Ast 0085422 esg-lab_validation_-_q_logic_fabric_cache_adapter_-_june_2013

Lab Validation
Report
QLogic FabricCache 10000 Series Adapter
Enterprise Application Performance Scalability with QLogic Caching
Technology
By Mike Leone, ESG Lab Analyst
June 2013
© 2013 by The Enterprise Strategy Group, Inc. All Rights Reserved.

Lab Validation: QLogic FabricCache 10000 Series Adapter 2
Contents
Introduction..................................................................................................................................................3
Background............................................................................................................................................................... 3
QLogic FabricCache 10000 Series Adapter............................................................................................................... 4
ESG Lab Validation........................................................................................................................................5
Efficiency................................................................................................................................................................... 5
Scalability.................................................................................................................................................................. 8
Agility......................................................................................................................................................................11
ESG Lab Validation Highlights.....................................................................................................................13
Issues to Consider.......................................................................................................................................13
The Bigger Truth .........................................................................................................................................14
Appendix.....................................................................................................................................................15
All trademark names are property of their respective companies. Information contained in this publication has been obtained by sources The Enterprise
Strategy Group (ESG) considers to be reliable but is not warranted by ESG. This publication may contain opinions of ESG, which are subject to change from
time to time. This publication is copyrighted by The Enterprise Strategy Group, Inc. Any reproduction or redistribution of this publication, in whole or in
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you have any questions, please contact ESG Client Relations at 508.482.0188.
ESG Lab Reports
The goal of ESG Lab reports is to educate IT professionals about data center technology products for
companies of all types and sizes. ESG Lab reports are not meant to replace the evaluation process that should
be conducted before making purchasing decisions, but rather to provide insight into these emerging
technologies. Our objective is to go over some of the more valuable feature/functions of products, show how
they can be used to solve real customer problems and identify any areas needing improvement. ESG Lab's
expert third-party perspective is based on our own hands-on testing as well as on interviews with customers
who use these products in production environments. This ESG Lab report was sponsored by QLogic.

Introduction
This ESG Lab Report summarizes the results of independent, third-party testing of the QLogic 10000 Series 8Gb
Fibre Channel Adapter with a focus on database performance improvements and cache effectiveness in single-
server and multi-server environments. Also of interest was the transaction latency impact when using remote cache
versus local cache in a multi-server environment. The QLogic 10000 Series Adapter is designed to help datacenters
extend the life of their existing IT investment and provide a wide range of application performance benefits with a
non-disruptive deployment approach.
Background
Solid-state storage has rapidly become a standard part of many storage infrastructures. While the sharp rise in
adoption is no doubt due in part to declining prices, it is also a factor of a growing number of implementation
options, as well as a shift towards the use of solid-state as cache and a broader range of applications than before.
Since this latest wave of solid-state use started with enterprise storage vendors shipping solid-state drives designed
to fit in external disk storage subsystems, it follows that nearly half (49%) of current users are leveraging this option
today. However a nearly identical percentage of end-users have leveraged the benefits of solid-state as extended
cache/memory/primary storage within servers (48%).1
Figure 1. Current Usage of Solid-state Storage Technology
Source: Enterprise Strategy Group, 2012.
ESG research has shown that performance is the primary reason for the initial implementation of solid-state
technology. As organizations gain more experience with solid-state storage, they are employing the technology
horizontally for a number of reasons, including improved I/O performance, reliability, longevity, and cost of
ownership. Solid-state is moving from a specialist niche performance tool to a more regular part of a storage
hierarchy. And at least from a purchase-decision perspective, performance and other attributes are becoming less
likely to be connected to specific applications and, instead, tend to be employed more as a horizontal infrastructure
“turbo boost” that is integrated efficiently into the storage infrastructure via technologies such as server based
caching, maximizing the bang for the buck. 2
1
Source: ESG Research Brief, Solid-state: Not Just for Storage Systems Anymore, December 2012
2
Source: ESG Research Brief, Solid-state Continues to Shed 'Niche' Moniker, May 2013
4%
38%
39%
40%
48%
49%
0% 10% 20% 30% 40% 50% 60%
Don’t know
Within a standalone solid-state storage
appliance used as primary storage
Within a standalone solid-state storage
appliance used as a cache
As extended cache/memory within a
storage controller
As extended cache/memory/primary
storage within a server
As solid-state drives in an external disk
storage subsystem
Which of the following implementations of solid-state storage technology is your
organization currently using?

