lab validation report lab validation...data growth has not slowed down over the last few years. as a...

Lab Validation Report Infineta Data Mobility Switch

Hyper-scale WAN Optimization

By Ginny Roth and Tony Palmer

June 2011 © 2011, Enterprise Strategy Group, Inc. All Rights Reserved.

Lab Validation: Infineta Data Mobility Switch 2

© 2011, Enterprise Strategy Group, Inc. All Rights Reserved.

Contents

Introduction .................................................................................................................................................. 3 Background ............................................................................................................................................................... 3 Infineta Data Mobility Switch ................................................................................................................................... 4

ESG Lab Validation ........................................................................................................................................ 6 Real World Simulations ............................................................................................................................................ 6 Optimization and Reduction for Accelerated Throughput ..................................................................................... 10 Traffic Control and Prioritization ............................................................................................................................ 14

ESG Lab Validation Highlights ..................................................................................................................... 17

Issues to Consider ....................................................................................................................................... 17

The Bigger Truth ......................................................................................................................................... 18

Appendix ..................................................................................................................................................... 19

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 part, whether in hard-copy format, electronically, or otherwise to persons not authorized to receive it, without the express consent of the Enterprise Strategy Group, Inc., is in violation of U.S. Copyright law and will be subject to an action for civil damages and, if applicable, criminal prosecution. Should 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 emerging technologies and products in the storage, data management, and information security industries. 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 offerings. 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 Infineta.



Introduction

Data growth has not slowed down over the last few years. As a matter of fact, most organizations are reporting more data growth than ever before. This growth presents a myriad of challenges, not the least of which is managing the storage and movement of data for high availability. In addition, the adoption of virtualization in the data center has enabled automated provisioning of resources as capacity requirements grow, which can put additional pressure on WAN connections between data centers. ESG Lab conducted hands on testing of Infineta’s Data Mobility Switch, examining its ability to provide extremely high performance connectivity while optimizing, reducing, and controlling delivery of inter-data center traffic.

Background

Recently, ESG asked IT managers about their spending plans for their storage infrastructure over the next 12-18 months: “data replication solution for off-site disaster recovery” was the second highest priority, just behind backup and recovery.1 Data growth puts pressure on backup and recovery, causing organizations to struggle to keep pace with performance requirements when working over WAN links.

Figure 1. Spending Priorities for Data Storage Infrastructure

Source: Enterprise Strategy Group, 2011.

1Source: ESG Research Report, 2011 IT Spending Intentions Survey, January 2011.

17%

17%

18%

18%

21%

21%

23%

24%

36%

0% 10% 20% 30% 40%

Tiered storage

Use cloud storage services

Data reduction technologies

Purchase more power-efficient storage hardware

Storage virtualization

Improved storage management software tools

Purchase new SAN storage systems

Data replication solution for off-site disaster recovery

Backup and recovery solutions

With regards to specific spending plans for data storage infrastructure, in which of the following areas will your organization make the most significant investments over the

next 12-18 months? (Percent of respondents, N=289, five responses accepted)

http://www.enterprisestrategygroup.com/2011/01/2011-it-spending-intentions-survey/



As businesses move to public and private services in the cloud, the need to move resources fluidly from one location to another becomes more essential. As servers become virtualized, moving data and applications becomes much more dynamic, decentralizing services across multiple data centers in various locations.

Branch office, remote office, SOHO, and mobile users have different requirements than inter-data-center communications. They are concerned with responsiveness and productivity of applications over low-speed, high-latency inks. Inter-data-center communications, on the other hand, consist of machine to machine interactions. Machines (e.g., storage arrays, compute clusters and data warehouses) are concerned with moving lots of data very quickly over high speed, low latency links. This need to move large volumes of data across multi-Gigabit, long distance WANs requires solutions that can scale up to provide the high throughput and reduction capabilities required for hyper-scale workflows such as replication and backup, big data transfers, and virtualization traffic such as VM migrations, VMDK transfers, etc.

