EMC Storage Product Knowledge Sharing

1. Install Fibre Channel HBAs in all systems
2. Install EMC CLARiiON LP8000 port driver ( For Emulex) on all system
3. Connect each host to both switches ( Broace/Cisco/McData)
4. Connect SP1-A and SP2-A to the first switch
5. Connect SP1-B and SP2-B to the second switch
6. Note:- You can use cross SP connection for HA and connect SPA1 and SPB1 to first switch and SPB2 and SPA2 to the second switch.
7. Install Operating System on windows/solaris/linux/Vmware hosts
8. Connect all hosts to the Ethernet LAN
9. Install EMC CLARiiON Agent Configurator/Navisphere Agent on all hosts
10. Install EMC CLARiiON ATF software on all hosts if you are not using EMC powerpath fail-over software otherwise install supported version EMC Powerpath on all hosts.
11. Install the Navisphere Manager on one of the NT hosts
12. Configure Storage Groups using the Navisphere Manager
13. Assign Storage groups to hosts as dedicated storage/Cluster/Shared Storage
14. Install cluster software on host.
15. Test the cluster for node failover
16. Create Raid Group with protection as application required(raid5,raid1/0 etc)
17. Bind LUN according to application device layout requirement.
18. Add LUN to storage Group.
19. Zone SP port and Host HBA on both switch
20. Register Host on CLARiiON using Navisphere Manager.
21. Add all hosts to storage group.
22. Scan the devices on host.
23. Label and Format the device on host.

Performance tuning has always been a challenge for System administrators and Database administrators for a long time. As virtualization continues to grow in every aspect of the IT infrastructure, tuning the OS, DB or storage tends to become even more complex.

Apart from CPU power and memory size, disk subsystem handles the movement of data on the computer system and has a powerful influence on its overall response. Also performance disk layout must also be designed to provide appropriate data protection with overall cost in mind.
Planning ahead is the most effective practice to avoid performance issues later on while also providing the flexibility to make adjustments before committing the changes into production.

Some fundamental disk terminology:

Alignment –Data block addresses compared to RAID stripe addresses
Coalesce – To bunch together multiple smaller IOs in one larger one
Concurrency – Multiple threads writing to disk simultaneously
Flush – Data in cache written to disk
Multi-pathing – Concurrent paths to same disk storage

How to choose a RAID type:

The concept of RAID is comprehensible to most in the storage industry. To extract the best disk performance, choosing the right RAID type based on IO patterns is very important. Most commonly observed IO patterns are listed later in the article. Since RAID 5 and RAID 1/0 are the most commonly used RAID types in the industry lets focus on these two for now.

RAID 1/0 – This RAID type works best for random IOs pattern especially for write-intensive applications. If the writes are above 20% go and RAID 1/0

RAID 5 – Compared to RAID1/0, for same number of physical spindles, the performance of the two is very close in a read-heavy environment. For instance, a 2+2 RAID 1/0 (total 4 disks) will perform similar to a RAID 5 3+1 (total 4 disks).

On the other hand, if one can afford to ignore the number of physical spindles and consider only the usable capacity (RAID 10 3+3 v/s RAID 5 3+1), RAID 1/0 is the way to go.

RAID1/0 has higher cost associated with it while RAID 5 provides a more efficient use of disk space. The only con associated with RAID 5 is the re-sync time after a disk replacement.

Number of Operations per RAID type:

RAID 1 and 1/0 require that two disks to be written for each host initiated write.
Total IO=host reads + 2* host writes
RAID5 (4+1) requires 4 operations per host write. If the data is sequential, do one large stripe write
A r5 write requires 2 reads and 2 writes
Total IO=host reads + 4*host writes

To re-cap,
. Parity RAID operations increase the disk load. For similar capacity, go for RAID1/0
. RAID5 is better than RAID1/0 for large sequential IO
. RAID 3 is much effective as you can now use cache with RAID 3
. RAID1/0 is best for mixed IO types.

