DCONTMOD.DCONT-08 · v1.0

Catch breakage at PR,
not in
production.

8 micro-lessons · ~78 min · Real Docker images

DCONT · CI GATE · LIVE
SCHEMA COMPAT
95%
FIELD NULLS
72%
SEMVER POLICY
90%
DEPRECATION WIN
88%
PII CLASSIFY
45%
CDC FRESHNESS
81%
BREAKING DELTA
38%
DCONTDATA ENGINEERINGTRENDING

Data Contracts

Schema-as-API for data teams — breakage caught at PR time, not in production.

WHY THIS MATTERS · ODCS V3.1.0 · LF AI & DATA · 50+ PRODUCTION IMPLEMENTATIONS · GARTNER HYPE CYCLE 2025
ODCS v3.1.0 (Dec 2025) is now a Linux Foundation standard under Bitol, originally developed at PayPal for Data Mesh. A synthesis of 50+ production implementations (Feb 2026) confirmed semantic versioning with a 90-day deprecation window as the dominant success pattern. Gartner Hype Cycle for Data Management 2025 positions data contracts as an emerging mechanism for building trust in AI workloads and data mesh architectures. The passive catalog-only contract pattern is formally deprecated — active CI/CD enforcement is the production standard.
WHAT YOU'LL LEARN
01Data contract anatomy: ODCS v3.1.0
02Three-layer enforcement model
03Schema evolution and compatibility modes
04CDC-based entity contracts with Debezium + Kafka
05CI/CD contract gates and breaking-change classification
06Contract violation kill-switch patterns
07Producer-side fixture generation and consumer simulation
08Downstream replay and safe version migration
YOU'LL BE ABLE TO
Author a production-grade ODCS v3.1.0 contract with schema, quality rules, SLAs, and ownership metadata
Wire three-layer enforcement: ODCS YAML in Git → dbt build-time gates → Soda/GX runtime checks
Catch breaking changes at PR time with datacontract-cli changelog and a GitHub Actions contract bot
Implement CDC-based entity contracts with Debezium + Kafka + Confluent Schema Registry CEL rules
Ship a downstream replay harness that validates safe schema-version migration before cutover
SKILLS YOU'LL GAIN

Real skills, real career delta.

Skills you'll gain

10
  • ODCS v3.1.0 contract authoringProduction

    Write complete ODCS v3.1.0 YAML contracts covering schema fields, field-level and model-level quality rules, executable SLAs, server definitions, and ownership metadata. Lint contracts with datacontract-cli and validate against the ODCS JSON Schema.

  • datacontract-cli: lint, test, changelog, exportProduction

    Run datacontract-cli lint for spec compliance, test against live data sources, changelog to diff two contract versions and classify BREAKING/NON-BREAKING/DEPRECATION changes, and export to Avro, JSON Schema, Pydantic, dbt models, and SodaCL.

  • Three-layer contract enforcement (spec → dbt → Soda/GX)Production

    Wire declarative ODCS YAML in Git as the spec layer, dbt model contracts (contract: enforced: true) as the build-time gate, and Soda Core or Great Expectations checks as the runtime enforcement layer. Each layer catches a distinct failure class.

  • Avro schema evolution and Confluent Schema Registry compatibility modesProduction

    Configure BACKWARD, FORWARD, and FULL compatibility modes in Confluent Schema Registry for Avro subjects. Manage schema versions, register new schemas via confluent-kafka-python, and apply intra-topic declarative migration rules for breaking-change cutover.

  • Confluent Schema Registry CEL condition and transform rulesProduction

    Attach CEL-based condition rules and transform rules to Avro/Protobuf Schema Registry subjects to enforce field-level contract constraints at message-produce time. Route contract violations to a DLQ topic using the built-in DLQ action.

  • CDC-based entity contracts with Debezium and KafkaProduction

    Build a Postgres → Debezium → Kafka → Schema Registry pipeline where entity-level contracts are enforced via CEL rules. Inspect DLQ topics for contract violations and validate the full stack with a Docker Compose integration test harness.

  • GitHub Actions contract gate with breaking-change PR botProduction

    Write a GitHub Actions workflow that runs datacontract-cli changelog between base and PR branch contracts, classifies each change, posts a structured PR comment, and fails CI on unannounced breaking changes. Blocks merges on destructive schema changes.

  • Airflow DAG circuit-breaker for batch contract enforcementProduction

    Configure an Airflow DAG where a datacontract-cli test task runs upstream of dbt transformation tasks. On contract failure the DAG halts immediately and fires a Slack alert, preventing bad data from reaching BI dashboards or ML feature stores.

  • Producer-side fixture generation from ODCS contract exportsWorking

    Export an ODCS contract to Pydantic models and Avro schemas via datacontract-cli, then use Faker with the generated models to produce synthetic fixture payloads that are structurally guaranteed to satisfy the contract for integration testing.

  • Downstream replay harness for schema-version migration (WAP pattern)Working

    Replay a recorded Kafka message set through a v1→v2 intra-topic schema migration using Confluent Schema Registry transform rules, then validate all migrated messages against the v2 ODCS contract. Implement the Write-Audit-Publish pattern in pure Python for lake-side assets.

RUNNABLE ON YOUR MACHINE
$ docker pull snap/data-contracts:hello
$ docker run --rm -it snap/data-contracts:hello
snap/data-contracts:hello
QUICK PREVIEW · 7 MIN
VERIFIED ENGINEER REVIEWS
The breaking-change PR bot alone was worth the course. Our data team now gets a structured impact report on every schema PR — no more surprise pipeline failures on Monday morning.
@platform_priyaVERIFY ON GITHUB
The CDC + Schema Registry + CEL rules project is the exact stack we run in prod. Having a reference Docker Compose that actually works saved me two days of debugging.
@kafka_sre_tomaszVERIFY ON GITHUB
LESSONS8
HOURS~1.3
LEARNERS0
THIS WEEK+0%