Software Performance
Load Testing Real React Applications for Production Performance
<p>In this talk, we'll explore how we built comprehensive load testing for React applications at Mattermost, achieving 100,000 concurrent users in production-like environments. We'll begin by revealing why traditional API testing missed critical browser issues that only emerged at scale. Next, we'll demonstrate our open-source tool that uses Playwright to run thousands of real browsers, measuring React-specific metrics like component render times, memory leaks, and state management bottlenecks. Finally, we'll share the optimization journey that reduced browser memory and enabled true production readiness, ensuring our React application performs flawlessly for enterprise customers.</p>
Weitere Infos
| Live Stream | https://live.fosdem.org/watch/h1301 |
|---|---|
| Format | devroom |
| Sprache | Englisch |
Weitere Sessions
| 01.02.26 |
<p>Nowadays, in the software industry, we already have a lot of ways to improve performance of our applications: compilers become better and better each year in the optimization field, we have a lot of tools like Linux perf and Intel VTune to analyze performance. Even algorithms are still improving in various domains! But how many of these improvements are actually adopted in the industry, and how difficult it is to adopt them in reality? That's an interesting question!</p> <p>In this talk, I ...
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| 01.02.26 |
<p>Relying only on nvidia-smi is like measuring highway usage by checking if any car is present, not how many lanes are full. </p> <p>This talk reveals the metrics nvidia-smi doesn't show and introduces open source tools that expose actual GPU efficiency metrics.</p> <p>We'll cover:</p> <ol> <li>Why GPU Utilization is not same as GPU Efficiency.</li> <li>Deep dive into relevant key metrics: SM metrics, Tensor Core metrics, Memory metrics explained.</li> <li>Practical gpu profiling and monitoring ...
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| 01.02.26 |
<p>In scientific computing on supercomputers, performance should be king. Today’s rapidly diversifying High-Performance Computing (HPC) landscape makes this increasingly difficult to achieve however...</p> <p>Modern supercomputers rely heavily on open source software, from a Linux-based operating system to scientific applications and their vast dependency stacks. A decade ago, HPC systems were relatively homogeneous: Intel CPUs, a fast interconnect like Infininand, and a shared filesystem. ...
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| 01.02.26 |
<p>Slow performance is often a major blocker of new visionary applications in scientific computing and related fields, regardless of whether it is embedded or distributed computing. This issue is becoming more and more challenging to tackle as it is no longer enough to do only algorithmic optimisations, only hardware optimisations, or only (operating) system optimisations: all of them need to be considered together.</p> <p>Architecting full-stack computer systems customised for a use case comes ...
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| 01.02.26 |
<p>Reliable performance measurement remains an unsolved problem across most open source projects. Benchmarks are often an afterthought, and when they aren't they can be noisy, non-repeatable, and hard to act on.</p> <p>This talk shares lessons learned from building a large-scale benchmarking system at Datadog and shows how small fixes can make a big difference: controlling environmental noise, designing benchmarks, interpreting results with sound statistical methods, and more.</p> <p>Attendees ...
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| 01.02.26 |
<p><a href="https://www.mercurial-scm.org/">Mercurial</a> is a distributed version control system whose codebase combines Python, C and Rust. Over its twenty years of development, significant effort has been put into its scaling and overall performance.</p> <p>In the recent 7.2 version, the performance of exchanging data between repositories (e.g. <code>push</code> and <code>pull</code>) has been significantly improved, with some of our most complicated benchmark cases moving from almost four ...
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| 01.02.26 |
<p>Database vendors often engage in fierce competition on system performance – in the 1980s, they even had their "benchmark wars". The creation of the TPC, a non-profit organization that defines standard benchmarks and supervises their use through rigorous audits, spelled an end to the benchmark wars and helped drive innovation on performance in relational database management systems.</p> <p>TPC served as a model for defining database benchmarks, including the Linked Data Benchmark Council ...
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