Commonly noticed Database IO patterns:

OLTP Log – sequential
OLTP – Data – random
Bulk Insert - sequential
Backup – sequential read/write
Restore – sequential read/write
Re-index - sequential read/write
Create Database - Sequential read

Knowing your IO personality is important to choose which RAID type to consider. Using the above notes and application IO patterns, one can make a choice on the disk layout. Some characteristics of the IOs to consider are:
- IO size
- IO Read/Write ratio
- Type of IO - Random v/s Sequential
- Snapshots / Clones
- Application type – OLTP ?
- Bandwidth requirements
- Estimated Growth

Once you decide the type of RAID to use, you can fine tune the disk system by following vendor recommended practices like:

-- Lun distribution
-- Distribute the IO load evenly across available disk drives
-- Avoid using Primary and BCv/Snapshots luns on same physical spindles. (The best way to avoid this is to have separate disk groups for primary data disks and BCVs/Clones/Snapshots)
-- Consider using Meta or host stripping

Cache:
Disk writes are more costly and thus must be given bigger share of cache
Match cache page size to IO size to prevent multiple Ios

Stripe Size:
Retain default stripe size of 64KB
Larger the stripe size, more cache size required and longer it takes to rebuild

FC or iSCSI:
FC Best for large IO and high bandwidth
FC More expensive
iSCSI involves lowest cost
iSCSI works best for OLTP, small block IO

Some Best Practice recommendations from Microsoft:

Microsoft has laid a few guidelines for designing the SQL database
Use RAID1+0 for log files
Isolate log from data at physical disk level
Use RAID 1+0 for tempdb

Revisiting the above recommendations periodically to stay on track, will go a long way in extracting the best out of disks

--Contributed by Suraj Kawlekar

For best performance with most applications, each SP should have its maximum amount of cache memory and you should use the default settings for the cache properties. Analyzer shows how the cache affects the storage system, and lets you tune the cache properties to best suit your application.

A storage-system cache has two parts: a read cache and a write cache. The read cache uses a read-ahead mechanism that lets the storage system prefetch data from the disk. Therefore the data will be ready in the cache when the application needs it. The write cache buffers and optimizes writes by absorbing peak loads, combining small writes, and eliminating rewrites.

You can change read cache size, write cache size, and cache page size to achieve optimal performance. The best sizes of the read and write caches depend on the read/write ratio. A general norm for the ratio of reads to writes is two reads per write; that is, reads represent 66 percent of all I/Os.

Since the contents of write cache are available for read operations as well, you should allocate most of the available SP memory to the write cache. However, since the write cache is flushed after a certain timeout period, a read cache is also required to hold active data for longer periods of time.

Read cache size

The read cache holds data that is expected to be accessed in the near future. If a request for data that is in the cache arrives, the request can be serviced from the cache faster than from the disks. Each request satisfied from cache eliminates the need for a disk access, reducing disk load. If the workload exhibits a “locality of reference” behavior, where a relatively small set of data is


accessed frequently and repeatedly, the read cache can improve performance. In read-intensive environments, where more than 70 percent of all requests are reads, the read cache should be large enough to accommodate the dataset that is most frequently accessed. For sequential reads from a LUN, data that is expected to be accessed by subsequent read requests is read (prefetched) into the cache before being requested. Therefore, for optimal performance, the read cache should be large enough to accommodate prefetched data for sequential reads from each LUN.

Write cache size

Write cache serves as a temporary buffer where data is stored temporarily before it is written to the disks. Cache writes are far faster than disk writes. Also, write-cached data is consolidated into larger I/Os when possible, and written to the disks more efficiently. (This reduces the expensive small writes in case of RAID 5 LUNs.) Also, in cases where data is modified frequently, the data is overwritten in the cache and written to the disks only once for several updates in the cache. This reduces disk load. Consequently, the write cache absorbs write data during heavy load periods and writes them to the disks, in an optimal fashion, during light load periods. However, if the amount of write data during an I/O burst exceeds the write cache size, the cache fills. Subsequent requests must wait for cached data to be flushed and for cache pages to become available for writing new data.

The write cache provides sustained write speed by combining sequential RAID 5 write operations and writing them in RAID 3 mode. This eliminates the need to read old data and parity before writing the new data. To take advantage of this feature, the cache must have enough space for one entire stripe of sequential data (typically 64 KB x [number-of-disks -1], or, for a five-disk group, 256 KB) before starting to flush. Note that the sequential stream can be contained in other streams of sequential or random data.

Cache page size

This can be 2, 4, 8, or 16 KB. As a general guideline, EMC suggest 8 KB. The ideal cache page size depends on the operating system and application. Analyzer can help you decide which size performs best.

