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Does your Building Block need a Fabric? <- Part 6
Okay, so this is all well and good, but you have been reading these posts and thinking that your environment is nowhere near the size of my example so Building Blocks are not for you. The fact is you can make individual Building Blocks quite a bit smaller or larger than the example I used in these posts and I’ll use a couple more quick examples to illustrate.
Small Environment: In this example, we’ll break down a 150 VM environment into three Building Blocks to provide the availability benefit of multiple isolated blocks. Additional Building Blocks can be deployed as the environment grows.
150 Total VMs deployed over 12 months
(2 vCPUs/32GB Disk/1GB RAM/25 IOPS per VM)
- 300 vCPUs
- 150GB RAM
- 4800 GB Disk Space
- 3750 Host IOPS
Assuming 3 Building Blocks, each Building Block would look something like this:
- 50 VMs per Building Block
- 2 x Dual CPU – 6 Core Servers (Maintains the 4:1 vCPU to Physical thread ratio)
- 24-32GB RAM per server
- 19 x 300GB 10K disks in RAID10 (including spares) — any VNXe or VNX model will be fine for this
- >1600GB Usable disk space (this disk config provides more disk space and performance than required)
- >1250 Host IOPS
Very Large Environment: In this example, we’ll scale up to 45,000 VMs using sixteen Building Blocks to provide the availability benefit of multiple isolated blocks. Additional Building Blocks can be deployed as the environment grows.
45000 Total VMs deployed over 48 months
(2 vCPUs/32GB Disk/4GB RAM/50 IOPS per VM)
- 90000 vCPUs
- 180,000 GB RAM
- 1,440,000 GB Disk Space
- 2,250,000 Host IOPS
Assuming 4 Building blocks per year, each Building Block would look something like this:
- 2812 VMs per Building Block
- 18 x Quad CPU – 10 Core Servera plus Hyperthreading (Maintains the 4:1 vCPU to Physical thread ratio)
- 640GB Ram per server
- 1216 x 300GB 15K disks in RAID10 (including spares) — one EMC Symmetrix VMAX for each Building Block
- >90000GB Usable disk space (the 300GB disks are the smallest available but still too big and will provide quite a bit more space than the 90TB required. This would be a good candidate for EMC FASTVP sub-LUN tiering along with a few SSD disks, which would likely reduce the overall cost)
- >140,000 Host IOPS
Hopefully this series of posts have shown that the Building Block approach is very flexible and can be adapted to fit a variety of different environments. Customers with environments ranging from very small to very large can tune individual Building Block designs for their needs to gain the advantages of isolated, repeatable deployments, and better long term use of capital.
Finally, if you find the benefits of the Building Block approach appealing, but would rather not deal with the integration of each Building Block, talk with a VCE representative about VBlock which provides all of the benefits I’ve discussed but in a pre-integrated, plug-and-play product with a single support organization supporting the entire solution.
Does your Building Block need a Fabric? <- Part 6
You may have noticed in the last installment that I did not include any FibreChannel switches in the example BOM. There are essentially three ways to deal with the SAN connectivity in a Building Block and there are advantages as well as disadvantages to each. (Note: this applies to iSCSI as well)
1.) Use switches that already exist in your datacenter: You can attach each storage array and each server back to a common fabric that you already have (or that you build as part of the project) and zone each of the Building Block’s servers to their respective storage array.
- Leverage any existing fabric equipment to reduce costs and centralize management
- Allow for additional servers to be added to each Building Block in the future
- Allow for presenting storage from one Building Block to servers in a different Building Block (useful for migrations)
- Increases complexity – Requires you to configure zoning within each Building Block during deployment
- Increases chances for human error that could cause an outage – Accidentally deleting entire Zonesets or VSANs is not as uncommon as you might think
- Reduces the availability isolation between Building Blocks – The fabric itself becomes a point-of-failure common to all Building Blocks.
2.) Deploy a dedicated fabric within each Building Block: Since each Building Block has a known quantity of storage and server ports, you can easily add a dual-switch/fabric into the design. In our example of 9 hosts you’d need a total of 18 ports for hosts and maybe 8 ports for the storage array for a combined total of 26 switch ports. Two 16-port switches can easily accommodate that requirement.
- Depending on the switches used, it could allow for additional servers in each Building Block in the future
- Allow for presenting storage from one Building Block to servers in a different building block (useful for migrations) by connecting ISLs between Building Blocks
- Maintains the Building Block isolation by not sharing the fabric switches across Building Blocks.
