5 Ways to Supercharge Your Performance Testing and Achieve Goals

A Comprehensive Overview of Performance Test Plan and Test Strategy can be discovered in our previous tutorial.

If your company is involved in creating, testing, and implementing software, then you are already using an array of technologies and tools.

=> Click Here To Access Complete Performance Testing Tutorials Series

The vast amount of technology within the enterprise is an even more compelling reason to leverage the work and products already in use to enhance your performance testing and deliver greater value, quicker, and at a lower cost.

Here are five successful strategies to boost your performance testing:

#1) Include Real Client Functional Tests

When assessing the performance of your servers, the goal is to acquire a precise measurement of the users’ experience, not just observing the server behavior.

The objective is to understand the complete sequence of events starting from a user’s click on the browser, through to the request and response with the server, and finally rendering the response in the client browser.

Load Testing mainly focuses on generating heavy traffic to evaluate the server side, giving less attention to the client side. Nonetheless, assessing the client side is critical for accurately gauging user experience.

By integrating Selenium browser automation test scripts (or other functional test scripts) into load testing, you will gain a full understanding of how your system behaves under heavy traffic. While applying a load using your load testing tool, you can concurrently run several browsers from different locations to monitor their activity.

The concept is to pair effectual traffic with several browsers to evaluate real user experience simultaneously.

Ultimately, you can analyze the combined results of server-side load along with the Selenium outcomes.

(Note: Click on any image for an enlarged view)

WebLOAD provides a Selenium extension to collect performance statistics.

#2) Incorporate Mobile Testing

We have surpassed the mobile tipping point, with mobile users now exceeding desktop users. Therefore, ignoring mobile devices in performance tests is unreasonable.

Similar to browser testing covered earlier, the aim is to assess user experience on actual mobile devices while producing load on your system.

Take into account the following:

• Use various mobile devices and networks to evaluate mobile experience.
• Analyze combined data from backend servers under load and actual mobile devices.
• Conduct performance tests on actual mobile devices within your load testing tool.

For instance, WebLOAD integrates with Perfecto Mobile (and can work with any mobile service that provides an appropriate API). While the load test runs, it captures all front-end measurements from Perfecto Mobile, enabling you to see the response time for each transaction from the mobile device to the backend servers and back.

You can also assess mobile device metrics such as CPU usage, memory, and battery usage within WebLOAD. Additionally, you can view side-by-side measurements of device-side and server-side information to thoroughly evaluate the relationship between all test components.

#3) Use APM Tools to Pinpoint Issues

A load testing tool assists in stressing your system to detect issues and usually offers server-side statistics to help identify the general location of the problem.

However, some performance problems require delving into the application to isolate and address the code responsible for slow response times. In such instances, integrating your load testing tool with an Application Performance Monitoring (APM) product like Dynatrace, AppDynamics, or NewRelic speeds up root cause analysis.

This allows you to observe the relationships between all components in real time, such as the web server, application server, database servers, cloud services, among others. By drilling down to the stack trace level, you can swiftly locate the most problematic calls and identify the bottlenecks in your system.

At a software firm, my colleague who leads performance testing shared that his team has reduced root cause analysis by 75% through the combination of load testing and APM!

Ideally, your load testing tool and APM tool should be closely integrated so that you can swiftly switch between them and view events within the same context.

For instance, by tracking an issue and reviewing the report created by your load test tool, you can easily transition to the APM tool that has been monitoring your servers. This allows you to delve into the exact timing and context of the load test to perform a comprehensive analysis of the relevant events.

By drilling down using the APM tool, you can trace the slow response of an extended login mainly to a slow database access.

A close integration between your load testing tool and APM tool can significantly reduce the time for identifying root causes and speed up processes in agile teams and continuous delivery processes.

#4) Engage with DevOps Processes

To keep up with agile development trends and enable faster deployments, performance testing should be expanded to accommodate software delivery methods like Continuous Delivery and DevOps. Achieving performance goals becomes simpler when multiple teams (R&D, QA, DevOps) collaborate and share data.

Companies that have integrated DevOps deploy to production eight times more frequently, have success rates that are two times higher, and resolve issues 12 times faster when problems emerge.

The goal is to automatically and continuously validate the performance of each build and confirm its fitness for production.

Begin by identifying the performance tests that should be automated. For instance, AVG, a provider of antivirus software and internet security services, uses WebLOAD to execute load tests that check the stability and response times of their revenue-critical pages.

While performance tests cover various components, the response time of business-critical areas is automated and regularly tested along with software releases.

In the case of Ellucian, an educational ERP software firm, performance tests validating the scalability of their production infrastructure as a service provider are automated. The performance testing team has integrated load tests into their DevOps processes, enabling them to automatically orchestrate tests against every build in the pipeline.

Pass/fail criteria in performance tests:

Note that prior to automating anything, you need clear definitions for pass/fail criteria in each of your tests. Determining pass/fail criteria in performance tests is usually not as clear-cut as in functional testing.

However, here are some testing aims to consider: These goals help determine the impact of performance changes on following steps in the continuous delivery pipeline.

• Response time – Determine a maximum response time per transaction or an average response time for multiple transactions beyond which a test is deemed failed.
• Error rate – Set an acceptable limit for error rates in transactions.
• Hits, or requests per second – A decrease in hits per second indicates that the server can manage fewer requests, warranting further investigation.
• Average throughput – Monitor the average number of bytes received from the server per second by virtual users to identify server issues sending unnecessary data.
• Server CPU or memory – Monitor CPU or memory usage to prevent potential crashes and slow response times.

The optimal method to trigger tests automatically is by employing Jenkins, the open-source automation platform. With Jenkins, you can use the ‘Build Step’ option and set thresholds to automatically flag poor performance. Another option is Bamboo, which aids in constructing continuous integration, deployment, and delivery processes.

#5) Broaden Analysis Using External Tools

While your performance testing tool may provide robust reporting and analysis capabilities, your reporting and analysis needs could be unique. You may require distinct perspectives or methodologies for presenting test data that aren’t supported by your tool.

To improve performance testing reporting and analysis capabilities, you should be able to export test data and employ external tools for additional handling, segmenting, and examining as required.

This can be as straightforward as using Excel or your in-house system to run calculations and present unique findings, or it might require using a more sophisticated business intelligence (BI) tool like Tableau.

You should be able to export test data using various methods such as SQL queries directly with the results database or utilizing a Restful API.

That concludes our list.

We hope these methods will help you improve your performance testing and reach your performance objectives.

About the Author: This is a guest post by RadView VP Product David Buch. He has led R&D teams in several high-tech companies. Before RadView, David was VP R&D at Softlib and Brightinfo, R&D Manager at HP Software, Director of R&D at Mercury Interactive. David holds a BA with high honors in computer science and economics from Bar Ilan University and is a MAMRAM (The Israeli Army Computer Corps) graduate.

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