Web Perf Hero: Amir Sarabadani
Today we recognize Amir’s work over the past six months which cut latencies by half!
Tag: web performance (page 2)
Web Perf Hero: Siddharth VP
Siddharth VP (@SD0001) implemented Package files for Gadgets in T198758. This enables gadget developers to bundle JSON files, unpacked via…
How we improved performance of a batch process from two days to five minutes
The Growth team recently improved the performance of a script that prepares data for usage in the mentor dashboard. Learn about how they decreased the average runtime of the script from more than 48 hours to less than five minutes.
Web Perf Hero: Umherirrender
@Umherirrender has initiated and carried out significant improvements to the performance of MediaWiki user preferences (T278650, T58633 , and T291748).…
Profiling PHP in production at scale
We built an efficient sampling profiler for PHP. It runs continually in production on live requests, and generates trace logs and flame graphs.
Web performance case study: Wikipedia page previews
Preview popups are common and requires careful scripting and styling; they can generate useful learning about performance as a reference for other front-end tasks.
Impact of using HTTP connection pooling for PHP applications at scale
This post explores the challenges of running PHP applications at a large scale and discusses the effect of using Envoy on MediaWiki applications.
Wikimedia’s CDN up to 2018: Varnish and IPSec
The 1st of a 3 part series that will describe some of the changes, which included replacing Varnish with Apache Traffic Server (ATS) as the on-disk HTTP cache component of the CDN.
How we contributed Paint Timing API to WebKit
The story of how we decided to commission the implementation of Paint Timing API, a feature that lets us observe web performance from an end-user perspective. This web browser feature tells us at what point in time content started to appear on the screen for a visitor.
Measuring the performance of Wikipedia visitors’ devices
We have been collecting microbenchmark scores for over a year. This lets us see the long-term evolution of our audience as a whole. The information gives us an idea of how fast device/operating system/browser environments improve on their own.