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Performance Benchmark for Online Store Traffic Volume - Hitachi Solutions Ecommerce

This document lays out the performance benchmark results for the Hitachi Solutions Ecommerce application.

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Performance Benchmark for Online Store Traffic Volume - Hitachi Solutions Ecommerce

  1. 1. Performance Benchmark for Online Store Traffic Volume – Hitachi Solutions Ecommerce
  2. 2. Global: Toronto Manila Pune Singapore Bangalore Kuala Lump Page | 2 Hitachi Solutions Ecommerce serves 125,000 page views and 3,500 orders in an hour on commodity hardware Hitachi conducted a benchmark to simulate online store performance for demonstrating how catalog browsing and order placement processes scale under a heavy load with a large size database on commodity hardware. A 4-core server with 16GB RAM and a single SATA hard drive in RAID1 array was able to serve 125,000 page views and 3,500 orders in an hour. 2 web servers with the same database server will handle up to 250,000 page views and 7,000 orders per hour. HIGH LEVEL RESULT SUMMARY The benchmark demonstrated that the online store architecture scales significantly without any performance bottlenecks.  125,000 pages viewed in an hour.  3,500 orders of 3 lines each received in an hour.  3,700 search requests served in an hour, each request resulted in an average of 2,500 search results. We simulated the following activities in the environment. The diagram below shows the activity flow that we simulated in the environment. Fig.1.0 Hitachi Solutions Ecommerce Transaction Flow THROUGHPUT MEASUREMENTS Scenarios Concurrent users load Peak hours Volume per minute Page View Count 1100 1 2080 Order Placement 1100 1 58 Keyword Search 1100 1 61 RESPONSETIME MEASUREMENTS Request Avg. Response (ms) Home Page 83 Keyword Search 275 Category Product Listing 84 Product Details 391 Add Item to Cart 271 View Cart 19 Login 569 Shipping Address Information 261 Shipping Quotation 301 Billing Address Information 137 Payment Information 865 Order Completion 44 The average checkout response time was 3 seconds. UTILIZATION SUMMARY This section shows the performance characteristics of application server and database server instances that were running on workloads. Application Server Statistics Measure Benchmark Average CPU Utilization 80% Peak Memory Utilization 39% Average Response Time 297ms Database Server Statistics Measure Benchmark Average CPU Utilization 19% Peak Memory Utilization 84% Average Response Time 12ms HARDWARE CONFIGURATIONS Application Server Hardware Specification
  3. 3. USA: Los Angeles Silicon Valley Page | 3  Single Application Server hosting IIS 7 and Hitachi Solutions Ecommerce Online store  Microsoft Virtual Machine  X64-based PC  Intel(R) Xeon(R) CPU X7550 @ 2.00GHz 1994 Mhz, 4 Core(s), 4 Logical Processor(s)  Windows Server 2008 R2 Enterprise 64 bit  16GB RAM Database Server Hardware Specification  Single Database Server hosting SQL Server 2008 R2  Dell PowerEdge R410  X64-based PC  Intel(R) Xeon(R) CPU E5506 @ 2.13GHz 2128 Mhz, 4 Core(s), 4 Logical Processor(s)  Microsoft Windows Server 2008 Enterprise SP1  16GB RAM Database Disk Configuration  SATA RAID1 HDD 750GB  2 Local Disks in RAID1  7,200 RPM (Revolutions Per Minute) BENCHMARK DATA COMPOSITION The benchmark ran on a 16GB database (excludes logs) running with uncompressed data. The system was configured as follows:  500,000 items in the catalog across 800 categories  500,000 customers with 2,500,000 addresses  175,000 price trade agreements  10,000 promotional offers  800,000 orders with total 2,000,000 lines BENCHMARK METHODOLOGY The Load Storm was used to generate load, which simulates real user behaviors like logging in, purchasing, clicking links, and browsing the site. The New Relic was used to monitor the environment that records necessary measurements during the load. Fig.2.0 Performance Benchmark Runtime Architecture Measurements were recorded on single application and database servers. The benchmarks were taken when the concurrency reached to the steady state. The steady state was maintained for an hour with linear load in repeated runs. Scenarios were considered successful when the deviation among consecutive 3 runs for response time and throughput was 3% or less. RECOMMENDATIONS Given the low utilization of the database server, additional web servers can be used to scale up the capacity of the online store. For example:  250,000 page views can be served and 7,000 orders can be placed in an hour using 2 web servers and the same database server.  37,000 search requests can be served in an hour using 10 web servers and the same database server.
  4. 4. USA: Los Angeles Silicon Valley Page | 4 DISCLAIMER These benchmark results were performed in a controlled lab environment in which Hitachi Solutions Ecommerce was the only running application (that is, no other applications were running on these servers). Performance tests and ratings reflect the approximate performance of Hitachi Solutions Ecommerce. Any difference in system hardware, software design or configuration, customizations, transaction mix, data composition, or indexes may affect actual performance. The transaction mix and data composition affects sizing and hardware requirements. Inherently, Hitachi believes that the Hitachi Solutions Ecommerce stack and application are built to scale, and changes to the code base need to go through localized performance testing. A customer or partner should consult other sources of information to evaluate the performance of systems or components they consider purchasing.

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