How do you implement event sourcing with serverless?

Event sourcing stores every state change as an immutable event rather than overwriting current state, creating a complete audit trail. Serverless implementation: (1) Event store — DynamoDB with event-driven append patterns (never update/delete, only insert new events) or Kinesis Data Streams as a time-limited event log; (2) Command handlers — Lambda functions validate commands and write events to the store; (3) Event processors — DynamoDB Streams or Kinesis triggers Lambda projectors that update read models (denormalized views) in separate DynamoDB tables; (4) Read models — DynamoDB tables or Elasticsearch optimized for specific query patterns (user order history, inventory levels); (5) Snapshots — periodically persist aggregate state to avoid replaying all events on every read; store snapshots in S3; (6) Event schema registry — use AWS Glue Schema Registry or EventBridge Schema Registry to version event schemas; (7) Replay — rebuild projections by replaying DynamoDB Streams from TRIM_HORIZON. Key challenge: eventual consistency between events and read models — design UI to handle slightly stale data.