- Increases complexity – Requires you to configure zoning within each Building Block during deployment
- Increases chances for human error that could cause an outage – Again, accidentally deleting entire Zonesets or VSANs is not as uncommon as you might think
3.) Dispense with the fabric entirely: Since Building Blocks are relatively small, resulting in fewer total initiator/target pairs, it’s possible in some cases to directly attach all of the hosts to the storage array. In our example, the nine hosts need eighteen ports and the VNX5700 supports up to twenty four FC ports. This means you can directly attach all of the hosts to the array and still have six remaining ports on the array for replication, etc. Different arrays from EMC as well as other vendors will have various limits on the number of FC ports supported. Also, not all vendors support direct attached hosts so you’ll need to check that with your storage vendor of choice to be sure.
- Maintains the Building Block isolation by not sharing the fabric switches across Building Blocks.
- Simplifies deployment by eliminating the need to do any zoning at all and effectively eliminates any port queue limits (HBA elevator depth settings)
- Simplifies troubleshooting by eliminating the fabric (buffer to buffer credits, bandwidth, port errors, etc) from the IO path.
- Limits the number of hosts per Building Block by the maximum number of ports supported by the storage array.
- More difficult to non-disruptively migrate VMs between Building Blocks since storage cannot be shared across. (If all Building Blocks are in the same Virtual Data Center in VMWare vSphere, you can still live-migrate VMs via the IP network between Building Blocks using Storage vMotion)
If you decide that the host count limit is okay, and either non-disruptive migration between Building Blocks is unnecessary or Storage vMotion will work for you, then eliminating the fabric can reduce cost and complexity, while improving overall availability and time to deploy. If you need the flexibility of a fabric, I personally like using dedicated switches in each building block. Cisco and Brocade both offer 1U switches with up to 48 ports per switch that will work quite well. Always deploy two switches (as two fabrics) in each Building Block for redundancy.
Okay, so you’ve managed to calculate the size of your environment, how much time it will take you to virtualize it, the number of Building Blocks you need, and the specifications for each Building Block, including whether you need a fabric. Now you can submit your budget, get your final quotes, and place orders. Once the equipment arrives it’s time to implement the solution.
When your first Building Block arrives, it would be a valuable use of time to learn how to script the configuration for each component in the Building Block. An EMC VNX array can be completely configured using Naviseccli or PowerShell, from the Storage Pool and LUN provisioning to initiator registration and Host/LUN masking. VMWare vSphere can similarly be configured using scripts or PowerShell. If you take the time to develop and test your scripts against your first Building Block, then you can use those scripts to quickly stand up each additional Building Block you deploy. Since future Building Blocks will be nearly identical, if not entirely identical, the scripts can speed your deployment time immensely.
EMC Navisphere/Unisphere CLI (for VNX) is documented fully in the VNX Command Line Interface (CLI) Reference for Block 1.0 A02. This document is available on EMC PowerLink at the following location:Home > Support > Technical Documentation and Advisories > Software ~ J-O ~ Documentation > Navisphere Management Suite > Maintenance/Administration
Be sure to leverage any storage vendor plug-ins available to you for your chosen hypervisor (VMWare, Hyper-V, etc) to improve visibility up and down the layers and reduce the number of management tools you need to use on a daily basis.
For example, EMC Unisphere Manager, the array management UI running on the VNX storage array, includes built-in integration with VMWare and other host operating systems. Unisphere Manager displays the VMFS datastores, RDMs, and VMs that are running on each LUN and a storage administrator can quickly search for VM names to help with management and/or troubleshooting tasks.
EMC also provides free downloadable plug-ins for VMWare vSphere and Hyper-V so server administrators can see what storage arrays and LUNs are behind their VMs and datastores. The plug-ins also allow administrators to provision new LUNs from the storage array through the plug-ins without needing access to the array management tools.
Depending on which storage vendor you choose, if you build a fabric-less Building Block, you may be able to do all of your server and storage administration from vCenter if you leverage the free plug-ins.
Now that we know we’ll be deploying about 562 VM’s per Building Block we can use the other metrics to determine the requirements for a single block.
- Since 562 VMs is about 12.5% of the 4500 total VMs, we then calculate 12.5% of the other metrics determined in the last post.
- 12.5% of 9000 vCPUs = 1125 vCPUs
- 12.5% of 4500GB RAM = 562GB RAM
- 12.5% of 225,000 IOPS = 28125 Host IOPS
- 12.5% of 562TB = 70TB Usable Disk capacity
First we’ll size the compute layer of the Building Block
- At 4:1 vCPUs per Physical CPU thread you’d want somewhere around 281 hardware threads per Building Block. Using 4-socket, 8-core servers (32 cores per server) you’d need about 9 physical servers per building block. The number of vCPUs per physical CPU thread affects the % CPU Ready time in VMWare vSphere/ESX environments.
