Design analytics event schema validation
WHAT IT TESTS: protecting data quality at scale. OUTLINE: define a schema registry, validate at both client (fast feedback) and server (authoritative gate), and quarantine failures to a dead-letter store.
WHAT IT TESTS: whether you can keep an event pipeline trustworthy. ANSWER OUTLINE: maintain a versioned schema registry defining each event's required fields and types; validate on the client for fast developer feedback but treat the server as the authoritative gatekeeper since clients can be old or malicious; on failure, do not silently drop, instead route bad events to a dead-letter queue with error metadata for inspection, alert on spikes, and version schemas to evolve safely.
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- #data-quality
- #schema-validation
- #event-tracking
- #dead-letter-queue
- #data-pipeline
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