QLogic FabricCache 10000 Series Adapter
The QLogic FabricCache 10000 Series 8Gb Fibre Channel Adapter is a fully integrated hardware solution that
combines Fibre Channel connectivity with enterprise-class PCIe flash technology. The result is increased, scalable
application performance with reduced I/O latency through data caching. A PCIe flash adapter caches SAN data and
accelerates server I/O access performance.
Shared caching gets offloaded to the QLogic 10000 Series Adapter’s hardware, which enables the acceleration of
clustered, virtualized, and distributed application workloads throughout the IT infrastructure. A universal single
driver and management model makes deployments fast and easy while reducing software stack complexity.
Figure 2. QLogic FabricCache 10000 Series Adapter
Without needing to change the existing SAN infrastructure, software drivers, or management framework, the
QLogic FabricCache Adapter helps organizations:
 Consolidate by using an integrated Fibre Channel adapter and cache solution.
 Simplify by leveraging transparent, server-based caching and I/O management.
 Share cache among clustered servers and applications in a fully virtualized environment.

ESG Lab Validation
ESG Lab performed hands-on evaluation and testing of the QLogic 10000 Series Adapter at the QLogic headquarters
in Aliso Viejo, California. Testing was designed to demonstrate the database performance benefits and cache
effectiveness of leveraging the QLogic caching technology with OLTP workloads in a single-server and multi-server
environment. ESG Lab also tested the performance impact of remote cache versus local cache in a multi-server
environment.
Efficiency
The first phase of testing focused on the performance efficiency of a QLogic 10000 Series Adapter in a single-server
environment. The test bed is shown in Figure 3. ESG Lab used an x86-based server running Windows Server 2008 R2
SP1 with a 2.5 GHz Intel Xeon processor (24 logical cores) and 32GB of RAM. A QLogic 10542 FabricCache Adapter
was installed and connected to an 8Gbps fibre channel switch. The switch was connected to three different storage
arrays from industry-leading vendors, one array with older technology using 10K drives was tested, along with two
newer technology arrays with 15K drives. Testing with the three different storage arrays yielded similar results,
demonstrating equivalent maximum performance regardless of the array being used, and served as a way for ESG
Lab to validate the achievable performance of a FabricCache Adapter across multiple storage vendors and array
capabilities. Array-agnostic performance was expected as the QLogic solution operates as server-based caching,
offloading read traffic from the SAN and the arrays.
It is noteworthy to consider that older arrays with lower performance charactistics will realize the largest relative
performance gain from the QLogic caching solution, but newer arrays such as those that contain flash-based
technologies themselves, while not part of this testing, will actually benefit the QLogic solution, as the time
required for the cache in the QLogic device to warm up will be minimized.
Two RAID5 LUNs were created: a 1TB database LUN containing a 200GB database and a 500GB log LUN.
Figure 3. ESG Lab Test Bed – Single-server Environment
ESG Lab Testing
ESG Lab used an OLTP online brokerage application to simulate the activity of database users with a goal of
demonstrating the achievable performance of a FabricCache Adapter. The workload was designed to emulate the
database activity of users in a typical online brokerage firm as they generated trades, performed account inquiries,
and did market research. The workload was composed of ten transaction types with a defined ratio of execution.
Four of the transactions performed database updates, the rest were read-only. The workload generated a high level
of I/O activity with small access sizes, creating a workload that was well suited for evaluating the efficiency of the
adapter.
The number of transactions processed per second for the ten transaction types were monitored as the concurrent
user count scaled from one to 250 for four different adapter cache data set coverage percentages: 0%, 30%, 50%,
and 100%. With 0% cache coverage, the workload was serviced strictly by the storage system and at 100%, the
workload was completely serviced by the FabricCache Adapter. Utilizing cache capacity just 30% of the size of the
database, ESG Lab attained peak performance with a concurrent user count of 50 and above. The results are
summarized in Figure 4 and Table 1.

