July 2023 Summaries

React Server Components (RSCs) are a new feature in React that allow developers to define where their code runs - on the server or client-side. This provides more flexibility and can lead to smaller bundle sizes and faster execution, particularly for data-heavy sites. However, there are some limitations, such as compatibility issues with CSS-in-JS and React Context. Adopting RSCs incrementally in a real-life codebase involves adding the "use client" directive to the root of an app, moving it lower in the rendering tree, and adopting advanced patterns when performance issues arise.

Timed metadata is a feature that provides additional context for media content by connecting the timeline of the media to related information. This can include features like "Skip Recap" or "Skip Intro" buttons, interactive transcripts, and educational video content with questions. Mux Player allows users to add out-of-band timed metadata in the form of CuePoints, which have two properties: a time for when the CuePoint begins in the media and a generic value that can store any JSON serializable information. This feature is useful for augmenting, contextualizing, and enriching users' media experiences.

The Mux Data team migrated from a shared, distributed Riak key-value (KV) store to the BadgerDB embedded KV store, resulting in lower operational costs, boosted scalability, and reduced latency. This change was made due to challenges with scaling up and down in response to changing load on their databases. The team found that managing the number of Riak nodes was a manual process and that it led to poor utilization of resources. They also experienced issues with stream processing latency as Riak often became a write-throughput bottleneck during large live events. By scoping the cache to a Kafka topic partition, they were able to follow a "Shared Nothing" architecture, which allowed them to optimize for the performance of frequently occurring activities and reduce operational costs. The team chose BadgerDB due to its high performance writes and reads, control over garbage collection frequency, granular data layout on disk, and compression capabilities. Since migrating from Riak to BadgerDB, they have seen significantly lower latency and been able to handle larger-scale events without any scaling concerns.