Scenario: You need to develop a machine learning model using AWS Lambda. Which runtime option would you choose and why?
- Go runtime
- Java runtime
- Node.js runtime
- Python with TensorFlow runtime
Python with TensorFlow runtime is a suitable choice for developing machine learning models on AWS Lambda, as it provides the necessary libraries and frameworks for training and inference tasks.
Upgrading to a newer version of a runtime in AWS Lambda may introduce ________ and compatibility issues.
- Breakages
- Bugs
- Errors
- Incompatibilities
Upgrading to a newer runtime version in AWS Lambda may introduce breakages and compatibility issues, necessitating thorough testing before deployment.
Custom runtimes in AWS Lambda allow developers to use ________ languages not officially supported by AWS.
- Custom
- Non-standard
- Third-party
- Unconventional
Custom runtimes in AWS Lambda enable the use of non-standard languages, extending the platform's flexibility beyond officially supported ones.
AWS Lambda automatically handles runtime __________, freeing developers from infrastructure management tasks.
- Code optimization
- Database management
- Provisioning and scaling
- Security configuration
AWS Lambda automatically handles runtime provisioning and scaling, ensuring that resources are allocated as needed to handle incoming events.
The choice of runtime determines the __________ available for development and deployment of Lambda functions.
- Cloud provider
- Cost structure
- Libraries and frameworks
- Network bandwidth
The choice of runtime in AWS Lambda determines the libraries, frameworks, and language features available for development and deployment of Lambda functions.
AWS Lambda supports runtimes such as __________, __________, and __________.
- C++, Ruby, PHP
- Go, Rust, Swift
- PowerShell, TypeScript, Perl
- Python, Node.js, Java
AWS Lambda supports various runtimes including Python, Node.js, and Java, allowing developers to write functions in their preferred programming language.
In what scenarios would you consider using a custom runtime for an AWS Lambda function?
- When you need to enhance security
- When you need to optimize performance
- When you need to reduce cost
- When you need to use a language or language version not supported by AWS Lambda
Custom runtimes are particularly useful when developers need to use programming languages or language versions that are not natively supported by AWS Lambda, providing flexibility for specific use cases.
How does AWS Lambda handle updates and maintenance of supported runtimes?
- AWS manages updates and maintenance
- Developers are responsible for updates
- Runtimes are static and do not require updates
- Updates are managed by third-party vendors
AWS Lambda handles updates and maintenance of supported runtimes, ensuring that they are up-to-date and secure without requiring manual intervention from developers.
What are the benefits of AWS Lambda providing support for custom runtimes?
- Enhanced security
- Improved performance
- Increased language support
- Reduced cost
AWS Lambda's support for custom runtimes allows developers to use programming languages and language versions that are not natively supported by AWS Lambda.
Can you modify the runtime of an existing AWS Lambda function after it has been deployed?
- No, runtime cannot be modified after deployment
- Yes, but it requires creating a new function
- Yes, by updating the function's environment variables
- Yes, through the AWS Management Console
While many aspects of a Lambda function can be modified post-deployment, such as code and configuration, the runtime itself cannot be changed once the function is deployed.
How does the choice of runtime affect the performance of an AWS Lambda function?
- It affects only memory usage
- It has no effect on performance
- It impacts startup time and execution speed
- It only affects security
The choice of runtime in AWS Lambda affects the performance by influencing factors such as startup time and the speed of executing functions.
What is the significance of choosing a specific runtime for an AWS Lambda function?
- Determines the event source for the function
- Determines the execution environment for the function
- Determines the programming language the function can use
- Determines the region where the function will run
Choosing a specific runtime for an AWS Lambda function determines the programming language you can use to write the function. Each runtime supports different languages.