What are the best practices for debugging slow web applications?

Debugging slow web applications can be challenging, but using the Measure and Analyze approaches can help identify and resolve performance issues effectively. - In measuring page load time, I recommend you use tools like Google PageSpeed Insights, GTmetrix, or Lighthouse to get detailed reports on page load performance. These tools work well on our site too. - In measuring API response times, useful tools such as New Relic or AppDynamics monitor API performance over time. - In user interactions, tools like Google Analytics or Mixpanel measure user engagement and identify areas where users experience delays or issues.

The initial step in resolving sluggish web applications is to assess and analyze their speed and performance. You can employ tools like browser dev tools, network analyzers, performance audits, and monitoring to gather data on load times, rendering, resource sizes, latency, throughput, and errors. This data helps identify the sources of slowness and where improvements are needed. To debug slow web applications effectively, you must begin by accurately measuring and analyzing their performance.

1st step to debug a slow web application is to analyse the performance bottle necks by simply using the browser developer tools: - Check Network Activities to identify if the backend calls was slowing the site down. - Check Javascript performance & Memory Usage to identify if the front end was causing the slowness. Then we can apply specific optimisation strategies to resolve these bottle necks. E.g. - Optimising DB queries to speed up backend. - Caching to speedup both backend & frontend. - Refactor the webpage from server-side rendering to SPA or vice versa depending on the context.

I can recommend using OpenTelemetry, which can significantly enhance the debugging of slow web applications by providing comprehensive insights into performance through automatic and custom instrumentation. It facilitates distributed tracing to pinpoint slowdowns across services, collects vital performance metrics, and correlates logs with traces for detailed error analysis. The integration with various backend tools enables effective visualization and alerting, aiding in the identification and prioritization of bottlenecks. This observability, combined with other tools and methods like browser dev tools and network analyzers, forms a robust strategy for optimizing web application performance and user experience.

When debugging slow web applications, it's crucial to adopt a systematic approach. Start by measuring and analyzing the application's performance. Utilize profiling tools and performance monitoring solutions to identify bottlenecks and resource-intensive areas. Focus on metrics like page load times, server response times, and network requests. Dive into the code using browser developer tools or server-side profilers to pinpoint specific issues. Additionally, leverage performance testing to simulate different user scenarios and load conditions, uncovering performance discrepancies. A comprehensive understanding of your application's performance metrics is the first step in diagnosing and addressing slow performance effectively.

Optimizing frontend requires many activities, but the very first principle to follow is to load resource size as small as possible during above-content-fold page load. Any sections below content fold shall be loaded lazily, including any api calls to make or images/resources to load can happen at the time of user scrolling to that section. This will ensure the initial page laod is as lean as possible and potentially can achieve aggressive SLAs like less than 3 seconds. Other optimizations to look into are - loading all resources from CDN instead of origin servers; Enabling gzip/brotli compression; Loading resources from http2 protocol as much as possible; minify and compress scripts to save space; loading sprite icons etc.

Optimizing the FE of a slow web application is essential for improving performance. Start by minimizing the use of large, unoptimized images and files that can slow down page loading. Implement browser caching and CDNs to reduce server load and decrease latency. Employ asynchronous loading for non-essential resources and defer JavaScript execution to prevent rendering bottlenecks. Opt for lazy loading of images and videos to load content progressively as users scroll. Employ efficient CSS and JavaScript coding practices, reducing unnecessary code and optimizing critical rendering paths. By streamlining the front-end, you can significantly enhance the user experience and address slow performance issues in web applications.

There are many techniques that can be applied to optimize the frontend. That’s the easy part. You can find that on ChatGPT or the internet. The trick is knowing which one to use, and how to apply it. And how do you know which one ? The answer to that is in the previous step where you “Measure & Analyze”. That analysis will give in signals or indicators on where the bottleneck which will help guide your solution.

Things I keep in mind when it comes to optimizing front-end: 1. Minimize number of requests to the server 2. Set appropriate caching 3. Compress and resize images 4. Use CDNs 5. Ensure web is responsive 6. Limit the number of third-party scripts and services to only those that are essential. 7. Remove redundant or unused codes and resources 8. Continuously test the performance of web app

We can use CDNs for static content to users, reducing latency and improving loading times. also Implement caching on different levels (browser, server, and CDN) to reduce the needs to create or retrieve data on each request.

Here's a checklist of things to look for in your backend code that can degrade performance: - Bad algorithms that become slower as the dataset grows (O(n^2) or worse) - Calling the database more than required (N+1 problem) - Not using database indexes

Profile the server side code to identify bottlenecks and optimize it. Techniques like database indexing, asynchronous processing, and code profiling can help.

Use a reverse proxy. A reverse proxy can serve static assets from a CDN and cache dynamic content. This can improve the performance and security of your application. Optimize your database queries. Avoid using unnecessary SELECT statements and subqueries. Use indexes to improve the performance of your queries. Use a profiling tool. A profiling tool can help you to identify performance bottlenecks in your code. Use a monitoring tool. A monitoring tool can help you to monitor the performance and health of your application.

Here are some additional tips for optimizing the back-end of a web application: Use a framework. A framework such as Laravel, Django, or Ruby on Rails can provide you with a lot of functionality out of the box, such as database access, authentication, and routing. This can save you a lot of time and effort, and it can also help you to write more efficient and maintainable code. Use a dependency manager. A dependency manager such as Composer or npm can help you to install and manage the dependencies for your application. This can help you to keep your application up to date and to avoid conflicts between dependencies.

Optimizing the back-end of a slow web application involves several steps to enhance its performance. Begin by examining database queries to identify and resolve any inefficiencies; this may entail indexing optimization and query refinement. Implement caching mechanisms to store frequently accessed data, reducing the load on the database and improving response times. Consider horizontal scaling by distributing the application load across multiple servers or instances to handle increased traffic effectively. Investigate server-side issues like memory leaks or resource bottlenecks that can slow down the application, addressing them as necessary.

It's essential to have a baseline value before beginning your test. Measure the performance of the thing you are trying to optimize before testing the new version. Once you have the test results, you can decide if your solution is better or worse. Speed doesn't have to be the only criterion. You can also look at allocation, number of queries, reduced load on the database, etc.

In addition to the mentioned methods, you can further enhance your testing and debugging process for web applications by considering load testing to evaluate performance under heavy traffic, monitoring tools to continuously track application performance, and incorporating user feedback during the testing phase to ensure it meets real-world user expectations

I think it's important to have specific performance focused tests in your regular build pipeline. The results of this should be recorded over time so you can measure the effect as you add more features and complexity. It's also useful to set a threshold for your performance tests in your CI pipeline so that you can fail a build that has too much of a negative impact on performance. Ideally these tests use something close to production-like data and common or important user journeys.

Of all the steps mentioned above, the ”Measure & Analyze” is the most important step. That’s because it’s difficult to know if something has improved or has gotten “better” if you don’t measure it.