Infineta Data Mobility Switch

Providing a cost-effective solution for Hyper-scale WAN optimization, Infineta’s Data Mobility Switch (DMS) optimizes, reduces, and controls data transmission for critical applications that require high performance throughput from data center to data center. The DMS has the ability to fully utilize large WAN links and reduce the footprint of hyper-scale traffic running between data centers.

The appliance is designed to address enterprise needs for inter-data-center traffic including:

Synchronous and asynchronous replication for data protection

Virtual machine mobility for live virtual machine migrations over long distances

Large-scale file transfers, including transferring large VM disk images (VMDKs)

Scale-out distributed computing traffic such as Hadoop

Figure 2. Infineta Data Mobility Switch

As shown in Figure 2, Infineta’s Data Mobility Switch uses a distributed processing framework in its design with core feature sets that address the following goals:

Acceleration: The DMS accelerates up to 10Gbps of traffic that matches a configured acceleration policy. The DMS is also able to bypass up to an additional 30Gbps of traffic that doesn’t match any configured acceleration policy, which is a critical feature for inline deployments.

Multi-Stage Data Reduction: The DMS is able to sustain inline data reduction rates at levels of 80-90% using a parallel, pipelined architecture implemented entirely in hardware.

High Throughput: The DMS creates an ideal replication solution for synchronous storage array replication and other latency sensitive traffic by supporting up to 1Gbps speeds per connection. High throughput is also guaranteed for other critical workflows (e.g., asynchronous replication and migration) traversing long distance (100ms+ latency) WAN links.



Control: The DMS supports creation of granular QoS policies to ensure tight SLAs for critical application traffic.

Low Latency Overhead: The DMS delivers all the features listed above while achieving an average of 50µs (microsecond) port to port latency, providing a transparent acceleration layer for Hyper-scale WAN workflows.

The DMS has been designed with simplicity in mind; it can be deployed both inline and out-of-path in a data center network as needed as show in Figure 3. The DMS can be deployed in a tiered data center network between the data center core and WAN routers where two WAN links are terminating in the data center. No additional investment is required to load balance traffic across a number of WAN optimization devices, making the entire solution simple and cost effective.

The DMS has also been designed to work with any/all routing asymmetries that may arise in a data center network for both inline and out-of-path deployments. Figure 3 depicts how routing asymmetry is addressed in inline deployments: the dotted line between the two DMSs depicts what Infineta calls ISL (Inter data mobility Switch Link) ports that can be connected back-to-back or via a switch or router. The ISL is a 1+1 dedicated 10Gbps connection that is used by DMSs to synchronize TCP connection summaries to ensure that the right DMS accelerates misrouted packets after a routing policy change.

Figure 3 also illustrates an out-of-path deployment using policy-based traffic redirection. The DMS appliances sit as a high availability pair using Virtual Router Redundancy Protocol (VRRP) for failover.

Figure 3. DMS In the Data Center



ESG Lab Validation

ESG Lab performed hands-on evaluation and testing of the Data Mobility Switch at Infineta’s facilities in San Jose, California. Testing was designed to demonstrate the optimization, reduction, and control achieved with the DMS appliance replicating high throughout data traffic from one data center to another.

Real World Simulations

The configuration for the tests is illustrated in Figure 4.Two data centers were simulated using two servers in each location. One server in each data center was used for testing acceleration through the DMS while the remaining pair was reserved for tests that included bypass traffic. The servers were connected directly to the DMS appliances over a 10Gbps link, which in turn were connected to an Apposite Netropy 10Gbps switch to simulate a long-distance WAN.

ESG Lab used the open source solution, Distributed Replicated Block Device (DRBD), to simulate real world replication use cases with seven volumes configured as DRBD resources to replicate traffic across the WAN to an identical data center configuration with mirrored DRBD resources. Both the accelerated and bypass servers contain seven DRBD resources each for direct comparison testing.

