How do you determine performance requirements for a web app?

1. CPU usage CPU usage affects the responsiveness of an application. High spikes in CPU usage might indicate several problems. 2. Memory usage Memory usage is also an important application performance metric. High memory usage indicates high resource consumption in the server. 3. Requests per minute and bytes per request: It's equally important to track the amount of data the application handles during every request. 4. Latency and uptime: Higher latency has a direct effect on the load time of an application.

Begin by understanding the business and user expectations for the web app. Collaborate with stakeholders to identify performance goals, considering factors like response time, throughput, and concurrent user capacity. Align these goals with the overall project objectives to ensure a clear understanding of the desired performance outcomes.

Things that should be done - Focus on the requirement - Enforcing the product quality - Continuous evaluation and optimization of the process

Determining performance requirements for a web app involves considering factors like expected user load, response time, scalability, and resource utilization. Conduct performance testing to analyze and optimize aspects such as server response, database queries, and page load times. Regular monitoring and feedback from users can help refine these requirements over time.

There is no one-size-fits-all industry standard for setting performance and response goals for an app. But there's a general performance goals for every app, 2-3 sec for web load, 500ms API response time, and 99,9% uptime. The rest is to be adjusted per application requirements.

Specify the key performance metrics that will be used to evaluate the web app's performance. Common metrics include response time, server resource utilization, error rates, and throughput. Tailor the selection of metrics to align with the identified performance goals and the specific requirements of the web app.

Performance metrics are quantifiable values used to track a system's efficiency and effectiveness. They include: Response Time: Time taken for a request to return a response. Throughput: Requests processed by the system per unit time. Load Capacity: Maximum user load the system can handle without performance dropping below an acceptable level. Resource Utilization: Percentage of system resources (CPU, memory, disk space, etc.) used. Scalability: System's ability to maintain performance as demand increases.

- From abstract to accountable: Translate goals into measurable metrics like throughput, response time, error rate, and availability. Numbers talk! - Units and thresholds: Give your metrics context. Define units (seconds, requests per minute) and set clear thresholds (acceptable error rate, ideal load times). - Prioritize like a pro: Not all metrics are created equal. Rank them based on their impact on your goals. Speed matters, but so does error-free uptime! - Tailored to your tune: Don't copy-paste generic metrics. Choose ones that resonate with your app's unique purpose and user experience. - Dynamic dance: As your app and goals evolve, so should your metrics. Adapt and refine them to keep your performance optimization on track.

In my view: to be able to write performance tests one would need a value to test against. This is why metrics are useful. Metrics should be robust enough to offer certainty and flexible enough to adapt to business needs. Each goal identified should have its own metrics. If we consider page loading time: Robust would mean a clearly defined metric - “Time between user clicks on button and new page is opened and content rendered” has clearly defined actions. “Time needed for content to load” is not clear enough. Users might not be happy to see content being rendered and page changing shape in front of their eyes. Flexibility for me means understanding that some users might prefer to wait a bit longer instead of paying extra for a service.

Determining performance requirements for a web app involves defining quantitative metrics that assess how effectively it meets performance goals. Common metrics include throughput, utilization, error rate, and availability. Specify units, values, and thresholds for each metric. Prioritize metrics based on their significance to your performance goals. This approach ensures a clear understanding of the app's performance expectations and facilitates effective monitoring and optimization.

Identify existing bottlenecks and constraints. Use tools like monitoring systems to collect data/ gather data on resource utilization.

Before conducting performance tests, establish baseline measurements for the web app's current performance. This baseline serves as a reference point for evaluating improvements or identifying performance regressions during and after testing. Capture data on the app's behavior under normal conditions to set a benchmark.

- Benchmark, don't guess: Don't fly blind! Gather performance data from past tests, industry averages, and even user expectations. - History whispers lessons: Analyze historical data. Did previous versions shine or stumble? Learn from their performance stories. - Competitive compass: Check what your rivals are up to. Benchmark against similar apps in your domain, not just generic standards. - Users hold the key: Listen to their whispers. Surveys, interviews, and reviews reveal their speed and reliability expectations. - Evolving baseline, growing success: Don't set it and forget it! Stay dynamic. Update your baseline as your app and expectations evolve.

creating performance baselines, which are standards representing your web app's current or expected performance. Collect data from various sources like past tests, industry benchmarks, and user feedback. Compare this data to identify areas for improvement. This process helps ensure your web app meets performance expectations and allows for enhancements.

The next stage involves evaluating the present performance of the web application in standard circumstances, utilizing the specified metrics. This serves as a benchmark for assessing the web app's performance both before and following any modifications or enhancements. It is crucial to document and validate these performance baselines.

Develop realistic performance scenarios that simulate various user interactions and system conditions. Consider scenarios such as peak usage, typical usage patterns, and worst-case scenarios. Design diverse test cases to cover a range of user activities, ensuring comprehensive coverage of the web app's functionality.

