$ show sitespeedio/sitespeed.io
Sitespeed.io is a mature, open-source web performance testing and monitoring tool that drives real browsers (Chrome, Firefox, Edge, Safari, including mobile) to collect a comprehensive set of performance metrics. It measures Core Web Vitals (LCP, INP, CLS, TTFB, FCP), visual metrics (Speed Index, filmstrip), HAR waterfalls, CPU long tasks, third-party requests, accessibility violations (via axe-core), and sustainability metrics (CO₂ estimates). The tool is used for one-off audits, CI/CD performance budgets, and continuous production monitoring, with results output as rich HTML reports, JSON, JUnit/TAP, and time-series data sent to Graphite/InfluxDB/Grafana. The architecture is plugin-based: a core message queue orchestrates a pipeline of plugins (setup → url → summarize → render). Built-in plugins handle browser testing (via Browsertime), HAR analysis (PageXray), best-practice advice (Coach), accessibility, sustainability, statistical comparison (Mann-Whitney U), performance budgets, and result storage (S3, GCS, SCP, Rsync). The CLI is built with yargs and supports ~600 options organized into topical modules. The tool is primarily delivered as a Docker image (multi-arch amd64/arm64) and an npm package. Key entry points are `bin/sitespeed.js` (CLI), `lib/sitespeed.js` (programmatic API), and `docker/scripts/start.sh` (Docker entrypoint). External dependencies include Browsertime, Coach Core, PageXray, axe-core, and the third-party-web dataset. The project has extensive CI/CD (GitHub Actions), a documentation site built with Eleventy, and a release workflow that publishes npm packages and Docker images with Sigstore signatures and SBOMs.
The LLM identified 5 files worth highlighting for reuse:
Provides deep get, set, and merge operations on nested objects using dot-separated paths. This is a foundational utility used throughout the codebase to avoid lodash-like dependencies. It is self-contained (no internal imports), well-tested, and could be extracted into a standalone npm package for any project needing safe nested object access.
Implements a streaming statistical aggregation pattern (pushStats, summarizeStats) that computes median, percentiles, min, max, and count from a stream of values. This is used to summarize performance metrics across runs. The pattern is generic, self-contained, and reusable in any data pipeline that needs online statistics computation.
A self-contained BFS web crawler that respects robots.txt, handles relative/absolute URLs, and supports include/exclude filters. It uses only standard Node.js fetch and URL parsing. This could be extracted as a standalone crawling library for projects needing a lightweight, configurable crawler without heavy dependencies.
Calculates estimated CO₂ emissions per page view using transfer size and green hosting status. Implements the 1byte model from The Shift Project and uses IEA/Ofgem carbon intensity factors. This is a self-contained, well-documented helper that could be reused in any web sustainability tool or dashboard.
Aggregates raw Browsertime run data into per-url and per-group summaries, computing medians, percentiles, and statistical distributions. It handles multiple iterations, error filtering, and metric extraction. The pattern of collecting raw measurements and producing statistical summaries is reusable in any performance testing framework.