What are some potential challenges when working with Lambda limits and quotas in complex serverless architectures?
- Coordination of multiple functions and services
- Lack of integration with other AWS services
- Limited programming languages support
- Static scaling limitations
In complex serverless architectures, coordination of multiple functions and services can present challenges in managing Lambda limits and quotas.
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.
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 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 request an increase in the default limits for AWS Lambda?
- By editing Lambda function code
- Through the AWS Management Console
- Using the AWS CLI
- Via email to AWS support
You can request an increase in the default limits for AWS Lambda by using the AWS Management Console, where you can submit a service limit increase request.
What is the default maximum execution time limit for an AWS Lambda function?
- 1 minute
- 15 minutes
- 30 seconds
- 5 hours
The default maximum execution time limit for an AWS Lambda function is 15 minutes, meaning a function will be terminated if it runs for longer than this duration.
What happens if a Lambda function exceeds its concurrent execution limit?
- Additional invocations are throttled
- The function automatically scales up to accommodate the load
- The function is paused until resources become available
- The function is terminated
If a Lambda function exceeds its concurrent execution limit, additional invocations beyond the limit are throttled, preventing them from executing until resources become available.
What types of limits and quotas are associated with AWS Lambda?
- CPU utilization and disk I/O
- Concurrent executions, invocation payload size, execution duration, and memory allocation
- Network bandwidth, storage capacity, and API calls
- Operating system licenses and software installations
AWS Lambda has various limits and quotas, including limits on concurrent executions, invocation payload size, execution duration, and memory allocation.
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.
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.
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.
What are some common methods for handling dependencies in AWS Lambda functions?
- Installing dependencies at runtime
- Packaging dependencies with the function code
- Sharing dependencies across multiple functions
- Storing dependencies in a separate S3 bucket
One common method for handling dependencies in AWS Lambda functions is to package them along with the function code, typically using tools like AWS SAM or AWS CLI.