Figure 4. OLTP Performance in a Single-server Environment – Transactions/sec
Table 1. ESG Lab Test Results – Transactions/sec
Total Number of Transactions/sec
Concurrent User Count No Cache 30% Cache 50% Cache 100% Cache
1 11.66 8.79 11.04 16.55
25 74.15 18.93 41.05 252.45
50 78.99 559.57 551.95 510.52
75 77.93 534.69 536.88 518.64
100 73.09 536.82 540.62 527.67
…
250 74.39 546.49 551.24 535.61
What the Numbers Mean
 Using one FabricCache Adapter in a single-server environment, ESG Lab scaled a concurrent user count
from one to 250 at four levels of cache data set coverage: 0%, 30%, 50%, and 100%.
 Peak performance in all cache coverage areas was reached at a concurrent user count of 50. It is important
to note that performance did not degrade as the user count continued to scale up to 250 users.
 The number of transactions/sec reached a plateau of over 500, with a maximum of 559.57 at 30% cache
coverage, proving to be a seven times performance improvement over not using the adapter.
 Cache only 30% the size of the database was needed to satisfy the OLTP workload requirements and attain
maximum performance
 Testing demonstrates array-agnostic maximum performance.
Recognizing that the workload only needed 30% database coverage, ESG Lab dug deeper into the results. To serve
as another way to measure the storage performance efficiency, the total number of IOPS was also measured as the
workload scaled. The results are highlighted in Figure 5 and Table 2.
0
100
200
300
400
500
600
1 25 50 75 100 125 150 175 200 225 250
Transactions/sec
Number of concurrent users
OLTP Performance in a Single-server Environment
No Cache 30% Cache 50% Cache 100% Cache

Figure 5. OLTP Performance in a Single-server Environment – IOPS
Table 2. ESG Lab Test Results – IOPS
Concurrent User Count Total Number of IOPS (with 30% cache coverage)
1 2,839
25 3,720
50 90,779
100 94,616
150 94,976
200 94,628
250 94,626
 In a single-server environment, one FabricCache Adapter with cache capacity only 30% -of the database size
easily serviced the requirements of a mission-critical OLTP application workload.
 Sustainable IOPS performance was achieved as the workload scaled up from one to 250 users.
 Peak performance of just under 100,000 IOPS was achieved between 50 and 100 concurrent users.
Why This Matters
With the increasing demands on IT, users have less tolerance for poor application performance. Many
organizations resist moving tier-1 applications to virtual servers for fear that workload aggregation will slow
performance. For virtualized and other data-intensive workloads, the primary performance bottleneck is storage
I/O. With a goal of increasing server performance and VM density and taking advantage of advancements in
network bandwidth, organizations seek solutions that meet the requirements of more demanding business
applications while keeping servers, networks, and storage balanced from the standpoint of I/O performance.
ESG Lab verified that the QLogic 10000 Series Adapter provides transparent I/O management and caching to the
host server through an integrated PCIe flash card and Fibre Channel Adapter solution. Using an OLTP workload to
provide real-world objective results, ESG Lab measured the performance acceleration delivered by the QLogic
server-based SAN caching technology in a single-server. With cache only 30% of the database size, OLTP
performance increased over seven times when compared to no cache coverage, demonstrating the cache
effectiveness offered by the QLogic technology. ESG Lab reached peak results of 559.97 transactions/sec and
94,976 IOPS.
0
20,000
40,000
60,000
80,000
100,000
1 25 50 100 150 200 250
TotalNumberofIOPS
OLTP Performance in a Single-server Environment
(with 30% cache coverage)

