Apache Kafka Tutorial 0/111 lessons ~6 min read Lesson 38
JSON Schema
What is JSON Schema?
Course progress0%
Focus
9 guided sections
Practice signal
Examples included
Career prep
Foundation builder
Introduction
What is JSON Schema? JSON Schema validates JSON event contracts while keeping payloads human-readable.
Understanding the topic
What happens — JSON Schema:
- Define connector plugin and config.
- Source: external system → Kafka.
- Sink: Kafka → external system.
- Schema Registry validates event contracts.
| Term | Description |
|---|---|
| Connector | Plugin for source or sink. |
| Task | Parallel unit of connector work. |
| Schema Registry | Central schema store + compatibility. |
| Subject | Schema name tied to topic. |
Visual explanation
Pipeline view:
text
Source system↓ Kafka ConnectTopic + Schema Registry↓Sink connector / consumer↓Data warehouse/search/app
Step-by-step explanation
- Deploy Connect — Connect worker cluster.
- Configure — Connector JSON properties.
- Run tasks — Parallel ingest/egress.
- Monitor — Task status and errors.
Informative example
Example:
bash
kafka-topics --bootstrap-server localhost:9092 --create --topic json-schema --partitions 6 --replication-factor 3kafka-console-producer --bootstrap-server localhost:9092 --topic json-schemakafka-console-consumer --bootstrap-server localhost:9092 --topic json-schema --from-beginningkafka-consumer-groups --bootstrap-server localhost:9092 --describe --group json-schema-service
Execution workflow
1JSON Schema workflow
1 / 4Deploy Connect
Connect worker cluster.
Best practices
- Register schemas and enforce compatibility before production deploys.
- Use connectors for commodity integration instead of writing one-off sync jobs.
- Document schema owners and evolution rules.
- Monitor connector task failures and dead-letter records.
Common mistakes
- Treating schema-less events as flexible when they are actually fragile.
- Ignoring connector offset and retry behavior.
- Changing field meaning without changing schema or docs.
Summary
JSON Schema — Treat schemas like APIs: version them, test compatibility in CI, and assign ownership.
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