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Metrics are published to standard formats (Prometheus, CloudWatch, DataDog) with zero configuration.

Batching is automatic—control it via `batch(100)` or `batch({ size: 50, timeoutMs: 1000 })` to trade latency for throughput.

stream.pipe(retry( maxAttempts: 3, backoff: 'exponential' ), timeout(30000)).subscribe(console.log);

Error handling is explicit: catch failures at any stage, log them, and route bad events to a dead-letter queue without stopping the main pipeline.

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The core wavehub object is a lightweight wrapper that manages the lifecycle of your event stream.

await stream.ack(event.id); const pipeline = stream.filter(e => e.amount > 100).map(e => ( ...e, fee: e.amount * 0.03 )).on('error', (err) => logger.error(err));

Batching is automatic—control it via `batch(100)` or `batch({ size: 50, timeoutMs: 1000 })` to trade latency for throughput.