you are trying to solve–restoring data as quickly as possible in the event of failure–and design for that problem.

How might these customers leverage what they already have, while designing a restore solution to meet their needs?

Since they are already using EMC storage, the first step would be to start taking snapshots and/or clones of the database.  These snapshots can be used for multiple purposes…

  • In the event of database corruption, or other host/filesystem/application level problem, the production volume can be reverted to a snapshot in a matter of minutes regardless of the size of the database (better RTO).  Snapshots can be taken many times a day to reduce the amount of data loss incurred in the event of a restore (better RPO).
  • A snapshot copy of the database can be mounted to a backup server directly and backed up directly to tape or backup disk.  This eliminates the requirement to perform database dumps at all as well as any network bottleneck between the database server and backup server.  Since there is no dump process, and no requirement to pre-compress the data, de-duplication (via DataDomain) can be employed most efficiently.  Using a small 10gbps private network between the backup media servers and DataDomain appliances, in conjunction with DD-BOOST, throughput can be 2.5X faster than with CIFS, NFS, or VTL to the same DataDomain appliance.  And with de-duplication being leveraged, retention can be very long since each day’s backup only adds a small amount of new data to the DataDomain.
  • Now that we’ve improved local restore RTO/RPO, eliminated the backup window entirely for the database server, and decreased the amount of disk required for backup retention, we can replicate the backup to another DataDomain appliance at the DR site.  Since we are taking full advantage of de-duplication now, the replication bandwidth required is greatly reduced and we can offsite the backup data in a much shorter period of time.
  • Next, we give the DBAs back the ability to restore databases easily, and at will, by leveraging EMC Replication Manager.  RM manages the snapshot schedules, mounting of snaps to the backup server, and initiation of backup jobs from the snapshot, all in a single GUI that storage admins and DBAs can access simultaneously.

So we leveraged the backup application they already own, the DataDomain appliances they already own, storage arrays they already own, built a small high-bandwidth backup network, and layered some additional functionality, to drastically improve their ability to restore critical data.  The very next time they have a data integrity problem that requires a restore, these customer’s will save literally millions of dollars due to their ability to restore in minutes vs. hours.

If RPO’s of a few hours are not acceptable, then a Continuous Data Protection (CDP) solution could be added to this environment.  EMC RecoverPoint CDP can journal all database activity to be used to restore to any point in time, bringing data loss (RPO) to zero or near-zero, something no amount of snapshots can provide, and keeping restore time (RTO) within minutes (like snapshots).  Further, the journaled copy of the database can be stored on a different storage array providing complete protection for the entire hardware/software stack.  RecoverPoint CDP can be combined with Continuous Remote Replication (CRR) to replicate the journaled data to the DR site and provide near-zero RPO and extremely low RTO in a DR/BC scenario.  Backups could be transitioned to the DR site leveraging the RecoverPoint CRR copies to reduce or eliminate the need to replicate backup data.  EMC Replication Manager manages RecoverPoint jobs in the same easy to use GUI as snapshot and clone jobs.

There are a whole host of options available from EMC (and other storage vendors) to protect AND restore data in ways that traditional backup applications cannot match.  This does not mean that backup software is not also needed, as it usually ends up being a combined solution.

The key to architecting a restore solution is to start thinking about what would happen if you had to restore data, how that impacts the business and the bottom line, and then architect a solution that addresses the business’ need to run uninterrupted, rather than a solution that is focused on getting backups done in some arbitrary daily/nightly window.

I’ve been having some fun discussions with one of my customers recently about how to tackle various application problems within the storage environment and it got me thinking about the value of having “options”.  This customer has an EMC Celerra Unified Storage Array that has Fiber Channel, iSCSI, NFS, and CIFS protocols enabled.  This single storage system supports VMWare, SQL, Web, Business Intelligence, and many custom applications.

The discussion was specifically centered on ensuring adequate storage performance for several different applications, each with a different type of workload…

1.)  Web Servers – Primarily VMs with general-purpose IO loads and low write ratios.

2.)  SQL Servers – Physical and Virtual machines with 30-40% write ratios and low latency requirements.

3.)  Custom Application  – A custom application database with 100% random read profiles running across 50 servers.

