Data EngineeringIn progress

Data Pipeline Platform

Kafka-based event pipeline built in explicit tiers. Producer, consumer, and metrics are working; the reliability tiers are not built yet.

Technology Stack

Apache KafkaStreamingPythonETLPostgreSQLStorageDocker ComposeLocal stackPrometheusMetrics

Where it actually is

The project is structured as four tiers, and I am partway through the second. T0 (local stack plus an end-to-end tracer-bullet flow) works. T1 adds a dead letter queue, schema evolution, backpressure handling, and basic observability. The producer and consumer with metrics are committed, the rest is in progress.

T2 (multi-source ingestion, backfills, hot/cold storage, orchestration) and T3 (reliability drills, SLOs, scale tests, a capacity model) are planned and not started.

Why the tiers are public

It would be easy to describe this as a system 'handling millions of events per day'. It is not doing that, and I would rather the page match the repository.

The tier structure is the honest version and I think it is also the more useful one: it states what reliability work is done, what is next, and what 'finished' means. Throughput numbers go on this page when T3 scale tests produce them.