Figure 4. ESG Lab Test Bed

The DMS accelerates business-critical traffic traversing hyper-scale WANs by reducing the footprint of this traffic, applying advanced TCP optimization to fill WAN pipes regardless of bandwidth, corrects for packet loss and latency over long distance WAN connections, and prioritizes traffic being accelerated to ensure that the most critical traffic makes its way across the WAN without any delays.

Data reduction is performed in hardware with the DMS performing three operations in a pipelined manner. Repeating byte suppression is first used to identify and remove repeating byte sequences. The Velocity Dedupe Engine (VDE), which is implemented in programmable logic, identifies and removes redundancies within and across all connections. The VDE performs deduplication at line rate (up to 10Gbps). Finally, the data is compressed to further reduce traffic before leaving the appliance.

Combining acceleration with data reduction enables the DMS to scale to very high traffic rates with thousands of TCP connections. This capability is required for enterprise data centers that are adopting paradigms such as distributed computing and virtual machine migrations. ESG Lab examined multiple real world use cases in order to compare the results of optimization with and without the DMS over a WAN link.



ESG Lab Testing

Storage Replication & Migration

ESG Lab first tested data migration by using the DRBD migration tool to move large volumes of data from one data center to the other. Two tests were started, one migrating data between two hosts using the bypass link on the DMS and the other migrating data using an accelerated link. ESG Lab started both migrations at 10:20 AM with 1.6 TB of data for each test used, totaling 3.2 TB migrated through the appliance. ESG Lab compared the progress of both migrations and observed that the accelerated link was quickly able to reduce the data by over 75% after about 15 minutes, with the overall accelerated migration experiencing 85% reduction in WAN traffic. As the migration progressed, ESG Lab observed that the accelerate traffic reached throughput levels of well over 4Gbps, compared to only 1.18Gbps for the bypass traffic.

After the tests completed, ESG Lab observed the total time for both migrations. The accelerated traffic test completed at 11:45 AM, approximately 1:25 total completion time. The bypass traffic test completed at 1:30 PM, approximately 3:10 total completion time.

Figure 5 shows the average results for the accelerated link, with the time scale (approximately) corresponding to the start and stop times for the accelerated migration. Note that the data reduction achieved by the DMS averaged over 85%. The results of data reduction are also reflected in the WAN traffic graph when compared to the LAN traffic graph, showing a significant drop in the throughput of data moving across the WAN link at the same time reduction levels began to increase. During most of the test, the DMS achieved throughput levels of 4Gbps+.

Figure 5. Data Migration

ESG Lab used the same DRBD tool to test data replication for both accelerated and bypass traffic. The tests were performed by running change block operations in parallel on 1 GB files on all seven resources. As shown in Figure 6, the DMS was able to reduce the replication traffic being accelerated by over 91%, effectively shrinking the traffic sent to the WAN link from 4.5Gbps to just under 400Mbps.In comparison, the bypass traffic achieved no more than 1.1Gbps throughput.



Figure 6. Data Replication

Backup and File Transfer

ESG Lab performed a series of additional tests to compare how DMS accelerates performance for backup and file transfer applications. Figure 7 shows the time-to-completion for various traffic types with and without the DMS accelerating them. The WAN link was configured at 1Gbps for all these tests.

The two SCP tests consisted of an SCP copy of a 1 GB random file from the primary to the secondary servers with the round trip time of the WAN increased for each test. The round trip time (RTT) is the time it takes for a data packet to reach the remote location plus the time for an acknowledgement of receipt of the packet to be returned.

ESG Lab simulated a backup test using Rsync to backup 35 (thirty-five) 1 GB files. Although the WAN link was configured for 1Gbps throughput, two tests were run: a) With a system-wide LAN cap of 1Gbps, and b) with a system-wide LAN cap of 10Gbps. As expected, the throughput results for bypass traffic and for the 1Gbps LAN cap scenario were quite similar. However, when the LAN cap was increased to 10Gbps, the DMS was so effective at reducing traffic that the transfer times dropped significantly when compared to the throughput for bypass traffic.

