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.
How does IAM role and permissions affect the behavior of an AWS Lambda function?
- Define the function's runtime environment
- Determine what AWS services the function can access
- Manage the function's memory allocation
- Specify the function's timeout duration
IAM roles and permissions determine the AWS services and resources that the Lambda function can access, ensuring appropriate access controls and security.
What role do environment variables play in AWS Lambda function development?
- Controlling network access
- Defining function behavior
- Managing compute resources
- Storing configuration settings
Environment variables in AWS Lambda are commonly used for storing configuration settings such as API keys, database connection strings, and other parameters necessary for the function's operation.
How does AWS Lambda handle the execution environment for your function?
- It delegates execution environment management to users
- It manages the execution environment automatically
- It requires manual configuration of execution environment
- It restricts access to the execution environment
AWS Lambda automatically manages the execution environment for your function, including provisioning resources and scaling based on demand.
What is the primary role of deployment packages in AWS Lambda function creation?
- Bundling code and dependencies
- Configuring networking
- Generating logs
- Managing server resources
Deployment packages in AWS Lambda serve the primary role of bundling the function code along with any dependencies required for execution.
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.
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.
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: 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.
What are some common tools used for creating deployment packages for AWS Lambda functions?
- AWS CLI, AWS Toolkit for Visual Studio, AWS CloudFormation
- AWS ECS, AWS CodeCommit, AWS CodePipeline
- AWS Elastic Beanstalk, AWS Redshift, AWS Step Functions
- AWS IAM, AWS S3, AWS RDS
The AWS CLI, AWS Toolkit for Visual Studio, and AWS CloudFormation are common tools used for creating deployment packages for AWS Lambda functions.