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Learn Apache Kafka, the event streaming platform behind countless data pipelines and microservice systems. See exactly how topics, partitions, offsets, consumer groups, replication and retention work by running examples on a small Kafka simulator in your browser, with the real Python client code alongside. Also covers schemas, Kafka Connect, stream processing, how Kafka compares with RabbitMQ, and running Kafka in production.

  • 14 days
  • ~30 min / day
  • Intermediate
  • Free account required
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The big picture

Everything you'll cover, and how it fits together.

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Day by day

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  1. 1
    Day 1Up next 30 min

    Why Event Streaming?

    Direct calls versus events, and what makes Kafka a log rather than a queue.

    CouplingEventsLogs vs queues
  2. 2
    Day 2 30 min

    Topics, Partitions & Brokers

    How Kafka stores events: append-only partitions spread across brokers.

    TopicsPartitionsOffsets
  3. 3
    Day 3 30 min

    Producers & Keys

    How a producer chooses a partition, and why keys decide ordering.

    KeysPartitioningOrdering
  4. 4
    Day 4 30 min

    Consumers & Offsets

    Reading events, tracking progress and replaying history.

    PollingCommittingReplay
  5. 5
    Day 5 30 min

    Consumer Groups

    Share the work between consumers and survive rebalances.

    GroupsAssignmentRebalancing
  6. 6
    Day 6 30 min

    Delivery Guarantees

    At-most-once, at-least-once and exactly-once, in practice.

    Commit orderDuplicatesIdempotence
  7. 7
    Day 7 30 min

    Replication & Fault Tolerance

    Leaders, followers, in-sync replicas and what acks really means.

    ReplicasISRacks
  8. 8
    Day 8 30 min

    Retention & Compaction

    How long Kafka keeps data, and keeping only the latest value per key.

    RetentionCompactionTombstones
  9. 9
    Day 9 30 min

    Schemas & Serialisation

    Agree on the shape of events and change it safely.

    JSON & AvroSchema RegistryCompatibility
  10. 10
    Day 10 30 min

    Kafka Connect

    Move data between Kafka and databases or other systems without code.

    Source connectorsSink connectorsCDC
  11. 11
    Day 11 30 min

    Stream Processing

    Filter, transform, join and aggregate events as they arrive.

    StatelessStatefulWindows
  12. 12
    Day 12 30 min

    Kafka vs RabbitMQ & Patterns

    When to use which, plus dead-letter topics and the outbox pattern.

    RabbitMQDead lettersOutbox
  13. 13
    Day 13 30 min

    Running Kafka

    Consumer lag, choosing partition counts, monitoring and KRaft.

    LagSizingKRaft
  14. 14
    Day 14 30 min

    Capstone: Order Processing

    Design and simulate an event-driven order system end to end.

    DesignSimulateFailure drills