ESG Lab also performed a test where VMDK files were transferred over the WAN using FTP. Achieving reduction rates of over 78%, the transfers accelerated by the DMS were able to outperform the bypass link for virtual machine copies by a significant margin.



Figure 7. File Transfer Times

Why This Matters

Data growth is precipitated by a number of factors that include the proliferation of distributed computing, automated provisioning of virtual resources, and other data center applications. These workflows require larger WAN links and need optimization solutions that can handle the inevitable big traffic requirements. Companies typically either invest in larger WAN links or face complex WAN optimization architectures. Infineta’s DMS provides a high-performance WAN optimization solution that can be deployed simply and seamlessly with no additional investments are needed to load balance traffic across a large number of WAN optimization devices. What’s more, the entry price for the DMS makes Infineta’s solution very compelling.

ESG Lab performed multiple real world tests to simulate data migration/replication, large file transfer, and backup and VMDK transfers and observed optimization and reduction results that allow the DMS to quite effectively accelerate hyper-scale WAN traffic such as high-speed replication and, more importantly, complete the activity in question (backup job, full migration, etc.) significantly faster. A single appliance that scales up to 10Gbps links provides the scalability to handle the predictable growth of data in enterprise data centers.

SCP (50ms) SCP(80ms) Rsync(1Gbps LAN cap)

Rsync(10Gbps LAN cap)

FTP

Tim

e (

in s

eco

nd

s)

File Transfer Times

Accelerated Bypass

400

0



Optimization and Reduction for Accelerated Throughput

ESG Lab used the same test bed to perform Iperf tests for acceleration and data reduction. Iperf is a network testing tool that can create TCP streams to benchmark the throughput supported by a system processing these streams. During the tests, ESG Lab changed the speed and RTT on the Netropy to simulate varying throughputs and distances from one data center to the other.

Figure 8. Iperf Test Bed

ESG Lab Testing

ESG Lab began testing both the optimization and reduction capabilities of the DMS using the Iperf utility to create persistent traffic flows from one data center to the other and to test the DMS performance under varying Iperf loads. As testing progressed, ESG Lab increased the number of Iperf connections, the WAN bandwidth, and the simulated distance between data centers. Performance of the accelerated link and data reduction results were recorded to compare the throughput and data reduction achieved by the DMS in varying conditions. Table 1 details the parameters used for each test.

Table 1: Iperf Test Parameters

Test # # Iperf Connections WAN RTT MTU Bypass Traffic

1 1 1Gbps 0ms 1500 0

2 1 1Gbps 50ms 1500 0

3 10 10Gbps 50ms 1500 0

4 10 10Gbps 50ms 3000 0

5 10 10Gbps 50ms 1500 10Gbps

6 10 10Gbps 50ms 1500 5Gbps

ESG Lab started Iperf tests with one TCP connection over a 1Gbps WAN link and used a 10Gbps WAN link for the third test and onwards. In the first four tests, a combination of Iperf connections, WAN speed, or WAN RTT was increased to test the throughput at different levels. The RTT of the WAN appliance was set to 50ms after the first test to simulate a distance from San Jose to Chicago. Figure 9 expresses the percent to which the DMS was able to fill a given WAN link, with 1Gbps for Test 1 and Test 2 and 10Gbps for the rest.



The reported throughput and data reduction numbers are based on all (Layer-2) data, not just TCP payload. This is important as headers and other overhead comprise a significant portion of the data and performance and should be included.

Figure 9. Optimized Traffic Results

ESG Lab ran additional tests with 10 Iperf connections over 10Gbps WAN links. As Figure 9 shows, the DMS was able to accelerate traffic to 10Gbps, including when jumbo frames were enabled.

