Apache Kafka & Real-Time Streaming Engineering Bootcamp Certificate

Checkpoint 1: Run Kafka locally or in a free managed environment; create topics with an explicit partition/retention plan and document ordering guarantees.
Checkpoint 2: Build an idempotent producer and a consumer group; test key-based ordering, offsets, retries and duplicate/failure scenarios.
Checkpoint 3: Introduce Schema Registry with Avro/JSON Schema/Protobuf; evolve a contract and prove backward/forward compatibility behavior.
Checkpoint 4: Connect one external source or sink with Kafka Connect and show replayability plus dead-letter/error handling for bad records.
Checkpoint 5: Build one stateful stream transformation using Kafka Streams or Flink: filter/join/aggregate/window with event-time or state semantics.
Checkpoint 6: Instrument lag, throughput, errors and processing latency; inject broker/consumer/dependency failure and demonstrate safe recovery.

Day 1: Define events, topic ownership, keys, partitions, retention, expected throughput/latency and schema-evolution policy.
Day 2: Implement producers and a scalable consumer group; verify ordering, offset commits, retry behavior and duplicate handling.
Day 3: Add Schema Registry and perform one compatible schema evolution plus one intentionally incompatible test.
Day 4: Integrate an external data source/sink with Kafka Connect and prove replay from a known offset or source position.
Day 5: Add stateful stream processing with a join/window/aggregation and validate event-time/state behavior on edge cases.
Day 6: Add metrics/alerts for lag, throughput, failures and latency; inject a broker/consumer outage or poison event and recover.
Day 7: Publish repo, architecture/event contracts, benchmark, failure timeline, replay proof, dashboards, demo and operations runbook.