AWS Lambda provides __________ for building and deploying custom runtimes to simplify the process.
- Documentation
- SDKs
- Templates
- Tooling
AWS Lambda provides tooling for building and deploying custom runtimes, such as the AWS Lambda Runtime Interface Emulator and the AWS Lambda Runtime API, to simplify the process.
When using a custom runtime, you have full control over the __________ and execution environment of your Lambda functions.
- Infrastructure
- Networking
- Permissions
- Runtime
When using a custom runtime, you have full control over the runtime and execution environment of your Lambda functions.
Monitoring and debugging custom runtimes might require integration with AWS __________ services.
- CloudWatch
- Glacier
- RDS
- S3
Monitoring and debugging custom runtimes in AWS Lambda might require integration with AWS CloudWatch services.
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.
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.
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.
How does a custom runtime differ from standard runtimes in AWS Lambda?
- Custom runtimes are only available for enterprise-tier AWS Lambda plans, while standard runtimes are included in all tiers.
- Custom runtimes enable the use of programming languages not officially supported by AWS Lambda, while standard runtimes are limited to a predefined set of languages.
- Custom runtimes offer greater control over the execution environment and configuration options compared to standard runtimes.
- Custom runtimes provide better performance and scalability compared to standard runtimes in AWS Lambda.
Custom runtimes enable the use of programming languages not officially supported by AWS Lambda, expanding the range of languages developers can use.
What is the primary advantage of using a custom runtime in AWS Lambda?
- Custom runtimes offer better performance and resource optimization compared to standard runtimes in AWS Lambda.
- Custom runtimes provide built-in monitoring and debugging tools for AWS Lambda functions, streamlining development and troubleshooting processes.
- The primary advantage of using a custom runtime is the ability to leverage existing libraries and frameworks in languages not officially supported by AWS Lambda.
- Using a custom runtime in AWS Lambda eliminates the need for managing server infrastructure, reducing operational overhead and costs.
The primary advantage of using a custom runtime is the ability to leverage existing libraries and frameworks in languages not officially supported by AWS Lambda.
How can you create a custom runtime for AWS Lambda?
- Modifying the AWS Lambda source code
- Uploading a custom Docker image
- Using a third-party service
- Using the AWS Lambda Runtime API
Using the AWS Lambda Runtime API allows you to build custom runtimes by implementing a specific interface for handling function invocations, initialization, and cleanup.
What are the considerations when deploying a custom runtime in AWS Lambda?
- Cold start performance
- Compatibility with AWS services
- Cost implications
- Security implications
Considerations for deploying a custom runtime in AWS Lambda include its impact on cold start performance, as custom runtimes may have different initialization times.