How Performance Testing Improves User Experience

Slow is the new downtime. How do you make sure your API won't be slow in production? 𝗟𝗼𝗮𝗱 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 Simulate the expected number of concurrent users to understand how it performs under normal and peak loads. Tools: Postman or Apache JMeter. 𝗖𝗮𝗽𝗮𝗰𝗶𝘁𝘆 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 Determine how many users your application can handle before performance starts to degrade. Tools: NeoLoad 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 𝗧𝗲𝘀𝘁𝗶𝗻𝗴  Measure the response times under load conditions. It is super important if your applications require real-time responsiveness. Tools: Postman can also help here. 𝗗𝗮𝘁𝗮 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 Populate your testing environment with data volumes that mock what you expect in production. You will understand how data management and database interactions impact performance. Tools: Datagen or Mockaroo. 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗣𝗿𝗼𝗳𝗶𝗹𝗶𝗻𝗴 Set monitoring tools to track application performance metrics. Profiling helps identify memory leaks, long-running queries, and other inefficiencies. Tools: New Relic, Datadog, or Prometheus These 5 things will help you to simulate your production environment. They are not perfect, but they will help you to: - Learn and fix performance bottlenecks early. - Build a reliable API. - Have a more reliable user experience. Are you flying blind or testing like in production?

We care a lot about user experience at Duolingo and monitor it via a number of app performance metrics. App performance is especially a challenge on Android because of the breadth of the ecosystem of devices. In 2021, we ran a cross-company Android reboot effort to improve the code architecture and improve latency. We then set latency and performance guardrails to prevent new changes from slowing down the app. Despite our best efforts, though, latency crept up. Early in 2024, one of our data scientists, Daniel Distler, was able to demonstrate that improving latency in some key parts of the user journey would drive solid increases in DAUs (daily active users), one of our main company metrics. This was the nudge we needed to re-invest in the effort. We created a cross-company tiger team to work on improving Android performance. Throughout the year, 20 software engineers participated. In 2024, the team ran 200+ A/B tests on Android performance and delivered remarkable results: - Entry-level device app open conversion jumped from 91% to 94.7% - Entry-level device users experiencing 5+ second app open latency dropped from 39% to just 8% - Hundreds of thousands of DAU gains were directly attributable to these performance enhancements and we expect the actual long-term impact was even larger What work proved most impactful? - Almost half of our DAU impact came from improving code efficiency - Another 20% of impact came from optimizing network requests  - Another chunk came from deferring non-critical work to happen later in key flows - Baseline profiles took a lot of time to get right, but sped up application start-up by 30% Want to learn more? Check out Chenglai Huang and Michael Huang’s blog post: https://lnkd.in/dni58Hez #engineering

Introducing Insights in Chrome DevTools Performance panel! Many web developers know the power of the Chrome DevTools Performance panel, but navigating its wealth of data to pinpoint issues can be daunting. While tools like Lighthouse provide great summaries, they often lack the context of when and where issues occur within a full performance trace. On the Chrome team we're bridging this gap with the new "Insights sidebar" directly within the Performance panel. Read all about it: https://lnkd.in/gGd3bkPw This exciting feature integrates Lighthouse-style analysis right into your workflow. After recording a performance trace, the Insights sidebar appears, offering actionable recommendations. Crucially, it doesn't just list potential problems but highlights relevant events and overlays explanations directly on the performance timeline. Hover over an insight like "LCP by phase," "Render blocking requests" or "Layout shift culprits" to visually connect the suggestion to the specific moments in your trace. The sidebar covers key areas like Largest Contentful Paint (LCP) optimization (including phase breakdowns and request discovery), Interaction to Next Paint (INP) analysis (like DOM size impact and forced reflows), Cumulative Layout Shift (CLS) culprits, and general page load issues such as third-party impact and image optimization. It's designed to make performance debugging more intuitive by linking high-level insights to the granular data, helping you improve Core Web Vitals and overall user experience more effectively. Check out the Insights sidebar in the latest Chrome versions (it's been evolving since Chrome 131!). It’s a fantastic step towards making complex performance analysis more accessible. Give it a try on your next performance audit! #softwareengineering #programming #ai

Netflix recently published that: Less JavaScript means more user engagement. Here’s why: Netflix recently shared a fascinating case study about improving their web performance. They found there's no one-size-fits-all solution for web performance optimization. The team focused on optimizing their logged-out homepage, where new users come to sign up. Initially, the page took 7 seconds to load on 3G connections, which was far too long. They made a bold move by removing React from the client side and switching to vanilla JavaScript. This decision reduced their JavaScript bundle size by 200kB. The results were impressive. Loading time and Time-to-Interactive decreased by 50% for desktop users accessing Netflix’s homepage. The simplified version worked just as well with basic HTML and JavaScript. They didn't completely abandon React though. Instead, they came up with a clever solution. While users were on the homepage, Netflix prefetched React and other resources needed for subsequent pages. This prefetching strategy reduced Time-to-Interactive by 30% for users navigating to other pages. It proved to be a low-risk way to improve performance without rewriting code. The team learned that even popular libraries like React aren't always necessary. Sometimes, simpler solutions work better. The homepage still uses React for server-side rendering to maintain consistency. The improvements had real business impact. Users started clicking the sign-up button more frequently, showing how better performance directly affects user engagement. I write one post for software engineers everyday at 10. Follow Pratik Daga so that you don't miss them.