𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗔𝗻 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺
You need a data platform for real-time analytics. It must handle streaming data with low latency. It must stay reliable.
Build your system with these five layers:
- Ingest layer: Producers push events.
- Streaming layer: A durable log keeps data in order.
- Processing layer: Processors compute metrics.
- Serving layer: Fast storage feeds your dashboards.
- Observability layer: One system for metrics, logs, and traces.
Follow these rules:
- Plan monitoring before you build features.
- Every component must emit health signals.
- Use a schema registry to stop bad data.
- Use circuit breakers to handle failures.
Step by step guide:
- Identify your core data streams.
- Deploy a broker like Kafka.
- Create a processor for windowed counts.
- Store results in a time-series database.
- Add OpenTelemetry for end-to-end visibility.
Measure success with these goals:
- Ingestion latency under 200ms.
- Data freshness within 60 seconds.
- Low alert noise.