ESG Lab ran two more tests in which bypass traffic was added; one was allowed to fill the link and the other was capped at 5Gbps. With both tests, the accelerated traffic was still able to reach near 10Gbps throughput. The DMS correctly selected traffic configured for acceleration, passing through the rest without overhead.

ESG Lab also ran a stress test that made use of Infineta’s internal change_block tool to create 100,000 TCP connections. The tool itself was limited in its ability to generate 10Gbps traffic and only scaled to 7Gbps. Although it is unlikely that data center to data center traffic would reach this number of TCP connections, the fact that the DMS was able to maintain 7Gbps throughput with 100k connections is very impressive. Figure 10 illustrates both the high level of TCP connections sustained through the test and the near 7Gbps throughput achieved.

96.50% 95.70% 94.70% 94.90% 95.60% 94.60%

Test 11Gbps

Test 21Gbps

Test 310Gbps

Test 410Gbps

Test 510Gbps

Test 610Gbps

DM

S Th

rou

ghp

ut(

%)

Accelerated Traffic



Figure 10. High TCP Connections Results

In all of the IPerf tests run for accelerated traffic, ESG Lab also observed the levels of data reduction achieved. Figure 11 illustrates the results of each test. With accelerated, multi-connection data flows scaling to 10Gbps, the DMS was able to achieve data reduction levels of 90% and over. The change block test discussed previously resulted in a reduction ratio of 89.43%.

Figure 11. Reduced Traffic Results

92.19% 92.00% 92.00%96.00%

92.08% 90.00%

Test 11Gbps

Test 21Gbps

Test 310Gbps

Test 410Gbps

Test 510Gbps

Test 610Gbps

Dat

a R

ed

uct

ion

%

Data Reduction



Why This Matters

Based on business requirements reported to ESG by IT managers, data replication across high-speed inter-data center WAN links is going to increase as the amount of production data in data centers grows. These changes are driven in part by increasing use of virtualization and cloud solutions.

Businesses are trying to meet the demands of live application mobility and replication requirements that are growing by orders of magnitude with existing WAN technology and shrinking budgets. Combining both optimization and reduction, Infineta’s DMS provides a Hyper-scale WAN optimization solution that can meet the demands of data center to data center traffic today and still grow with customers’ needs as they move to wider WAN links.

ESG Lab tested the raw speed and data reduction capabilities of the DMS using persistent TCP connections, and observed significant data reduction and acceleration at wire speed. The DMS performed flawlessly even with 10Gbps links with hundreds of thousands of TCP connections. As companies look to scale inter-data center communications, the DMS can accommodate those needs with a minimum impact on their budgets.



Traffic Control and Prioritization

Infineta’s DMS employs a fully non-blocking switch fabric that can make complex switching decisions in microseconds in the face of sustained traffic. It includes a policy-based QoS engine that selects and prioritizes incoming traffic for acceleration processing at wire speeds. Mission critical traffic can be prioritized (strict or deficit round robin scheduling) for acceleration and minimum bandwidth can be allocated to QoS Profiles (akin to Class of Service) to ensure service level agreements are met.

ESG Lab Testing

ESG Lab tested QoS Profiles created on the DMS to examine their impact on traffic throughput for each port. Testing started with eight profiles, all given a weight of 0, which implies strict priorities for each profile. Traditionally, with strict priorities in play, profiles with higher precedence are expected to be awarded all the bandwidth they need at the expense of profiles with lower precedence. However with the Minimum Bandwidth Guarantee configuration, lower precedence profiles can be guaranteed a certain level of performance so they are not starved in the face of bursty, high-priority traffic. ESG Lab capped the total LAN-side bandwidth for the DMS at 5Gbps, with minimum bandwidth guarantees defined on a per-profile basis (each was configured to correspond to an Iperf server port for simplicity) as shown in Table 2. The LAN-side bandwidth was capped in order to test bandwidth allocation under strict bandwidth constraints and to examine whether each profile is able to receive its minimum guarantee.