Scalability
The next phase of testing focused on the performance scalability of a FabricCache Adapter in a multi-server
environment. The test bed is shown in Figure 6. ESG Lab used four x86-based servers with the same specifications
and the same FC switch as with the single-server testing. ESG Lab also used the same three storage arrays on the
backend. Each server was fitted with a QLogic 10542 FabricCache Adapter and given access to a specific LUN on the
storage array that contained the same 200GB database.
Figure 6. ESG Lab Test Bed – Multi-Server Environment
ESG Lab Testing
ESG Lab used the same OLTP online brokerage application to simulate the activity of database users with a goal of
demonstrating the scalable performance of multiple FabricCache Adapters within the same environment. The
workload was consistent across all four adapters, with the same number of concurrent users being serviced by each
adapter as the concurrent user count went from one to 250. ESG Lab witnessed similar results to the single-server
testing in that cache capacity on each adapter only 30% of the database size was needed to attain the peak number
of transactions/sec for the given workload. The results are summarized in Figure 7 and Table 3.
Figure 7. Aggregate OLTP Performance in a Multi-Server Environment
0
500
1,000
1,500
2,000
2,500
1 25 50 75 100 125 150 175 200 225 250
Transactions/sec
OLTP Performance in a Four Server Clustered Environment
No Cache 30% 50% 100%

Table 3. ESG Lab Test Results – Transactions/sec
Concurrent User Count No Cache 30% Cache 50% Cache 100% Cache
1 14 11 13 12
25 71 56 57 61
50 124 510 616 511
75 108 1,796 1,841 1,768
100 93 1,924 1,911 1,945
125 92 1,916 1,962 1,964
…
250 87 1,925 1,950 1,957
 Using four FabricCache Adapters in a clustered, multi-server environment, ESG Lab scaled a concurrent user
count from one to 250 at four levels of data set cache coverage: 0%, 30%, 50%, and 100%.
 At the concurrent user count of 100, ESG Lab witnessed peak performance for all cache coverage areas.
Performance sustained this high level throughout the rest of the scaling user counts.
 The number of transactions/sec reached a plateau of over 1,900, with a maximum of 1,996 at 50% cache
coverage.
 Similar to the single-server testing, ESG Lab only needed to utilize cache capacity only 30% of the database
size to reach the highest performance for the OLTP workload.
ESG Lab broke down the results further to better understand how each of the four servers performed and scaled
when comparing no cache coverage to 30% cache coverage. The number of transactions/sec was measured for
each server and the results are shown in Figure 8 and Table 4.
Figure 8. Scalable OLTP Performance in a Multi-Server Environment
0
500
1,000
1,500
2,000
2,500
1 2 3 4
Transactions/sec
Total Numer of Servers
OLTP Performance Scalability
(4 Servers, 250 Concurrent Users)
0% Cache 30% Cache

Table 4. ESG Lab Test Results –Transactions/sec
Number of Servers No Cache 30% Cache Absolute Performance Difference
1 34 561 16.5 x
2 51 959 18.8 x
3 73 1,511 20.7 x
4 87 1,925 22.1 x
 OLTP workload performance was measured on four servers outfitted with FabricCache Adapters to show
performance scalability as each server was added to the environment.
 The workload measured focused on the highest concurrent user count of 250 and ESG Lab compared no
cache coverage with 30% cache coverage being utilized.
 Without using the adapter’s cache, the number of transactions/sec scaled from 34 to 87, showing very
minimal scalability. When using 30% cache coverage, performance scaled linearly from 561
transactions/sec with one server to 1,925 transactions/sec with four servers.
 Together, the four adapters yielded over 22 times more performance at 30% cache coverage than when not
using them.
Why This Matters
As data continues to grow, so do performance requirements. Adding a very large number of underutilized disk
drives to solve performance problems with I/O-bound applications decreases the efficiency of the IT infrastructure
by increasing acquisition, maintenance, power, cooling, and data center floor space costs while significantly
increasing the management complexity.
ESG Lab has confirmed that the QLogic FabricCache Adapter delivered extremely high levels of scalable, linear
performance as a mission-critical OLTP application workload increased from one to 250 concurrent users at varying
levels of cache coverage. ESG Lab needed cache coverage only 30% of the database size to reach peak performance
of nearly 2,000 transactions/sec, proving to be over 22 times faster than when not using the adapter.

