Here's how you can effectively evaluate the performance of complex applications.

I agree. Baseline metrics provide a reference point to compare future performance test results. Additionally, they help in understanding the current health of the system under normal load conditions.

To evaluate the performance of a complex application, start by establishing baseline metrics for key performance indicators (KPIs) under normal conditions. Conduct load and stress testing using tools like JMeter to simulate real-world and extreme scenarios, and use performance profiling to identify bottlenecks and inefficiencies. Implement continuous monitoring and logging with tools like Prometheus to track real-time metrics and identify issues. Finally, benchmark your application's performance against industry standards and optimize based on the insights gained from testing and monitoring.

This article is very much a how-to, but very vague enough that is sounds like it was written by a language model and can encompass just about any stack. A good article presents an issue or goal and then proceeds to solve it, it creates a narrative to follow that is missing in this draft. People who would need this information are not gonna have the abstract experience to really grasp it, so i highly recommend building a narrative example. This is an article, not an API doc, it can be interesting and have flavour. :)

The start of a project is also a great time to collect use cases and results of user interactions. You can compare these with later results to ensure you have not introduced issues of correctness into the code base. Also, look at the current performance, and set reasonable expectations as to the performance improvements, and the criteria when you expect to be finished.

Using RUM data, You may use it to discover a specific feature is causing confusion among users. By redesigning the interface for that feature, overall user satisfaction and task completion rates can be improved drastically.

Acho útil e de fácil entendimento diria mesmo intuitivo, nunca tive dificuldade na utilização não sendo eu entendida em plataformas digitais dou apenas uma mera utilizadora.

We must increase our comprehension of RUM and KPI interpretation. For example, using a legacy system that can process files and give the user a comprehensive report in about six hours. A challenger in this field creates a system that requires four hours or more to process a file. The user experience is this two-hour difference. Although the final customer will be happy, the user experience will be subpar if it takes more than six hours.

Improving user experience (UX) involves several key strategies: Simplify navigation to make the interface intuitive and easy to use, optimize load times by minimizing code and using CDNs, and ensure responsive design across devices. Maintain a consistent UI design to aid familiarity, gather and analyze user feedback to address pain points, and conduct A/B testing to refine interface effectiveness. Ensure accessibility for all users, implement clear error handling, and provide seamless onboarding experiences. Monitor user behavior through analytics to understand interaction patterns and identify workflow bottlenecks, enabling continuous refinement and enhancement of the application's usability and overall user satisfaction.

Very Very useful to make delightful software or apps. In one of my past projects of iOS application, during a code profiling session, we identified a loop that was significantly slowing down the app. Optimizing this loop resulted in a noticeable performance boost. I would recommend if we profile our code on a regular / periodic basis, we can identify bottlenecks much earlier then causing the issues.

Code profiling plays a important role in improving user experience (UX) by identifying and addressing performance bottlenecks and inefficiencies within the application's codebase. By conducting code profiling, developers can pinpoint specific areas where the application may be slow or inefficient, such as slow database queries, CPU-intensive operations, or memory leaks. Addressing these issues through optimization and refactoring can lead to faster load times, smoother interactions, and overall improved responsiveness for users. Code profiling tools provide detailed insights into how the application utilizes resources, helping developers prioritize optimizations that directly enhance UX by ensuring the application runs efficiently.

Totally agree, Simulating high user demand with load testing tools has allowed us to identify scalability issues and make necessary infrastructure and code adjustments. But I also disagree that conducting load tests without REALISTIC usage patterns can yield misleading results. It's crucial to mimic real-world scenarios as closely as possible. Else it can influence the over engineering kind of scenario in many use cases

Load testing helps in application performance by simulating realistic user traffic and stress conditions. It identifies performance bottlenecks, such as slow response times or resource limitations, under varying loads. This testing enables optimization of infrastructure and code to handle peak usage efficiently, ensuring that the application maintains responsiveness and stability. By proactively addressing these issues, load testing enhances overall performance and user satisfaction, mitigating risks of downtime or degraded user experience during high-demand periods.

Regular infrastructure review with relevant performance metrics helps to identify potential bottleneck across multi-tier software system. There is tendency among many developers to scale horizontally mitigating current blockers as it provides ease of implementation, However this inclination hides the issue shortly only to reappear at higher severity. Each layer should ideally be benchmarked for optimal configuration as adjustments in soft limits to leverage performance holds priority over demand of additional hardware resources. As concurrent traffic and load scales with time, constant infrastucture review helps to instantiate effectively thus reducing cost and allocation of efforts.

The performance of your application, complex or otherwise, requires that you are always monitoring performance. It will help you identify your "high-traffic" times, to help you establish adequate support. It will help you design your performance tests before you go to Production. Finally, you can identify trends (if you're getting lower performance numbers, maybe your latest changes have slowed things down). All of this rides on your ability to do Continual Monitoring.