Last updated on Apr 15, 2024
- All
- Test Engineering
Powered by AI and the LinkedIn community
1
Define your goals and criteria
2
Collect and visualize your data
3
Analyze and interpret your data
4
Identify and diagnose the issues
5
Recommend and implement the solutions
6
Review and refine your process
Be the first to add your personal experience
7
Here’s what else to consider
Be the first to add your personal experience
Performance testing is a crucial part of ensuring that your software meets the expected standards of speed, reliability, and scalability. But how do you make sense of the data and metrics that you collect from your performance tests? How do you identify the bottlenecks, errors, and areas for improvement? In this article, we will share some tips and best practices for analyzing and interpreting performance test results and metrics.
Top experts in this article
Selected by the community from 11 contributions. Learn more
Earn a Community Top Voice badge
Add to collaborative articles to get recognized for your expertise on your profile. Learn more
- Suresh Yerolkar People First | Creating Abundance | Quality Matters | CSM® | 15x Community Top Voice | QA Engineering | Quality…
8
-
5
- Zouhair B. Leader en Tests Fonctionnels et Automatisation Confirmé | Consultant et Formateur Selenium | ISTQB® CTFL - Scrum | A4Q®…
4
1 Define your goals and criteria
Before you run your performance tests, you need to have a clear idea of what you want to achieve and how you will measure it. You should define your performance goals and criteria based on your business requirements, user expectations, and industry benchmarks. For example, you might want to set goals for response time, throughput, resource utilization, error rate, and availability. You should also specify the acceptable range or threshold for each metric, as well as the priority and severity of any deviations.
Help others by sharing more (125 characters min.)
- Zouhair B. Leader en Tests Fonctionnels et Automatisation Confirmé | Consultant et Formateur Selenium | ISTQB® CTFL - Scrum | A4Q® Selenium Tester Certified
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
L'analyse et l'interprétation des résultats des tests de performance sont essentielles pour garantir la stabilité d'une application. Je débute par examiner en détail des métriques clés telles que le temps de réponse, le débit et l'utilisation des ressources, en les comparant avec des seuils prédéfinis. L'utilisation d'outils de visualisation comme Grafana offre une représentation graphique claire des tendances et des anomalies. L'interprétation des résultats comprend une analyse approfondie des goulots d'étranglement, des pics de charge et des zones de dégradation de la performance. En collaboration étroite avec l'équipe de développement pour identifier des recommandations d'optimisation.
Translated
LikeLike
Celebrate
Support
Love
Insightful
Funny
4
- Sangita M. Transforming businesses workflows and minimize operational costs through Multimodal Generative AI and Conversational AI solutions | BFSI | Customer Experience | Intelligent Chatbot | AI Agents
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Analyzing and interpreting performance test results involves examining various metrics such as response time, throughput, error rates, and resource utilization. By comparing these metrics against predefined thresholds or benchmarks, we can identify performance bottlenecks, pinpoint areas for optimization, and make informed decisions to enhance system performance and scalability. Additionally, trend analysis over multiple test runs can provide insights into system stability and the impact of changes over time.
LikeLike
Celebrate
See AlsoWhat evaluation testing results meanPercentile | Definition, Quartile, & FactsDifference Between Percentage and Percentile: Know the differenceHow Percentiles Work (and Why They're Better Than Averages)Support
Love
Insightful
Funny
2
-
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
It can be highly relevant to do performance testing even on performance for which there is no specification (e.g. target or acceptance criteria).Performance testing is essential in increasing your understanding of your design (or product), and therefore also provides a data basis for decision on what performance metrics to establish specifications for.Focusing only on performance metrics that you have, up front, decided to establish specifications for is likely to ultimately leave you blindsided as to the actual workings and performance of your design, giving raise to problems such as poor yield or high complaints rates in production.
LikeLike
Celebrate
Support
Love
Insightful
Funny
2
2 Collect and visualize your data
Once you have your goals and criteria, you need to collect and visualize your data from your performance tests. You should use a reliable and consistent tool or framework that can capture and store your data in a structured and accessible format. You should also use a dashboard or a report that can display your data in a clear and meaningful way. You should use graphs, charts, tables, and other visual elements that can help you compare, contrast, and correlate your data across different scenarios, parameters, and time periods.
Help others by sharing more (125 characters min.)
