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Q&A
Q&APooled threads outlive requests, so forgotten thread-local values can leak data and memory across tasks.
Thread pools reuse worker threads. A ThreadLocal value can remain attached after a request ends, retaining large objects or exposing one request’s context to a later task if it is not overwritten. Clear it in a finally block or use a scoped context mechanism with well-defined propagation and cleanup.
python
8 minA practical guide to request concurrency, connection pools, timeouts, and overload behavior in async Python APIs.
security
5 minSeparate identity proof from session continuity and design browser authentication without exposing credentials or trusting client state.
Q&A
Q&ANo; an adapter can hide an unbounded push queue behind a pull-shaped interface.
A consumer can request one item at a time, but callback-backed sources still need an explicit capacity and overflow policy. Tie early iterator exit and cancellation to resource cleanup.
typescript
8 minUse for-await consumption, cancellation, and iterator return semantics without hiding queues.
Q&A
Q&ACompare post-GC live-set size and object retention paths over time.
High allocation can cause frequent collections while post-GC occupancy remains broadly stable. A leak tends to retain objects that should have become unreachable, so compare heap dumps and dominator paths across time. Check allocation rate, live set, GC logs, and process/container memory together before changing heap settings.
security
8 minSeparate cross-site request forgery from cross-origin response access and validate state changes.
python
8 minFastAPI is fast, but speed is not the same as correctness. Learn where async, background jobs, and bounded concurrency matter in Python services.