Table 2: QoS Profiles with Strict Priority

Profile Port Weight Min. Bandwidth Guarantee

0 5001 0 1.00 (bypass)

1 5002 0 0.50

2 5003 0 0.50

3 5004 0 1.00

4 5005 0 0.75

5 5006 0 0.50

6 5007 0 0.50

7 5008 0 0.25

ESG Lab started Iperf connections to servers bound to ports 5001 through 5008. Traffic was allowed to run for approximately five minutes with the QoS profiles enforcing the policies for minimum bandwidth guarantee. After the test, ESG Lab examined the results of the bandwidth allocation via the DMS graphical user interface. As seen in Figure 12, the connections were sorted from highest to lowest bandwidth allocation.

ESG Lab examined the bandwidth share for each port and confirmed that each received a percentage approaching the minimum bandwidth associated with the configured profiles.



Figure 12. QoS Results with Strict Priority

ESG performed a second test to validate the impact of assigning weights to profiles configured in the previous test. Weights imply the use of Deficit Round Robin (DRR) scheduling and allow for weighted allocation of bandwidth across profiles. ESG Lab configured the same Minimum Bandwidth Guarantee values for each profile as was the case in the previous test and kept the same 5Gbps LAN-side cap on traffic being accelerated by the DMS. As shown in Table 3, ESG Lab assigned new weights to the profiles and started Iperf connections to servers bound for ports 5002 through 5005.

Table 3: QoS with Deficit Round Robin

Profile Port Weight Min. Bandwidth Guarantee

0 5001 1 1.00 (bypass)

1 5002 8 0.50

2 5003 8 0.50

3 5004 2 1.00

4 5005 2 0.75

5 5006 1 0.50

6 5007 1 0.50

7 5008 1 0.25



ESG Lab observed the results of weighted profiles and compared the bandwidth changes between strict priority and weighted priority. As expected, the ports with a weight of 8 received the majority of the bandwidth. However, minimum bandwidth guarantees were still maintained even if the guarantee was for a profile with a lower configured weight.

Figure 13. QoS Results with Deficit Round Robin

Why This Matters

Providing improved performance with WAN optimization is a compelling value proposition for companies running services generating heavy data center to data center traffic, but it’s only half the solution. When these services are down, businesses can lose money by the hour or even by the minute. Highly reliable and dependable performance requires effective QoS offerings that provide the granular control needed to ensure service level guarantees for crucial applications and data.

ESG Lab was able to effectively create profiles on the DMS to allocate bandwidth priorities for select ports and observed effective QoS service for prioritized traffic. These prioritization decisions are made at line speed with no impact on traffic performance.



ESG Lab Validation Highlights

Infineta’s Data Mobility Switch was able to achieve consistent levels of data reduction for WAN links varying from 1Gbps to 10Gbps speeds, averaging 85-95% reduction for each test.

The DMS showed significant performance gains in real world tests where migration/replication, large file transfers, and backups were simulated over the WAN.

The DMS was able to maintain successful prioritization of traffic by assigning policies to service classes, providing an effective solution for QoS requirements.

The DMS was able to accelerate 100,000+ TCP connections while effectively filling a multi-Gigabit WAN and significantly increasing the volume of data being sent over the WAN.

Issues to Consider

Currently, there is no global manager for DMS appliances. Each DMS is managed individually by accessing it directly via a command-line interface (CLI) or a web-based graphical user interface (GUI). Infineta has plans to include a global manager in a future release.

The Infineta Acceleration Report provides a summary of the DMS activity for a selected time period. The report is comprehensive, with information on data reduction, optimization, and QoS for each service class, and would be useful for executive management if provided at regular intervals, but currently reports can only be generated in real time. Infineta has plans to include report scheduling support in an upcoming release.