- Suresh Yerolkar People First | Creating Abundance | Quality Matters | CSM® | 15x Community Top Voice | QA Engineering | Quality Auditing | Driving Quality Growth | QA COE | Delivery Excellence
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Purpose-Driven Metrics: - I focus on metrics that align with our goals. Whether it’s response time, throughput, or error rates, each metric should serve a purpose.Tool Selection: - I’ve found that using tools like Grafana or Kibana helps capture and store data effectively. These tools provide flexibility and scalability.Custom Dashboards: - I create custom dashboards tailored to our specific needs. Visualizing trends over time and comparing scenarios becomes easier.Storytelling Visuals: - Graphs and charts are my storytelling tools. A well-designed graph can convey more than rows of raw data.Thresholds and Alerts: - I set thresholds and configure alerts. When a metric crosses a critical point, we’re notified immediately.
LikeLike
Celebrate
Support
Love
Insightful
Funny
8
- Reshma Narkhede LWD 25th September | Serving Notice Period | ISTQB Advance Level Certified Engineer | Insurance
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
To analyze and interpret performance test results and metrics, I collect data from various sources such as load tests, stress tests, and user experience monitoring. I then visualize the data using graphs and charts to identify trends, patterns, and outliers. By comparing the metrics against predefined thresholds and benchmarks, I can determine the system's performance, scalability, and potential bottlenecks. Additionally, I conduct root cause analysis to understand the underlying reasons for any performance issues and make recommendations for optimization and improvement.
LikeLike
Celebrate
Support
Love
Insightful
Funny
3
- Md Maruf Rahman ISTQB® Certified Tester | QA Automation Engineer | Cypress | WebdriverIO | Selenium |
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Analyzing and interpreting performance test results and metrics involves collecting and visualizing data to gain actionable insights. This process begins with gathering comprehensive performance data, including response times, throughput, and error rates. Visualizing this data through graphs, charts, and dashboards helps identify patterns and trends. Comparing current results to baseline or previous tests provides context for performance improvements or regressions. Interpretation involves understanding bottlenecks, such as high response times or resource constraints, and their impact on system performance. With clear visualization and analysis, testers can make informed decisions on optimizations.
LikeLike
Celebrate
Support
Love
Insightful
Funny
2
3 Analyze and interpret your data
After you have your data and visuals, you need to analyze and interpret your data to understand the performance of your software. You should look for patterns, trends, outliers, and anomalies that can indicate the strengths and weaknesses of your software. You should also compare your data with your goals and criteria to see if you met, exceeded, or failed them. You should use statistical methods and techniques to calculate and validate your data, such as mean, median, standard deviation, confidence interval, and hypothesis testing.
Help others by sharing more (125 characters min.)
- Suresh Yerolkar People First | Creating Abundance | Quality Matters | CSM® | 15x Community Top Voice | QA Engineering | Quality Auditing | Driving Quality Growth | QA COE | Delivery Excellence
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Outliers Investigation: - I hunt for outliers. Are they genuine anomalies or data errors? Investigating outliers often reveals hidden issues.Statistical Rigor: - I apply statistical techniques. For instance, calculating the mean, median, and standard deviation helps me understand the central tendency and variability.Hypothesis Testing: - When assessing performance improvements, I use hypothesis testing. Did that code optimization really make a difference? A well-designed A/B test provides answers.User-Centric Metrics: - Beyond technical metrics, I consider user experience. High throughput doesn’t matter if users face frustrating delays.
LikeLike
Celebrate
Support
Love
Insightful
Funny
7
-
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
In my experience, trying out various kinds of visualisations is very much a part of the analysis and interpretation phase.Descriptive statistics and exploratory data analysis are key skills to apply to your data – starting with the simple question of whether you can use the normal distribution assumption on the set of data.
LikeLike
Celebrate
Support
Love
Insightful
Funny
2
4 Identify and diagnose the issues
Based on your analysis and interpretation, you need to identify and diagnose the issues that affect your software performance. You should focus on the metrics that are most relevant and important for your software, such as response time, throughput, resource utilization, error rate, and availability. You should also trace the root cause of the issues to the specific components, modules, or functions of your software that are responsible for them. You should use tools and methods that can help you isolate and debug the issues, such as logs, profilers, monitors, and traces.
Help others by sharing more (125 characters min.)
