Database access in Serverless architecture requires special attention to performance and cost optimization:
Database selection:
- Serverless databases: Such as Aurora Serverless, DynamoDB, Cosmos DB
- Traditional databases: RDS, PostgreSQL, MySQL (require connection pool management)
- NoSQL databases: Suitable for high concurrency and flexible data model scenarios
Connection management challenges:
- Connection pool limits: Traditional databases have limited connection counts, which may be exhausted when function concurrency is high
- Cold start impact: New connections need to be established for each cold start, increasing latency
- Connection leaks: Function abnormal exit may cause connections not to be released
Optimization strategies:
1. Use Serverless databases
- Auto-scaling: Automatically adjust resources based on load
- Pay-as-you-go: Pay only for resources actually used
- No connection limits: No need to worry about connection pool issues
2. Connection pool management
- External connection pools: Use connection pool services like RDS Proxy, Neon
- Connection reuse: Reuse connections within the function instance lifecycle
- Reasonable configuration: Configure connection pool size based on concurrency needs
3. Access pattern optimization
- Batch operations: Reduce database round trips
- Caching strategy: Use Redis to cache hot data
- Read-write separation: Use read replicas to distribute load
4. Performance optimization
- Index optimization: Create indexes reasonably to improve query efficiency
- Query optimization: Avoid full table scans, optimize complex queries
- Asynchronous processing: Put database operations into message queues for asynchronous processing
Candidates should be able to choose appropriate databases and access strategies based on business scenarios.