Setting Up Redis Streams Consumer Groups for Reliable Message Processing
Learn how to create a Redis Streams consumer group, consume messages, acknowledge them, monitor pending entries, and recover from consumer failures using XCLAIM.
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redisBackpressure Bottleneck in Akka Streams: Identifying Buffer Overflows and Latency Issues
Diagnosing a Backpressure Bottleneck We need to determine why throughput drops and latency spikes in an Akka Streams pipeline. The suspect is a backpressure signal propagating from a downstream stage, potentially causing upstream stages to pause and queues to grow. Constraints include the default 16‑element buffer per stage, the configured overflow strategy,
akkaTurbo Streams + Rails Time Zone Helpers: Date Fragment Updates
Goal: Ensure that date/time fragments rendered by Rails view helpers display the correct offset after a Turbo Stream update when a user changes their preferred time zone. Constraint: Turbo Streams inserts server‑generated HTML without performing any additional client‑side time‑zone conversion, and its cache‑busting flags do not automatically invalidate cache
rails
turbo