With Ayoka’s application development services, companies are able to monitor and improve the performance of their core business processes, including supply chain management systems, customer relationship management systems, and e-commerce systems used by B2B and B2C customers. Ayoka will develop an SAP performance management solution for companies that rely on SAP.

For the solution below, performance refers to the ability to fulfill customer’s expectations for response time and throughput, such as viewing products or purchasing them from the shopping cart.

SAP Performance Management Solution – Business Problem:

A large manufacturer and distributor of consumer products internally developed e-commerce systems using SAP’s ABAP programming language. As online traffic increased, with more B2B and B2C customers making purchases through the SAP driven website, customers began to experience significant performance issues. Ayoka was contracted to design and implement an SAP performance management solution that would improve their websites’ performance and users’ experience.

This company was using multiple websites on the same back-end SAP server. SAP requires every web page on their site to be associated with a corresponding SAP transaction. This requires a log in to be initiated by the browser each time a user browses to a new page. Therefore, as the user navigates through the client website, each request is handled as a separate call to the SAP server. This setup caused a high stress on the back-end server during peak web traffic hours.

SAP Performance Management Solution – Technical Resolution:

In order to reduce the load on the SAP server, Ayoka developed an SAP performance management solution that used server-side caching. This allowed pages with static data elements and relatively static server responses to remain in the cache, alleviating the load issue. Through the SAP performance management solution, it was no longer necessary to send a request to SAP for static pages.

Load Testing Results:

To begin load testing for the SAP performance management solution and generate the maximum load on the client’s SAP server, Ayoka utilized JMeter to simulate the client-defined number of users. Table 1 below shows the actions and expected results of the simulated user while browsing through the client’s two websites (website 1 and website 2). The simulated user begins on the website home page, then proceeds to click on category and product links allowing for user think time (a designated period of time between user actions). The two websites are tested concurrently with 1100 virtual users on website 1 and 1000 user’s on website 2. Over a period of 2100 seconds, each of the 2100 virtual users are loaded one per second. The websites are tested with the SAP performance management solution (caching solution) and without (non-caching solution).

Table 1: Actions and Expected Results of Simulated Users (SAP Performance Management Solution)

Step Description Expected Result User Think
Time(s)
1 Open website home page Home page is displayed 1
2 Click on a category link Category page is displayed 10
3 Click on a product link Product details page is displayed 10
4 Click on a static page Page is displayed 10

The results from load testing both websites with and without the SAP performance management solution (caching solution) are displayed below in Tables 2 and 3. Overall, the Ayoka SAP performance management solution made the average page load time three times faster than the non-cached solution. In addition, the implementation of the SAP performance management solution resulted in a drop in the average error rate from 20.18% to 0.0%.

Table 2*: Baseline Load Testing Results for SAP Performance Management Solution (Non-Cached site)

Website 1 (1100 simulated users)
Sample Label Report Count Average (ms) Report Median Report 90% Line Report Min Report Max Report Error % Report Rate Report Bandwith
Home Page 1100 242 224 428 38 2576 12.18 1.00 26.61
Click Category Link 1100 451 260 774 162 5092 1.64 1.00 63.85
Click Product Link 1100 320 222 455 92 4740 1.00 1.00 54.42
Click Static Page 1100 335 142 777 26 4780 0.55 1.00 33.48
TOTAL 6600 313 172 767 0 5092 35.89 5.83 175.64
Website 2 (1100 simulated users)
Sample Label Report Count Average (ms) Report Median Report 90% Line Report Min Report Max Report Error % Report Rate Report Bandwith
Home Page 1000 238 214 426 38 2123 12.30 1.00 17.96
Click Category Link 1000 542 437 763 277 3923 0.70 1.00 80.20
Click Product Link 1000 433 387 736 193 4177 0.40 1.00 63.19
TOTAL 3000 404 402 723 38 4177 4.47 2.94 158.09

Table 3*: Load Testing Results for SAP Performance Management Solution (Cached site)

Website 1 (1100 simulated users)
Sample Label Report Count Average (ms) Report Median Report 90% Line Report Min Report Max Report Error % Report Rate Report Bandwith
Home Page 1100 133 128 149 110 453 0.00 1.00 89.57
Click Category Link 1100 122 112 144 105 720 0.00 1.00 56.28
Click Product Link 1100 138 131 159 110 617 0.00 1.00 48.99
Click Static Page 1100 111 102 129 95 681 0.00 1.00 28.69
TOTAL 6600 114 110 141 70 720 0.00 5.83 217.51
Website 2 (1100 simulated users)
Sample Label Report Count Average (ms) Report Median Report 90% Line Report Min Report Max Report Error % Report Rate Report Bandwith
Home Page 1000 134 128 155 106 1352 0.00 1.00 74.77
Click Category Link 1000 137 126 163 107 507 0.00 1.00 64.44
Click Product Link 1000 134 124 154 109 690 0.00 1.00 47.95
TOTAL 3000 135 126 156 106 1352 0.00 2.94 183.44

SAP Performance Management Solution – ROI:

The solution allowed the e-commerce system to accommodate more web traffic during peak online shopping season. It decreased page load time and enhanced the user’s online experience. In addition, the SAP performance management solution enabled the manufacturer to reduce the number of customers switching from online transactions to telephone and reduce attrition, i.e. decrease the number of users abandoning sales due to unsatisfying performance.

* Below are definitions of the terms used in the solution results tables above.

Term Definition
Report Count Number of simulated users
Average (ms) The average page load time for a set of results
Report Median The time in the middle of a set of results
Report 90% Line 90% of the samples took no more than this time
Report Min The shortest time for the samples with the same label
Report Max The longest time for the samples with the same label
Report Error % Percent of request with errors
Report Rate Requests per second
Report Bandwidth Throughput measure in kilobyte per second

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