Il manque à cette étape la clarification des ressources disponibles: Spécialistes disponibles dans l'équipe Outils à disposition. Faut-il impliquer une ressource externe. Durée à planifier resp. disponible pour les actions prévues. Mesures de communication vers les utilisateurs. Création des données nécessaires, par exemple un grand nombre de comptes de test avec leurs mots de passe. Mettre en place les outils de mesure nécessaires, par exemple, en demandant au responsable base de données *DBA* d'activer le moniteur des ressources Aviser les responsables des applications des mesures prévues afin que le test ne soit pas bloqué par les services de sécurité qui constatent une charge exceptionnelle du système

1. Mirror real-world traffic: Craft scenarios like "normal load" (daily users) and "peak load" (holiday rush) to see how your app handles typical and surge conditions. 2. Push the limits with stress: Don't be afraid to overload! Design "stress load" scenarios beyond capacity to uncover potential bottlenecks and weaknesses. 3. Define the details: Each scenario needs parameters, variables, and inputs – user numbers, actions, and think times. Make it realistic! 4. Orchestrate the flow: Determine the frequency, duration, and sequence of your scenarios. Will normal load be interrupted by peak bursts? 5. Adapt and evolve: As your app and user base grow, so should your scenarios. Keep them dynamic and relevant to stay ahead of the curve.

create performance scenarios—test cases or scripts mimicking real-world conditions impacting your web app's performance. Examples include normal load (average usage), peak load (maximum load during special events), and stress load (testing limits). Define parameters, variables, and inputs for each scenario. Specify the frequency, duration, and sequence of scenarios to comprehensively assess your web app's performance under various conditions.

Create realistic scenarios that simulate actual user behavior. Consider scenarios for peak loads, different user profiles, and varying usage patterns.

Tools of the trade: Choose wisely! Select performance testing tools, frameworks, and platforms tailor-made for your app's needs. Scenarios come alive: Run the designed scenarios - load, stress, and endurance - mimicking real-world user traffic and interactions. Metrics in motion: Capture and monitor every beat! Collect performance data like response times, throughput, errors, and resource utilization. Results revealed: Watch the story unfold! Analyze the test outcomes, identifying bottlenecks, strengths, and opportunities for improvement. Continuous optimization: Don't let the curtain fall! Use the insights to refine your app, performance benchmarks, and testing strategies for lasting success.

Implement the designed performance scenarios by executing performance tests. Utilize testing tools and frameworks to simulate user behavior, generate load, and monitor the app's performance metrics. Execute tests under controlled conditions to assess the app's responsiveness, stability, and scalability.

Choose suitable tools, frameworks, and platforms for your web app. During the tests, closely monitor and record the results and outcomes. Examples of performance tests include evaluating how your web app handles various loads, stresses, and sustained usage. This process helps identify strengths and weaknesses, ensuring your web app meets performance expectations.

Use testing tools to simulate user interactions and monitor system behavior. Conduct tests in a controlled environment that mirrors the production setup.

The fifth phase involves conducting performance tests utilizing the devised scenarios, employing diverse tools and methods such as load testing, stress testing, and endurance testing. These tests should be carried out in a controlled and realistic setting, with thorough recording and monitoring of the test results.

It is important to analyze performance results because this proves how well the web app is doing. Findings shows if the web app performance meets the requirements that were defined earlier. Examples may include metrics such as page load time, server response time, and user interactions. You are also able to analyze if the tool passes or fails the test requirements or any challenges or deviations you encountered. There are various tools like Google PageSpeed Insights and Chrome DevTools that come in handy.

Analyze the performance test results to evaluate the web app's adherence to the defined performance goals and metrics. Identify areas of improvement, potential bottlenecks, and performance anomalies. Consider the results in the context of the established baselines to determine the effectiveness of optimizations or enhancements.

Assess whether the app meets, exceeds, or falls short of established metrics and baselines. Identify bottlenecks or issues causing performance degradation or failure. Offer recommendations or actions for optimization. Compare and evaluate performance metrics for each scenario. Communicate results and recommendations clearly to stakeholders and users, ensuring a comprehensive understanding of your web app's performance.

Evaluating performance results is crucial as it demonstrates the effectiveness of the web application. The analysis determines whether the web app's performance aligns with the pre-established requirements. This assessment encompasses metrics like page load time, server response time, and user interactions. Additionally, it allows for an examination of whether the tool meets or falls short of the test requirements, and addresses any challenges or deviations encountered during the process.

Your application’s legal requirements, such as Service Level Agreements (SLAs) that specify uptime and performance standards. Your application’s business goals, such as conversion rates, user retention, and customer satisfaction. Your application’s competitive landscape, such as how fast and responsive your rivals’ web applications are. Your application’s user expectations, such as how long they are willing to wait for a page to load or an action to complete.