-
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
As test engineers, we need to also be humble.Our analysis of the data does not identify "issues", but it can help us identify questions. Whenever something does not look "right" (whether the performance seems a bit too imperfect or a bit too perfect), we start with "why", which must necessarily engage our stakeholders.Testing is often a complex interaction between a design (or product) and test equipment, and in order to understand why data do not seem right, we will usually need to engage with specialists on the other aspects – product design and test equipment.
LikeLike
Celebrate
Support
Love
Insightful
Funny
5
- Suresh Yerolkar People First | Creating Abundance | Quality Matters | CSM® | 15x Community Top Voice | QA Engineering | Quality Auditing | Driving Quality Growth | QA COE | Delivery Excellence
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Prioritize Metrics: - I focus on key metrics like response time, throughput, and error rate. These provide a clear picture of system behavior.Resource Utilization: - I delve into resource utilization patterns. High CPU or memory usage might indicate bottlenecks.Availability: - I keep an eye on system availability. Downtime affects user experience and business.Root Cause Investigation: - When issues arise, I trace them back to specific components. For instance, a database query causing slow response.Tooling: - I leverage tools like logs, profilers, and traces. They reveal hidden issues and guide debugging efforts.
LikeLike
Celebrate
Support
Love
Insightful
Funny
6
5 Recommend and implement the solutions
Finally, based on your diagnosis, you need to recommend and implement the solutions that can improve your software performance. You should prioritize the solutions based on the impact and urgency of the issues, as well as the feasibility and cost of the solutions. You should also test and validate the solutions to ensure that they work as expected and do not introduce new issues or side effects. You should document and communicate your solutions to the relevant stakeholders, such as developers, managers, and clients.
Help others by sharing more (125 characters min.)
- Suresh Yerolkar People First | Creating Abundance | Quality Matters | CSM® | 15x Community Top Voice | QA Engineering | Quality Auditing | Driving Quality Growth | QA COE | Delivery Excellence
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Collaborate with Experts: - I engage with developers, architects, and system administrators. Their insights are invaluable for understanding root causes.Data-Driven Decisions: - I rely on data, not assumptions. Metrics like throughput, latency, and error rates guide my decisions.Cost-Effective Solutions: - I consider feasibility and cost. Sometimes, simple code optimizations yield significant gains.Validation Testing: - Before rolling out solutions, I rigorously test them. A/B testing, load testing, and soak testing ensure stability.Clear Documentation: - I document the issue, solution, and rationale. Transparency helps stakeholders understand the impact.
LikeLike
Celebrate
Support
Love
Insightful
Funny
6
6 Review and refine your process
As a performance tester, you should not stop at implementing the solutions. You should also review and refine your process of analyzing and interpreting performance test results and metrics. You should evaluate the effectiveness and efficiency of your process, as well as the quality and accuracy of your data and metrics. You should also seek feedback and suggestions from your peers, clients, and users to improve your process. You should also keep yourself updated with the latest trends, tools, and techniques in performance testing and analysis.
Help others by sharing more (125 characters min.)
7 Here’s what else to consider
This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?
Help others by sharing more (125 characters min.)
Test Engineering
Test Engineering
+ Follow
Rate this article
We created this article with the help of AI. What do you think of it?
It’s great It’s not so great
Thanks for your feedback
Your feedback is private. Like or react to bring the conversation to your network.
Tell us more
Tell us why you didn’t like this article.
If you think something in this article goes against our Professional Community Policies, please let us know.
We appreciate you letting us know. Though we’re unable to respond directly, your feedback helps us improve this experience for everyone.
If you think this goes against our Professional Community Policies, please let us know.
More articles on Test Engineering
No more previous content
- How do you analyze test result trends to identify root causes of failures? 22 contributions
- How do you balance penetration testing and vulnerability testing in your test engineering process?
- What are some best practices for test data management and governance? 9 contributions
- What are the benefits and challenges of using A/B testing as a user feedback method in test engineering? 13 contributions
- What are some tools or techniques that help you write test cases faster and easier? 13 contributions
No more next content
More relevant reading
- System Development What steps can you take to ensure your software meets performance requirements?
- Technical Analysis How can you stay ahead of technical analysis software trends?
- Operations Research How do you measure and improve the performance and efficiency of your OR software and tools?
- Quality Assurance How do you identify defects using boundary value analysis?