What is the maximum payload size limit for synchronous invocation of Lambda functions?
- 1 GB
- 10 KB
- 500 MB
- 6 MB
The maximum payload size limit for synchronous invocation of Lambda functions is 6 MB, allowing you to send data within this size constraint when invoking functions synchronously.
How can you monitor and manage Lambda limits and quotas in a production environment?
- Contact AWS Support for updates
- Ignore limits and quotas
- Manually track usage in spreadsheets
- Utilize AWS CloudWatch metrics and alarms
Utilize AWS CloudWatch metrics and alarms to monitor Lambda usage and set up alerts for approaching or exceeding limits.
What strategies can be employed to optimize Lambda usage within the imposed limits?
- Ignore imposed limits
- Implement efficient code practices and minimize dependencies
- Increase memory allocation for all functions
- Rely solely on auto-scaling
Implement efficient code practices and minimize dependencies to optimize Lambda usage within the imposed limits.
To ensure high availability and fault tolerance, AWS Lambda automatically scales the execution ________.
- Horizontally
- Manually
- Statically
- Vertically
AWS Lambda automatically scales the execution horizontally, meaning it adds more instances to handle increased load.
AWS Trusted Advisor can provide recommendations on optimizing Lambda usage based on ________.
- Cost only
- Performance only
- Performance, cost, security, and fault tolerance
- Security only
AWS Trusted Advisor can analyze various aspects of Lambda usage, including performance, cost, security, and fault tolerance, to provide recommendations for optimization.
How can you test the functionality of an AWS Lambda function before deploying it?
- Deploying directly to production
- Locally using a testing framework
- Manual testing in production
- Testing only after deployment
AWS Lambda functions can be tested locally using testing frameworks like AWS SAM or the Serverless Framework, allowing developers to simulate events and verify functionality before deployment.
Scenario: Your team is developing a real-time data processing application using AWS Lambda. How would you design the architecture to accommodate Lambda's concurrency limits?
- Configure Amazon SQS as an event source
- Implement event-driven architecture
- Increase Lambda function memory
- Provision additional AWS Lambda functions
Implementing an event-driven architecture allows AWS Lambda to scale automatically, mitigating the impact of concurrency limits by dynamically allocating resources based on incoming events.
Scenario: A Lambda function in your application occasionally hits the timeout limit. How would you troubleshoot and resolve this issue?
- Enable AWS X-Ray tracing
- Increase Lambda function memory
- Monitor CloudWatch Logs
- Optimize code and increase timeout
Optimizing code to improve performance and increasing the timeout setting can address the issue by allowing the function more time to complete its tasks.
Scenario: You're planning to migrate an existing application to serverless using AWS Lambda. What considerations would you take into account regarding Lambda's limits and quotas?
- Estimate function resource requirements
- Ignore Lambda limits
- Increase Lambda function memory
- Limit Lambda function invocations
Estimating resource requirements helps in avoiding resource contention and staying within Lambda's limits, ensuring optimal performance.
What are the primary components required for creating a Lambda function?
- Database and storage setup
- Function code and handler
- Operating system and kernel
- Virtual machine and network configuration
The primary components required for creating a Lambda function include the actual function code and a handler that specifies the entry point for the function.