Excellent tour through this topic, here's my best attempt at a tl;dr summary:

1. write a 'Hello World' HTTP server to show how Tokio's async-Rust primitives work for epoll-based I/O;

2. show how the tracing crate ecosystem works to inspect and debug async-runtime tasks;

3. play with converting traces to OpenTelemetry, tokio-console, etc. for different views of the collected data;

4. play with hyper and axum to build a simple HTTP service that makes an upstream HTTP request to the YouTube API;

5. cache results by ID so it can shared across all request-handlers;

6. add 'request coalescing' to prevent multiple concurrent requests from making upstream requests in parallel;

7. fix a bug in the request-coalescing implementation that caused coalesced requests to hang when the in-flight request raised an error.

One word of caution about using any request-coalescing pattern like this on a highly-loaded server: in the case where every request fails to populate the cache (e.g., timeout / not found), you end up in a situation where all requests end up _serialized_ and can quickly lock up a server under constant load. You need to either add a circuit-breaker, or otherwise ensure that _something_ always gets cached in any otherwise-uncacheable edge case (e.g., hit-for-pass in Varnish [1].)

[1] https://info.varnish-software.com/blog/hit-for-pass-varnish-...