AWS CloudWatch provides log monitoring and analysis capabilities, allowing you to identify performance bottlenecks in AWS Lambda function logs during testing.

AWS Lambda functions should be thoroughly tested to ensure they perform as expected under various conditions, including different inputs and workload scenarios.

Testing AWS Lambda functions that interact with other AWS services may involve challenges such as handling asynchronous behavior, managing IAM permissions, and debugging event triggers.

Load testing on AWS Lambda functions can be performed using third-party tools like Locust or Artillery, which simulate multiple concurrent invocations to assess performance and scalability.

AWS CodePipeline can be configured to automate the testing process for AWS Lambda functions, including running unit tests, integration tests, and other types of tests as part of the deployment pipeline.

To create a custom validator in Spring Boot, you should extend the Validator interface and implement the validate method. This allows you to define custom validation logic for specific fields in your application. Options 1 and 3 are not correct; Spring Boot does not have an @CustomValidator annotation for field-level validation, and the @Valid annotation is typically used at the method level, not for field-level validation. Option 4 is incorrect as it's not a true statement.

You can customize error messages in Bean Validation in Spring Boot by defining custom error messages using the message attribute within the validation annotations on your entity fields. This approach allows you to specify custom messages for specific validation constraints.

In Spring Security, user authentication is primarily handled by the UserDetailsService interface. This interface is responsible for loading user-specific data, such as username, password, and authorities, which is essential for authentication and authorization processes. The Authentication Provider is responsible for authenticating users based on this user-specific data. The Filter Chain and Controller are not primarily responsible for user authentication.

In Spring Boot, the "@ConditionalOnProperty" annotation is used to specify that a bean should be created only under a specific condition based on the values of specified properties. This is a powerful feature that allows developers to control bean creation based on property values, making the application's configuration more flexible and adaptable. The other options are not the correct annotations for this purpose.

To address N+1 select issues in Spring Data JPA while maintaining data consistency, you should implement batch fetching strategies or use join fetch to eagerly fetch related entities. Disabling lazy loading can lead to data inconsistency and is not recommended. Tuning the database server's caching mechanisms can improve performance but doesn't directly address the N+1 issue. Using non-relational databases is a significant architectural change and may not be suitable for all scenarios.

The @GetMapping annotation is mainly used to handle HTTP GET requests in a Spring Boot application. It is a specialized annotation that maps HTTP GET requests to specific controller methods. While @RequestMapping is a more generic annotation used for various HTTP methods, @GetMapping specifically targets GET requests, making the code more readable and explicit. The other options are not valid Spring annotations.

To enable global method security in Spring Security, you should set the prePostEnabled attribute to true in the @EnableGlobalMethodSecurity annotation. This enables the use of @PreAuthorize and @PostAuthorize annotations for method-level security.