Top 10 resources to learn Kafka + event-driven systems (practical, for people shipping code):

1. Apache Kafka docs (http://kafka.apache.org)
   Start with producers/consumers, consumer groups, partitioning, and delivery semantics. Most “mysteries” are in the basics.

2. Confluent docs + tutorials (http://docs.confluent.io)
   Clear operational guidance: configs that matter, Schema Registry, Connect, ksqlDB, and real examples.

3. Book: Kafka: The Definitive Guide (O’Reilly)
   Good mental model for partitions, replication, ISR, acks, and why throughput vs latency tradeoffs exist.

4. Book: Designing Event-Driven Systems (Ben Stopford)
   How to think in events, streams vs logs, choreography vs orchestration, and where teams get stuck.

5. Course: Confluent Developer courses
   Hands-on labs that feel close to production work: serializers, consumer lag, rebalancing, idempotent producers.

6. Blog: Confluent blog (reliability + ops posts)
   Solid deep dives on rebalancing, exactly-once, and config gotchas like min.insync.replicas and http://linger.ms.

7. Blog: Uber Engineering (Kafka at scale stories)
   Practical failure modes: multi-DC realities, backpressure, incident patterns, and what breaks under load.

8. Blog: LinkedIn Engineering (original Kafka lineage + evolution)
   Good context on why Kafka looks the way it does and which constraints shaped the design.

9. Practice project: run a local cluster + break it
   Docker Compose Kafka + UI. Then: kill a broker, throttle disk, change partitions, watch consumer lag, tune batch.size/linger.ms, verify reprocessing.

10. Practice project: build an outbox + idempotent consumer
    Postgres outbox table + Debezium CDC into Kafka, consumer writes with dedupe key. Teaches the stuff interviews skip: retries, ordering, and “at least once” reality.

Apache Kafka

Source: https://kafka.apache.org/ Learn MoreDownload

More than 80% of all Fortune 100 companies trust, and use Apache Kafka.

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Manufacturing

10 OUT OF 10

Transportation

8 OUT OF 10

Energy and Utilities

10 OUT OF 10

Above is a snapshot of the number of top-ten largest companies using Kafka, per-industry.

See full list

Core capabilitieshttps://kafka.apache.org/#core-capabilities

Kafka boasts core capabilities that are battle tested and ready to power businesses in the digital world.

High Throughput

Deliver messages at network limited throughput using a cluster of machines with latencies as low as 2ms.

Scalable

Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing.

Permanent Storage

Store streams of data safely in a distributed, durable, fault-tolerant cluster.

High Availability

Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions.

Built-in Stream Processing

Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing.

Connect to almost anything

Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more.

Trust and Ease of Usehttps://kafka.apache.org/#trust-and-ease-of-use

Kafka is simple to use and is trusted by thousands of organizations around the world.

Mission Critical

Support mission-critical use cases with guaranteed ordering, zero message loss, and efficient exactly-once processing.

Trusted By Thousands of Orgs

Thousands of organizations use Kafka, from internet giants to car manufacturers to stock exchanges. More than 5 million unique lifetime downloads.

Vast User Community

Kafka is one of the five most active projects of the Apache Software Foundation, with hundreds of meetups around the world.

Client Libraries

Read, write and process streams of events in a vast array of programming languages.

Rich Online Resources

Rich documentation, online training, guided tutorials, videos, sample projects, Stack overflow, etc.

Large Ecosystem Open Source Tools

Large ecosystem of open source tools: Leverage a vast array of community-driven tooling.