How does Lambda@Edge help improve content delivery performance?
- Executing code closer to viewers
- Increasing server capacity
- Managing networking hardware
- Optimizing database queries
Lambda@Edge allows code execution at CloudFront edge locations, reducing latency by executing code closer to viewers, thus improving content delivery performance.
What AWS services can trigger Lambda@Edge functions?
- AWS Lambda
- Amazon CloudFront
- Amazon RDS
- Amazon S3
Lambda@Edge functions can be triggered by events generated by Amazon CloudFront, allowing for dynamic content manipulation and delivery optimizations.
How does Lambda@Edge impact the latency of content delivery?
- Increases latency by adding additional processing overhead
- Increases latency by routing requests through central servers
- No impact on latency
- Reduces latency by executing functions closer to the end-user
Lambda@Edge reduces latency by executing functions closer to the end-user, improving response times for content delivery.
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.
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.
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.
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.
Scenario: You are migrating an existing application to AWS Lambda but require a runtime environment that is not natively supported. How would you approach this using custom runtimes?
- Deploy the application on EC2 instances
- Develop a custom runtime using the AWS Lambda Runtime API
- Modify the application to use a natively supported runtime
- Utilize AWS Fargate for containerized execution
Developing a custom runtime using the AWS Lambda Runtime API allows for supporting the required runtime environment in AWS Lambda.
What are some advantages of using AWS Step Functions over traditional orchestration methods?
- Data storage
- Higher scalability
- Lower cost
- Simplified workflow management
AWS Step Functions offer a visual workflow editor and built-in error handling, simplifying workflow management compared to traditional methods.
How does AWS Step Functions manage error handling and retries?
- Built-in error handling and automatic retries
- External error handling services
- Manual error handling only
- No error handling
AWS Step Functions provide built-in error handling capabilities, allowing you to define how to handle different types of errors and automatically retry failed steps based on configured retry policies.