Agility
The final phase of testing focused on the performance agility of a FabricCache Adapter when accessing data from a
local cache or remote cache. The test bed is shown in Figure 6. ESG Lab used two Dell R720 servers with the same
server specifications, connected them to the same FC switch, and finally connected to the same three storage
arrays as mentioned in the previous test bed descriptions. The two servers had their own FabricCache Adapters and
both adapters were configured to use the same data set. The primary data set was located in Server 1’s adapter,
which meant when Server 1 accessed the data, it was considered a local cache operation and when Server 2
accessed the data, it was considered remote cache operation as Server 2’s FabricCache Adapter had to access
Server 1’s FabricCache Adapter over the SAN.
Figure 9. ESG Lab Test Bed – Local vs. Remote Cache
ESG Lab Testing
ESG Lab used the same OLTP online brokerage application to simulate the activity of database users with a goal of
demonstrating how performance of remote cache showed negligible differences when compared to local cache.
ESG Lab scaled the concurrent user count from 100 to 350. ESG Lab witnessed results that showed with 30% cache
coverage users could expect to see a minimal performance impact of around 10% when data was accessed
remotely vs. locally, which still yields over 7x improvement over the non-cached performance. The results are
summarized in Figure 7 and Table 3.
Figure 10. OLTP Performance Overhead for Local vs. Remote Caching
100
150
200
250
300
350
400
450
500
550
600
650
100 125 150 175 200 225 250 275 300 325 350
Transactions/sec
OLTP Performance with Local and Remote Cache
(with 30% cache coverage)
Local Remote

Table 5. ESG Lab Test Results –Local vs. Remote Caching Transactions/sec
Concurrent User Count Local Cache Remote Cache Percent Difference
100 529.58 493.17 7%
125 542.12 486.34 10%
150 528.18 477.5 10%
175 525.44 478.73 9%
200 522.27 486.31 7%
225 548.66 494.42 10%
250 544.15 496.33 9%
275 535.39 486.1 9%
300 537.74 492.04 8%
325 536.63 484.52 10%
350 534.18 491.73 8%
 ESG Lab configured two servers for each FabricCache Adapter to test the potential performance impact of
servicing I/O requests remotely, as opposed to locally with an emulated OLTP application workload.
 The workload focused on concurrent user counts from 100 to 350 while ESG Lab utilized 30% cache
coverage.
 As the concurrent user count increased, the performance impact of using the remote cache, as opposed to
the local cache, remained a manageably low 10% IOPS difference, while maintaining an overall
performance gain of 7x compared with the non-cached measurements.
Why This Matters
PCIe flash adapters sit between the server hardware and the storage system. When deployed in clustered
environments, some degree of performance overhead can be expected when data is accessed on a remote server,
as opposed to when it is accessed on a local server. A high performance overhead would limit the types and
number of mission-critical business applications that can leverage the speeds and feeds associated with flash
storage.
ESG Lab measured a remote cache performance overhead of around 10% for a busy tier-1 database application
workload, which still provides the same relative performance increase of local cache operations, 7x over non-
cached operation. ESG Lab believes that this manageably low performance impact is easily justified given the
compelling consolidation, manageability, and cost saving benefits that can be achieved with the QLogic FabricCache
Adapter.

ESG Lab Validation Highlights
 ESG Lab verified how easy it was to integrate a QLogic 10000 Series Adapter into a single-server
environment and multi-server clustered environment, using a standard QLogic HBA driver.
 OLTP performance was measured in a single-server environment with different levels of cache coverage of
the database ranging from zero to 100%. The number of transactions/sec increased by up to seven times,
from 79 with 0% cache to 560 with only 30% cache coverage.
 In a multi-server environment, ESG Lab witnessed over 22 times OLTP performance improvements. This
scenario emulated a clustered application deployment, where four servers ran simultaneous I/O to the
same storage system.
 ESG Lab measured and compared the latency impact of remote caching versus local caching when adapters
are deployed in a multi-server cluster. The impact proved to be negligible at less than 10%. The
performance increase of cache-based operations is significant over non-cached operation that the user
experience is likely to be unaffected by the negilibile performance decrease of remote cache operation.
 Performance measurements with various arrays showed maximum performance attained with older, less
powerful arrays as well as newer, higher-end arrays.
Issues to Consider
 The QLogic FabricCache Adapter caches reads and write-through traffic, which is advantageous for typical
business application traffic where 80% or more I/O is reads. Though it does not cache writes via write-back
yet, the offloading of reads to the adapter provides the SAN with more cycles dedicated specifically to
servicing write requests to a storage array, improving array performance. Also, from the standpoint of
disaster recovery, there is no risk of data loss from a server failure in a multi-node cluster.
 The high cost of solid-state capacity compared with traditional hard drive capacity has focused early
adoption mainly among businesses whose revenue depends strictly on application performance (e.g.,
trading applications within the financial industry). As a matter of fact, ESG research indicates that the high
cost of solid-state capacity is the number-one objection by organizations that have not yet deployed a flash-
based storage solution. As the cost of flash capacity decreases over the next three to five years and
performance needs increase, ESG expects that the adoption of PCIe flash drives will grow in the broader,
horizontal enterprise IT market. This is especially true within server virtualization and desktop virtualization
environments with high performance needs. In this case, PCIe flash drives have an economic advantage
($/IOP) compared with traditional hard drives.

