𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗗𝘂𝗿𝗮𝗯𝗹𝗲 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀
You need dashboards with fresh data. You need them to stay accurate as you grow. Event sourcing solves this.
The flow:
- Producers: Services send domain events.
- Event Bus: Kafka or Kinesis stores events in a log.
- Processors: They read the log and update read models.
- Read Models: Postgres or Redis stores the final metrics.
- Query API: Your dashboard pulls data from here.
Key rules for your design:
- Make events immutable. Never update an event.
- Use idempotency keys. This stops duplicate data.
- Version your schemas. This prevents breaks.
- Use deterministic projections. This keeps data consistent.
How to build it:
- Identify your core events.
- Pick your storage tools.
- Build initial projections for metrics.
- Implement deduplication.
- Create a schema registry.
- Monitor your event lag.
This setup lets you scale and audit your data. You keep a full history of every change.