While Serverless architecture has many advantages, it also has some limitations and challenges that need to be reasonably evaluated based on business scenarios:
Main limitations:
1. Execution time limits
- Maximum execution time: AWS Lambda maximum 15 minutes, Azure Functions 10 minutes
- Impact: Not suitable for long-running tasks such as video processing, big data analysis
2. Cold start latency
- First call latency: Ranges from a few hundred milliseconds to a few seconds
- Impact: Applications sensitive to latency (such as real-time communication, games) may not be applicable
3. Resource limits
- Memory limits: Usually maximum 10GB
- Disk space: /tmp directory usually limited to 512MB-10GB
- Concurrency limits: Account-level and function-level concurrency limits
4. State management
- Stateless nature: Cannot share state between function instances
- Impact: Need to rely on external storage services to manage state
5. Debugging difficulties
- Local environment differences: Local development environment may differ from cloud environment
- Debugging tool limitations: Cannot set breakpoints like traditional applications
6. Vendor lock-in
- Platform dependency: Significant differences between Serverless platforms of different cloud providers
- Migration costs: Migrating to other platforms requires code refactoring
7. Cost uncertainty
- Pay-as-you-go: Costs may exceed expectations in high concurrency scenarios
- Difficult to predict: Difficult to accurately predict actual usage and costs
Applicable scenarios:
- Event-driven applications
- API services
- Data processing pipelines
- Microservices architecture
- Scheduled tasks
Candidates should be able to reasonably evaluate the applicability of Serverless architecture based on business needs.