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.
What is the recommended format for packaging dependencies with AWS Lambda functions?
- Embedding dependencies within the function code directly
- Hosting dependencies on external servers
- Installing dependencies globally on the Lambda environment
- Using a deployment package with bundled dependencies
The recommended format for packaging dependencies with AWS Lambda functions involves bundling dependencies within the deployment package, ensuring all required libraries are included for execution.
Scenario: Your team needs to deploy a Lambda function that processes data uploaded to an S3 bucket. What steps would you take to ensure the Lambda function has the necessary permissions?
- Attach an S3 bucket policy to the Lambda function
- Configure S3 ACLs
- Create an IAM role with permissions to access the S3 bucket
- Use AWS Security Groups
By creating an IAM role with the necessary permissions to access the specified S3 bucket, you can assign this role to the Lambda function, ensuring it has the required permissions.
Scenario: You're developing a serverless application where Lambda functions need access to resources in an Amazon VPC. How would you configure the Lambda functions to achieve this?
- Configure the Lambda function to run inside a VPC
- Enable AWS Direct Connect
- Grant IAM roles to Lambda functions
- Use VPC endpoints
By configuring the Lambda function to run inside a VPC, you can provide it with access to resources within that VPC, such as EC2 instances or RDS databases.