The EMC Unified solution:

EMC Storage already sports virtual provisioning in order to provision LUNs from large pools of disk to improve overall performance and reduce complexity.  In addition, QoS features in the array can be used to provide guaranteed levels of performance for specific datasets by specifying minimum and maximum bandwidth, response time, and IO requirements on a per-LUN basis.  This can help alleviate disk contention when many LUNs share the same disks, as in a virtual pool.  Enterprise Flash Drives (EFD) are also available for EMC Storage arrays to provide extremely high performance to applications that require it and they can coexist with FC and SATA drives in the same array.  Read and write cache can also be tuned at an array and LUN level to help with specific workloads.  With the updates to the EMC Unified Platform that I discussed previously, Sub-LUN FAST (auto tiering), and FAST Cache (EFD used as array cache) will be available to existing customers after a simple, non-disruptive, microcode upgrade, providing two new ways to tackle these issues.

So which feature should my customer use to address their 3 different applications?

Sub-LUN FAST (Fully Automated Storage Tiering)

Put all of the data into large Virtual Provisioning pools on the array, add a few EFD (SSD) and SATA disks to the mix and enable FAST to automatically move the blocks to the appropriate tier of storage.  Over time the workload would even out across the various tiers and performance would increase for all of the workloads with much fewer drives, saving on power, floor space, cooling, and potentially disk cost depending on the configuration.  This happens non-disruptively in the background.  Seems like a no-brainer right?

For this customer, FAST helps the web server VMs and the general-purpose SQL databases where the workload is predominately read and much of the same data is being accessed repeatedly (high locality of reference).   As long as the blocks being accessed most often are generally the same, day-to-day, automated tiering (FAST) is a great solution.  But what if the workload is much more random?  FAST would want to push all of the data into EFD, which generally wouldn’t be possible due to capacity requirements.  Okay, so tiering won’t solve all of their problems.  What about FAST Cache?

FAST Cache

Exponentially increase the size of the storage array’s read AND write cache with EFD (SSD) disks.  This would improve performance across the entire array for all “cache friendly” applications.

For this customer, increasing the size of write cache definitely helps performance for SQL (50% increase in TPM, 50% better response time as an example) but what about their custom database that is 100% random read?  Increasing the size of read cache will help get more data into cache and reduce the need to go to disk for reads, but the more random the data, the less useful cache is.   Okay, so very large caches won’t solve all of their problems.   EFDs must be the answer right?

EFD Disks

Forget SATA and FC disks; just use EFD for everything and it will be super fast!!   EFD has extremely high random read/write performance, low latency at high loads, and very high bandwidth.  You will even save money on power and cooling.

The total amount of data this customer is dealing with in these three applications alone exceeds 20TB.  To store that much in EFD would be cost prohibitive to say the least.  So, while EFD can solve all of this customer’s technical problems, they couldn’t afford to acquire enough EFD for the capacity requirements.

But wait, it’s not OR, it’s AND

The beauty of the EMC Unified solution is that you can use all of these technologies, together, on the same array, simultaneously.

In this customer’s case, we put FC and SATA into a virtual pool with FAST enabled and provision the web and general-purpose SQL servers from it.  FAST will eventually migrate the least used blocks to SATA, freeing the FC disks for the more demanding blocks.

Next, we extend the array cache using a couple EFDs and FAST Cache to help with random read, sequential pre-fetching, and bursty writes across the whole array.

Finally, for the custom 100% random read database, we dedicate a few EFDs to just that application, snapshot the DB and present copies to each server.  We disable read and write cache for the EFD backed volumes which leaves more cache available to the rest of the applications on the array, further improving total system performance.

Now, if and when the customer starts to see disk contention in the virtual pool that might affect performance of the general-purpose SQL databases, QoS can be tuned to ensure low response times on just the SQL volumes ensuring consistent performance.  If the disks become saturated to the point where QoS cannot maintain the response time or the other LUNs are suffering from load generated by SQL, any of the volumes can be migrated (non-disruptively) to a different virtual pool in the array to reduce disk contention.

Options

If you look at offerings from the various storage vendors, many promote large virtual pools, some also promote large caches of some kind, others promote block level tiering, and a few promote EFD (aka SSDs) to solve performance problems.  But, when you are consolidating multiple workloads into a single platform, you will discover that there are weaknesses in every one of those features and you are going to wish you had the option to use most or all of those features together.

You have that option on EMC Unified.

“The opinions expressed here are my personal opinions. Content published here is not read or approved in advance by my Employer (EMC) and does not necessarily reflect the views and opinions of EMC nor does it constitute any official communication of EMC.”

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