The Storage Processor (SP) processes all I/Os, host requests, management and maintenance tasks, as well as operations related to replication or migration features.

In Navisphere Analyzer, the statistics for an SP are based on the I/O workload from its attached hosts. It reflects the overall performance of CLARiiON storage system. The following Performance Metrics will be monitored for each CLARiiON storage system.

A LUN is an abstract object whose performance depends on various factors. The primary consideration is whether a host I/O can be satisfied by the cache. A cache hit does not require disk access; a cache miss requires one or more disk accesses to complete the data request.

As the slowest devices in a storage system, disk drives are often responsible for performance-related issues. Therefore, we recommend that you pay close attention to disk drives when analyzing performance problems.

SP performance metrics

• Utilization (%)

The percentage of time during which the SP is servicing any request.

• Total Throughput (I/O/sec)

The average number of host requests that are passed through the SP per second, including both read and write requests.

• Read Throughput (I/O/sec)

The average number of host read requests that are passed through the SP per second.

• Write Throughput (I/O/sec)

The average number of host write requests that are passed through the SP per second.

• Read Bandwidth (MB/s)

The average amount of host read data in Mbytes that is passed through the SP per second.

• Write Bandwidth (MB/s)

The average amount of host write data in Mbytes that is passed through the SP per second.

LUN performance metrics

• Response Time (ms)

The average time, in milliseconds, that a request to a LUN is outstanding, including waiting time.

• Total Throughput (I/O/sec)

The average number of host requests that are passed through the LUN per second, including both read and write requests.

• Read Throughput (I/O/sec)

The average number of host read requests passed through the LUN per second.

• Write Throughput (I/O/sec)

The average number of host write requests passed through the LUN per second.

• Read Bandwidth (MB/s)

The average amount of host read data in Mbytes that is passed through the LUN per second.

• Write Bandwidth (MB/s)

The average amount of host write data in Mbytes that is passed through the LUN per second.

• Average Busy Queue Length

The average number of outstanding requests when the LUN was busy. This does not include idle time.

• Utilization (%)

The fraction of an observation period during which a LUN has any outstanding requests.

DISK performance metrics

• Utilization (%)

The percentage of time that the disk is servicing requests.

• Response Time (ms)

The average time, in milliseconds, that it takes for one request to pass through the disk, including any waiting time.

• Total Throughput (I/O/sec)

The average number of requests to the disk on a per second basis. Total throughput includes both read and write requests.

• Read Throughput (I/O/sec)

The average number of read requests to the disk per second.

• Write Throughput (I/O/sec)

The average number of write requests to the disk per second.

• Read Bandwidth (MB/s)

The average amount of data read from the disk in Mbytes per second.

• Write Bandwidth (MB/s)

The average amount of data written to the disk in Mbytes per second.

• Average Busy Queue Length

The average number of requests waiting at a busy disk to be serviced,

including the request that is currently in service.

CLARiiON SP, LUN and DISK performance data is retrieved and processed daily. Raw performance data is kept for a longer term, i.e. 180 days, and CLARiiON performance reports are kept indefinitely for performance trend analysis.

Gold Copy represents a virtual point-in-time copy of the secondary LUN before the secondary LUN is updated with the changes from the primary LUN. Since it is a pointer-based virtual copy it only consumes space in the reserved LUN pool based on the amount of changes on the secondary LUN. During the secondary LUN update, the Gold Copy tracks all of the updates. When a region on the secondary is updated, the original region is copied to the reserved LUN pool to preserve a consistent point-in-time view of the secondary LUN at the time of start of update. This is a key feature that always ensures a consistent view of the secondary LUN. If the update from primary to secondary is interrupted due to a link failure or due to failure at the primary site (during the update), the Gold Copy is used by MirrorView/A software to rollback the partial update on the secondary LUN and return it to its previous consistent state.

Delta Set : MirrorView uses asynchronous writes, which means that I/O is not sent to the remote site at the same time as the host I/O. It is a periodic replication of a set of LUNs to a remote storage system. The Delta Set is created and changes are tracked during a MirrorView/A replication cycle. MirrorView/A replicates only

the last changed blocks during replication cycle and results in lower bandwidth requirement than synchronous or traditional native ordered write techniques. The Delta Set is, in reality, a local snap taken at the source side at the time of replication.