Monitoring Reactive Streams
summary
Measures element throughput checkpoints at chosen graph points and records a per-checkpoint rate (elements/sec) so source, filter and sink rates can be compared. Computes backpressure ratio by timestamping onPull/onPush in an Akka Streams GraphStage API stage (time waiting for downstream requests vs waiting for upstream emits) and emits a histogram showing 0–100% backpressure. Demonstrates a 10ms source vs 250ms mapAsync processor, shows bottlenecked stage and suggests tuning via mapAsync parallelism; library publishes Dropwizard/other backends on Maven.
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chapters (8)
- 0:00Introduction to monitoring
- 1:26Why monitor streaming apps
- 3:13Throughput in reactive streams
- 9:14Back pressure challenges
- 14:09Measuring back pressure
- 20:59Bottleneck diagnosis
- 23:08Key monitoring principles
- 24:11Tools and resources
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