- For 562GB of total RAM per Building Block, each server needs about 64GB of RAM
- Per standard best practices, a highly available server needs two HBAs, more than two can be advantageous with high IOPS loads.
Next, we’ll calculate the storage layer of the Building Block
- Assuming no cache hits, the backend disk load for 28,125 Host IOPS @ 50:50 read/write looks like the following:
- RAID10 : 28125/2 + 28125/2*2 = 42187 Disk IOPS
- RAID5 : 28125/2 + 28125/2*4 = 70312 Disk IOPS
- RAID6 : 28125/2 + 28125/2*6 = 98437 Disk IOPS
- If you calculate the number of disks required to meet the 70TB Usable in each RAID level, and the # of disks needed for both 10K RPM and 15K RPM disks to meet the IOPS for each RAID level, you’ll eventually find that for this specific example, using EMC Best Practices, 600GB 10K RPM SAS disks in RAID10 provides the least cost option (317 disks including hot spares). Since 10K RPM disks are also available in 2.5” sizes for some storage systems, this also provides the most compact solution in many cases (29 Rack Units for an EMC VNX storage array that has this configuration). In reality this is a very conservative configuration that ignores the benefits of storage array caching technologies and any other optimizations available, it’s essentially a worst case scenario and it would be beneficial to work with your storage vendor’s performance group to perform a more intelligent modeling of your workload.
- Finally, you’ll need to select a storage array model that meets the requirements. Within EMC’s portfolio, 317 disks necessitate an EMC VNX5700 which will also have more than enough CPU horsepower to handle the 28125 host IOPS requirement.
At this point you’ve determined the basic requirements for a single Building Block which you can use as a starting point to work with your vendors for further tuning and pricing. Your vendors may also propose various optimizations that can help save you money and/or improve performance such as block-level tiering or extended SSD/Flash based caching.
Example bill-of-materials (BOM):
- 9 x Quad-CPU/8-Core servers w/64GB RAM each
- 2 x Single port FibreChannel HBAs
- 1 x EMC VNX5700 Storage Array with 317 x 300GB 2.5” 10K SAS disks
Wait, where’s the fabric?
The key to sizing Building Blocks is to calculate the ratio between the compute and storage metrics. First you need to take a look at the total performance and disk space requirements for the whole environment, similar to the below example:
- Total # of Virtual Machines you expect to be hosting (example: 4500 VMs)
- Total Virtual CPUs assigned to all Guest VMs (average of 2 vCPUs per VM = 9000 vCPUs)
- Total Memory required across all Guest VMs (average of 1GB per VM = 4.5TB)
- Total Host IOPS needed at the array for all Guest VMs (average of 50 IOPS per VM = 225,000 Host IOPS)
- You will need to have a read/write ratio with this as well (we will use 50:50 for these examples)
- Total Disk Storage required for all Guest VMs. (average of 125GB per VM = 562TB)
Once you have the above data, you need to decide how many Building Blocks you want to have once the entire environment is built out. There are several things to consider in determining this number:
- How often you want to be deploying additional Building Blocks (more on this below)
- Your annual budget (I’m ignoring budget for this example, but your budget may limit the size of your deployment each year)
- How many VMs you think you can deploy in a year (we’ll use 2250 per year for a two year deployment)
Some of these are pretty subjective so your actual results will vary quite a bit, but based what I’ve seen I do have some recommendations.
- In order to take advantage of the availability isolation inherent in the Building Block approach, you’ll want to start with at least two Building Blocks and then add them one or two at a time depending on how you want to spread your server farms across the infrastructure.
- Depending on the size of each Building Block you may want to keep Building Block deployments down to one every 3-6 months. That gives you ample time to build each block correctly and hopefully leaves time between deployments to monitor and adjust the Building Blocks.
That said I’d lean toward 4 to 6 Building Blocks per year. Of course this is just my opinion and your mileage may vary. For our example of 4500 VMs over 2 years @ 4 Building Blocks per year. we’ll end up with 8 Building Blocks with about 562 VMs each.
Since server virtualization abstracts the physical hardware from the operating systems and applications, essential for Cloud Infrastructures (also known as Infrastructure-as-a-Service), it’s ideally suited for breaking down the physical infrastructure into Building Blocks. Put simply, Building Blocks are repeatable, pre-designed mixes of storage, CPU, and memory.
