This repository implements a live streaming solution on AWS using AWS Elemental MediaLive for transcoding, MediaPackage for packaging, and Amazon CloudFront for content delivery. It is deployed via AWS CloudFormation using the AWS CDK (v2) and includes Lambda-backed custom resources to manage MediaLive inputs, channels, and MediaPackage endpoints. A demo React-based video player is optionally deployed to an S3 bucket behind CloudFront. The solution supports multiple input types (RTP, RTMP, URL pull, MediaConnect) and three encoding profiles (1080p, 720p, 540p). The codebase is well-structured with unit tests, CDK nag suppressions, and a build pipeline for AWS Solutions publishing. It is actively maintained and uses current AWS SDK v3 and Node.js 22 runtimes.
Awesome Video is a curated resource catalog for streaming video technologies, maintained as structured JSON (contents.json) and rendered into both a README and a static documentation site (MkDocs Material) deployed to awesome.video. The catalog spans ~50 hierarchical categories covering HLS, DASH, FFmpeg, codecs (HEVC/VP9/AV1), transport protocols (RIST/SRT/RTMP), players, DRM, QoE, testing, CDN, HDR, subtitles, and learning resources. It is not a runtime application — it is a content curation pipeline: contents.json is the source of truth, convert.rb generates the README, database.json feeds the site's lunr search index, and loader.py imports bookmarks from Raindrop.io. The repo is hybrid in nature: primarily a curated data catalog with a static-site build system around it, rather than a software application or research pipeline. The build pipeline (GitHub Actions) validates the JSON against schema.json, checks external links with awesome_bot, and deploys to GitHub Pages. The curation quality is strong — entries include authoritative references (Netflix TechBlog, DASH-IF specs, Apple WWDC sessions, Xiph test media) — but the supporting code is simple utility scripting with notable weaknesses: hardcoded Raindrop.io credentials in loader.py, inconsistent category identifiers and malformed tag entries in the data, and aging CI dependencies (Python 3.7, jinja2 3.0.3). The repo is actively maintained and the data model (hierarchical categories + multi-tagged project records) is a clean, portable schema for any awesome-list-style content site.