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Explain how to implement schema validation for incoming data streams.

System Design/Architectureeasy0.3 min readPremium
Frequency
Low
Asked at 1 company
Category
179
questions in System Design/Architecture
Difficulty Split
15E|6M|158H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Adidas
Interview Pro Tip

Pro-Move: 'We version schemas; invalid events go to DLQ with original payload + error—reprocess after schema fix.'

Expert AnswerPremium
58 wordsInterview-ready
**Why**: Invalid records corrupt downstream; validation at ingress isolates failures. **Components**: (1) Schema Registry (Avro/Proto/JSON Schema)—versioned schemas; (2) Validate at ingress—Kafka with Schema Registry, API gateway; (3) Check required fields, types, enums; (4) Dead-letter queue for invalid. **Evolution**: Backward/forward compatible changes. Confluent Schema Registry; producers validate before produce. For JSON: jsonschema, pydantic....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Adidas. The answer also includes follow-up discussion points that interviewers commonly explore.

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