In the case of distributed, high-throughput string interning, horizontal scaling can be achieved by breaking up one large keyspace that requires strict coordination into billions of smaller keyspaces that can be randomly load-balanced across.
Read the post →By examining the limits of reasonable user behavior and embracing imperfection for users who go beyond it, we can continue to provide service that meets the expectations of users without sacrificing scalability of the system.
Jetstream is a streaming service that consumes an AT Proto Sync Firehose and converts it into lightweight, filterable, friendly JSON, allowing us to live tail all posts on Bluesky for as little as ~850 MB/day
HLS (HTTP Live Streaming) is basically just a bunch of text files in a trench coat pointing at a handful of itty-bitty seconds-long video files
Roaring Bitmaps offer an even more efficient way to store and query an entire social graph, fitting the entire network of 5.5M users and 164M+ follows into a ~1.6GB SQLite DB on disk.
We need a fast way to query multiple potentially large sets of data on-demand at interactive speeds.
When running on baremetal, however, we found two key limitations of the Go runtime so far.
Using request coalescing, we can serve the 200,000 user strong thundering herd by making only one request to our DB, so every other identical request wait for the results from the first request to hit the cache before they resolve.
Instead, let's structure the query as a Common Table Expression and leverage the power of doing significantly less work to make things go faster.
Postgres uses an internal table called 'pg_statistic' to keep track of some metadata on all tables in the DB.
ChatGPT has incredible potential for accelerating your development flow.
I think we’ll soon find that LLMs have strong parallels with Cloud Compute that will ensure they stay affordable and accessible resources, allowing the next generation of software projects and companies to thrive.
A closer examination of these contrasting trajectories reveals how the research-driven innovation behind LLMs can triumph over consumerism-driven hype of the Metaverse that puts the cart of "monetizable experiences" before the horse of technology capable of sustaining them.