What is a custom runtime in AWS Lambda?
- A custom runtime allows you to use programming languages not officially supported by AWS Lambda, such as Rust or COBOL.
- A custom runtime is a built-in feature of AWS Lambda for optimizing performance and resource allocation.
- A custom runtime is a tool provided by AWS Lambda for debugging and monitoring functions in production environments.
- A custom runtime refers to manually configuring the execution environment of a Lambda function to tailor it to specific requirements.
A custom runtime allows you to use programming languages not officially supported by AWS Lambda, such as Rust or COBOL.
Scenario: You are migrating workloads from one AWS account to another. How would you ensure seamless access to resources during the migration process using Cross-Account Access?
- Create IAM users in the destination account and manually copy permissions from the source account.
- Grant cross-account access to all users in both accounts to facilitate resource access.
- Set up IAM roles in the destination account with permissions to access resources in the source account and establish trust relationships between the two accounts.
- Temporarily disable IAM policies in the source account to allow unrestricted access during the migration.
By configuring IAM roles in the destination account with the necessary permissions to access resources in the source account and establishing trust relationships between the two accounts, you can ensure seamless access to resources during the migration process.
Scenario: You are working with a third-party vendor who needs temporary access to specific resources in your AWS account. How would you implement Cross-Account Access securely?
- Allow the third-party vendor to create their IAM users in your account for access.
- Create a temporary IAM role with limited permissions and provide the third-party vendor with temporary credentials to assume the role.
- Share your root account credentials with the third-party vendor for direct access to the resources.
- Use IAM groups with cross-account access policies to grant access to the third-party vendor.
By creating a temporary IAM role with restricted permissions and providing the third-party vendor with temporary credentials, you can ensure secure access to specific resources in your AWS account for the duration of their need.
What is the primary purpose of Lambda@Edge?
- Analyzing data
- Customizing content delivery and enhancing user experience
- Managing databases
- Securing network traffic
The primary purpose of Lambda@Edge is to enable customization of content delivery and enhance user experience by running code closer to end-users.
What is Lambda@Edge?
- AWS service for running code closer to end-users
- Container service
- Database service
- Machine learning service
Lambda@Edge is an AWS service that allows you to run code closer to end-users, enabling you to customize content delivery and enhance user experience.
Scenario: You need to ensure compliance with strict security requirements for your AWS Lambda functions, including custom runtime environments. How would you implement security controls and best practices?
- Enable AWS CloudTrail logging for Lambda function activity
- Encrypt environment variables containing sensitive data
- Implement least privilege IAM roles for Lambda functions
- Utilize AWS WAF to filter incoming requests
Implementing least privilege IAM roles for Lambda functions helps restrict access and reduce the attack surface, contributing to compliance with strict security requirements.
Scenario: Your team is developing a new programming language optimized for specific computational tasks. How would you integrate this language as a custom runtime in AWS Lambda?
- Create a Lambda layer with the language runtime
- Deploy the language runtime as a standalone service
- Embed the language runtime directly into the function code
- Use an existing natively supported runtime and adapt it
Creating a Lambda layer with the language runtime allows for reusability across multiple functions and simplifies maintenance.
AWS Lambda enforces a __________ for custom runtimes to ensure security and stability.
- Execution policy
- Hardware specification
- Runtime API
- Scripting language
AWS Lambda enforces a Runtime API for custom runtimes to ensure security and stability.
The deployment of Lambda@Edge functions is managed through AWS __________.
- CloudFront
- Elastic Beanstalk
- IAM
- Route 53
The deployment of Lambda@Edge functions is managed through AWS CloudFront, which integrates with Lambda@Edge to execute functions at edge locations.
Lambda@Edge enables you to customize content delivery based on the viewer's __________.
- Browser
- Location
- Operating system
- Time zone
Lambda@Edge enables you to customize content delivery based on the viewer's geographic location, enabling personalized experiences.
Can Lambda@Edge functions access resources in a VPC?
- Limited access, requiring special permissions
- No, Lambda@Edge functions cannot access resources in a VPC
- Partial access, depending on VPC configuration
- Yes, Lambda@Edge functions have full access to resources in a VPC
Lambda@Edge functions execute at edge locations and do not have access to resources within a VPC due to the distributed nature of edge computing.
What are the limitations of Lambda@Edge compared to regular AWS Lambda functions?
- Access to fewer AWS services
- Higher memory allocation
- Longer maximum execution time
- Smaller function size limit
Lambda@Edge functions have a smaller size limit compared to regular AWS Lambda functions due to the constraints of edge computing environments.