There are several advantages to the Building Block approach that I’ll point out here:
- Rather than dropping a huge amount of capital up front on the entire infrastructure you need over the long haul, some of which will not be used at first, you can start with a smaller capital outlay today, then make multiple similarly small capital purchases only as needed. Further, when the hardware in a single Building Block reaches the end of its life (for any number of reasons), only that one Building Block will need to be refreshed at that time rather than a wholesale replacement of the entire environment.
- In an environment where virtualization is a new endeavor, sizing the compute, memory, and storage required is really an educated guess. As each Building Block is consumed, the real-world performance can be analyzed and adjusted for future Building Blocks to more closely match your specific workload.
- Building Blocks are inherently isolated which creates natural performance and availability boundaries. This can be leveraged for web and application server farms by spreading nodes of each farm across multiple Building Blocks. In the event of a catastrophic failure of one Building Block, due to major software bug affecting the cluster or the failure of an entire storage array for some reason, nodes of the server farm not hosted on the failed Building Block will be unaffected.
- The list price for storage arrays and servers goes down over time. If your growth is similar to many of my customers, where full build out of the physical infrastructure will not be required until 2-3 years after the start of the project, the acquisition cost of each individual Building Block will decrease over time, saving you money overall.
- In many cases, and due to a variety of factors, the cost to upgrade a storage array is higher than the cost to purchase the capacity with a new array. Upgrades also add complexity, complicate asset depreciation, and warranty renewals. The Building Block approach eliminates the majority of upgrades and the associated complexity.
Each Building Block can be maintained in its original build state or upgraded independent of the other building blocks so, for example, you don’t have to worry about upgrading every server in your datacenter with new HBA drivers if you decide to upgrade the storage array firmware on one array. You would only need to upgrade the servers in that arrays’ Building Block.
You may be thinking that your environment is not large enough to use a Building Block approach, but the more I worked on this project, the more I realized that Building Blocks can be adjusted to fit even very small environments. I’ll go into that a bit more later.
Part 1 -> The Building Block Approach
As 2011 wraps up and I have a little time at home over the holidays, I’ve been reflecting on some of the customer projects I’ve worked on over the past year. Cloud computing and EMC’s vision for the “Journey to the Private Cloud” have been hot topics this year and of the various projects I’ve worked on this past year, one stands out to me as something that could be used as a blueprint for others who want to deploy their own Private Cloud but may not know how to start.
I have been working with a customer with approximately 10,000 servers that support their business and for all intents had zero virtualization as recent as 2010. As most customers already know, they thought it would be good to begin virtualizing their environment to drive up asset utilization and flexibility while bringing down costs. In the past, they’ve experimented with multiple server virtualization solutions (such as VMWare ESX and Microsoft Hyper-V) with limited success and had all but abandoned the idea. A change in leadership in late 2010 brought a top-down initiative to virtualize wherever possible, but in order to instill confidence in virtualized environments within the various business units, the virtual infrastructure needed to be reliable and performant.
The customer spent the latter half of 2010 looking at their existing physical environment, finding that about 80% of the 10,000 servers were various application, file, and web servers; the remaining 20% being various database servers (mostly MS SQL). Moving an infrastructure this large into a Private Cloud model would take several years and, further adding to the challenge, the DBA teams were particularly wary about virtualizing their database servers. That said, the newly formed Virtualization and Cloud team set a goal of virtualizing the approximately 8,000 non-database servers over 36 months, starting out with dev/test and gradually adding production and tier-1 applications until only the database servers remained on physical infrastructure. They believe that if they prove success with virtualization during this first 3 years, the DBAs will be more willing to begin virtualizing their systems, plus there should be more knowledge and tools in the public domain for managing virtual database instances by then.
To accomplish all of their goals, the customer leveraged some experience that individual team members had gained from prior environments to come up with a Building Block based deployment. I worked with them to finalize the design and sizing for the each Building Block and throughout the year have helped analyze the performance of the deployed infrastructure to help determine how the Building Blocks can be optimized further. Through the next several posts, I will explain the Building Block approach, detailing the benefits, some of the considerations, and some thoughts around sizing. I hope that this information will be useful to others. The content is mostly vendor agnostic except for some example data that uses EMC specific storage best practices.
Part 1 -> The Building Block Approach
(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.
- 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.
- Install Replication Manager on a server and deploy an agent to each Exchange server
- Configure SANCopy connectivity between the two arrays over the IP ports built-in to each array
- 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.
- Install SnapManager for Exchange on each Exchange server
- Configure SnapMirror connectivity betweeen the two arrays over the IP ports built-in to each array
- 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.
- 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.