In what scenarios would you use AWS Lambda to process events from Amazon SNS?
- Implementing event-driven architectures
- Managing networking
- Running batch jobs
- Storing data
AWS Lambda is commonly used with Amazon SNS to implement event-driven architectures, reacting to messages published to SNS topics.
How does AWS Lambda process events from Amazon DynamoDB streams?
- Asynchronously
- In batches
- Manually
- Synchronously
AWS Lambda processes events from Amazon DynamoDB streams asynchronously, allowing for real-time processing of changes to DynamoDB tables.
What types of events can trigger AWS Lambda functions through Amazon API Gateway?
- Database queries
- Email notifications
- File uploads
- HTTP requests
AWS Lambda functions can be triggered by HTTP requests routed through Amazon API Gateway, allowing for serverless APIs.
How does AWS Lambda handle events from Amazon S3 buckets?
- By deleting events from Amazon S3
- By ignoring events from Amazon S3
- By invoking functions in response to bucket events
- By pausing functions in response to Amazon S3 events
AWS Lambda can be configured to execute functions in response to events in Amazon S3 buckets, such as object creation, deletion, or modification.
Which AWS service can trigger AWS Lambda functions directly?
- Amazon RDS
- Amazon Redshift
- Amazon S3
- Amazon SQS
Amazon S3 can trigger AWS Lambda functions directly by invoking them when certain events occur, such as object creation, deletion, or modification.
What are AWS Lambda event sources?
- Only Amazon EC2 instances
- Only Amazon RDS databases
- Only Amazon S3 buckets
- Various AWS services and custom applications
AWS Lambda can be triggered by events from various AWS services like Amazon S3, Amazon DynamoDB, Amazon Kinesis, etc., as well as custom applications.
Scenario: A project requires integration with a third-party library not supported by default AWS Lambda runtimes. How would you approach this challenge using custom runtimes?
- Create a custom runtime with the necessary dependencies
- Explore alternative AWS services for integration
- Rewrite the functionality without the third-party library
- Use AWS Lambda layers for library integration
Creating a custom runtime allows you to include the required third-party library dependencies, enabling integration with AWS Lambda.
Scenario: Your team is considering migrating existing applications to AWS Lambda. How would you evaluate the compatibility of the current runtimes with AWS Lambda?
- Conduct compatibility tests with existing codebase
- Consult AWS Lambda experts
- Review AWS Lambda documentation and runtime support
- Trial migration with a sample application
Reviewing AWS Lambda documentation and runtime support is crucial to understanding which runtimes are officially supported and compatible with AWS Lambda.
The flexibility of custom runtimes enables fine-tuning of ________ and dependencies for specific use cases.
- Performance
- Resource usage
- Scalability
- Security
Custom runtimes in AWS Lambda allow for fine-tuning of performance-related parameters and dependencies, optimizing functions for specific use cases.
How do Lambda limits and quotas affect the scalability of serverless applications?
- They can impact the ability to handle sudden spikes in traffic
- They have no effect on scalability
- They improve scalability by optimizing resource utilization
- They only affect cost, not scalability
Lambda limits and quotas, such as concurrent executions, can impact the ability of serverless applications to handle sudden spikes in traffic, potentially leading to throttling or failed invocations during peak loads.
Scenario: You are tasked with setting up an architecture where changes to items in an Amazon DynamoDB table should trigger AWS Lambda functions to update corresponding records in an Amazon RDS database. What steps would you take to implement this solution?
- Use Amazon EC2 Instances
- Use Amazon S3 Event Notifications
- Use DynamoDB Streams
- Use DynamoDB Triggers
DynamoDB Streams can capture changes to items in a table and trigger AWS Lambda functions, allowing you to update corresponding records in RDS.
Scenario: Your team needs to design a solution where incoming messages from an Amazon SQS queue should trigger AWS Lambda functions to process the data. Which AWS service would you use to accomplish this integration?
- Amazon EC2 Autoscaling
- Amazon RDS Instances
- Amazon S3 Buckets
- Amazon SQS Triggers
Amazon SQS can directly trigger AWS Lambda functions, allowing you to process incoming messages from the queue efficiently.