The Bigger Truth
Both virtualized and distributed workloads demand faster performance in today’s mission-critical data centers.
Current solutions lack the multidimensional requirements of clustered servers and complex business-critical
applications working together in perfect harmony. With a goal of reaching the highest levels of efficiency,
organizations are looking for solutions to improve server performance, increase VM density, free up network
bandwidth, and maximize I/O performance for demanding application workloads like OLTP.
To handle the performance needs of rapidly proliferating virtual servers, VDI boot storms, OLTP database
workloads, and the demands of cloud computing, many organizations purchase Fibre Channel and/or high-speed
SAS HDDs with SSD as a tier of cache or deploy entire arrays full of SSD. These are expensive storage solutions to a
performance problem that can be managed elsewhere. As an alternative, QLogic enables organizations to
significantly boost performance while using entry-level, mid-range or enterprise SAN arrays. By using this combined
approach, for example, organizations can lower costs by using high-capacity SATA drives, which help lower power,
cooling, and floor space costs that come from using fewer, larger capacity storage arrays. Backend storage arrays
are freed from servicing high performance read/write operations and can focus instead on storage-based tasks such
as snapshots, remote mirroring, compression, deduplication, and backup.
ESG Lab validated that the QLogic 10000 Series Adapter improved OLTP performance by over seven times in a
single-server environment with just 30% cache coverage. ESG Lab witnessed performance gains even higher in a
multi-server environment with the same cache coverage achieving over 22 times the performance with a four node
cluster. When comparing the latency of transactions/sec between local caching and remote caching in a multi-
server cluster, ESG Lab observed a negligible performance difference of less than 10%, which is unlikely to effect
the user experience of cache accelerated applications. ESG Lab has confirmed that the 10000 Series Adapter
optimized performance and maximized the achievable number of transactions/sec, which will help organizations
increase the value of their existing infrastructures while decreasing costs.
The QLogic 10000 Series Adapter offers a cost-efficient solution that plugs into an existing infrastructure without
the need to change anything else. Organizations can consolidate their infrastructures by combining an FC adapter
and SSD cache solution that can be shared among clustered servers and applications to simplify I/O management
through transparent, server-based caching.
Organizations are turning to server-based cache solutions for database application workloads that demand high
performance. QLogic looks to leverage its deep knowledge of networking technology with flash management and
on-board caching intelligence to offer the new FabricCache Adapter: a highly effective, server-based caching
solution that enables organizations to meet the strict performance requirements of mission-critical enterprise
applications.

Appendix
Table 6. ESG Lab Test Bed
Servers
Intel Xeon Processor
24 logical cores
2.5 GHz
32GB of RAM
Networking
8Gbps FC switch
Storage
QLogic 10542 FabricCache Adapter
Dual 8Gbps FC
400GB
SAN
Arrays featuring 10K FC drives or 15K FC drives
1TB database LUN (RAID5) with 200GB database
500GB log LUN (RAID5)

20 Asylum Street | Milford, MA 01757 | Tel: 508.482.0188 Fax: 508.482.0218 | www.esg-global.com

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