# Event Streams Between Services — Redis Pub/Sub & Streams

Source: https://www.skillbyai.com/en/redis-streams/d-events

> Use streams to publish domain events with an outbox and idempotent consumers.

## A lightweight event bus

Streams work well as a lightweight **event bus** between a modest number of services. A service appends **domain events** (`OrderPlaced`, `PaymentCaptured`) to a stream per domain, such as `events:orders`; each interested service creates its own **consumer group** and processes events at its own pace, with acknowledgements and recovery. New services can start a group from `0` to process the retained history. Reliability rules from event-driven design still apply: write events through a **transactional outbox** so database changes and published events cannot disagree (a relay reads the outbox table and calls `XADD`); include an **event ID** and **type** in each entry; make consumers **idempotent**, since redelivery happens; and keep retention long enough for consumers to recover from outages. Because a stream is one key, all events in it are **ordered** and live on a **single shard**; partition across several streams when one becomes too hot.

## An outbox relay publishing to a stream

The relay marks rows as published only after XADD succeeds.

```python
def relay_outbox(db, r, batch=100):
    rows = db.fetch_all(
        "SELECT id, aggregate_id, type, payload FROM outbox "
        "WHERE published_at IS NULL ORDER BY id LIMIT %s FOR UPDATE SKIP LOCKED", (batch,))
    for row in rows:
        r.xadd("events:orders",
               {"eventId": str(row.id), "type": row.type,
                "aggregateId": row.aggregate_id, "payload": row.payload},
               maxlen=1_000_000, approximate=True)
        db.execute("UPDATE outbox SET published_at = now() WHERE id = %s", (row.id,))
    db.commit()
# a crash between XADD and UPDATE republishes the event; consumers dedupe by eventId
```

## A shared logbook in a control room

Each department writes significant events in the control-room logbook. Every other department keeps its own bookmark and reads new lines when ready; nobody tears pages out, and the oldest pages are archived after a while.

**Quiz:** How should several services each receive every event from the same Redis stream?

- [ ] Use one consumer group shared by all services
- [x] Give each service its own consumer group
- [ ] Use XDEL after each read
- [ ] Publish a copy of each event per service

*Answer:* Give each service its own consumer group. Each group tracks its own position, so every service sees every event.