The Bigger Truth

Data growth has not slowed over the last few years; in fact, most organizations report that their data is growing at an increasing rate. This growth presents a number of challenges for IT, not the least of which is managing the storage and movement of data to an offsite location to protect critical business assets. In addition, the adoption of virtualization promotes the automated provisioning of resources as applications and systems gain the ability to run in different locations on demand, putting additional pressure on inter-data-center WANs. Customers are now starting to see limitations with current strategies for application mobility and disaster recovery, and are looking for cost-effective solutions that will accommodate data growth without requiring any changes to existing WAN infrastructure. In fact, more than half of companies surveyed by ESG cited keeping pace with the volume of data they need to protect and the need to reduce backup and recovery times as top concerns for overall data protection strategies.2 Providing efficient and fast WAN communications to additional data hosting locations would help alleviate that concern.

Data center to data center traffic is very different from remote office/branch office traffic. The data reduction/optimization strategies that work for remote users running e-mail and productivity applications cannot scale to the requirements of multi-gigabit WANs supporting workflows such as storage replication and migration, distributed computing, big data transfers, and other high-performance applications. This machine to machine traffic is aggressive, bursty, and latency-sensitive, requiring high bandwidth, low latency WANs.

Infineta Systems delivers a Hyper-scale WAN optimization solution based on multiple technologies that not only reduce the time-to-completion for finite workflows, but also significantly reduce the amount of traffic traversing inter-data center WANs. The DMS’s most unique feature is the Velocity Dedupe Engine, a hardware-based deduplication engine that enables the DMS to maintain the highest levels of data reduction at multi-Gigabit speeds while guaranteeing port to port latencies in the tens of microseconds. Customers can accelerate all high-performance applications traversing inter-data center WANs, including highly latency-sensitive applications such as synchronous replication and VMware vMotion.

ESG Lab tested the DMS and was very impressed with the results. The DMS was able to accelerate a full 10Gbps of simulated data center traffic while deduplicating at greater than 90% with no detectable increase in end-to-end latency. The DMS also provided excellent control, with a sophisticated weighted QoS capability that not only prioritized traffic, but enforced minimum guarantees quite simply and effectively. In simulated real world tests, the DMS enabled a storage system moving 3.2 TB of data across a long-distance (San Jose to Chicago) WAN link to cut migration times by roughly one-third (1/3) while reducing the footprint of the migration traffic by well over 80%.

The Data Mobility Switch boasts high-speed hardware-based inline data deduplication and transport optimization capabilities that can enable synchronous replication and server mobility on an unprecedented scale combined with a plug-and-play appliance that is easy to deploy within an existing infrastructure. ESG Lab has confirmed that Infineta’s Data Mobility Switch is more than capable of satisfying the most demanding data center to data center replication and server mobility needs for businesses of all sizes.

2 Source: ESG Research Report, 2010 Data Protection Trends, April 2010.

http://www.enterprisestrategygroup.com/2010/04/2010-data-protection-trends/



Appendix

Table 4. ESG Lab Test Bed

Data Mobility Switch

DMS-10A (two appliances) Accelerated 20Gbps (In+Out), Total 40Gbps

4x10G/1G data ports

2x10G/1G ISL(inter-DMS) ports

2x1GigE mgmt ports

1.0-GA software image

Apposite Netropy

Netropy 10G 1.1.2 software image

Hosts

4 Servers Linux CentOS 2.6.18 kernel

7 – 240 GB disks

Testing Software Tools

DRBD Version 8.3.8

WGET Version 1.11.4

Rsync Version 2.6.8

Iperf Version 2.0.5

FTP CentOS2.6.18 package

SCP CentOS 2.6.18 package

Change_Block Utility Internally developed tool used to generate high number

of TCP connections

20 Asylum Street | Milford, MA 01757 | Tel:508.482.0188 Fax: 508.482.0128 | www.enterprisestrategygroup.com

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