The primary advantage of using Spring Cloud Config Server in a microservices environment is centralized configuration management. It allows you to store configuration properties externally and manage them in a centralized manner, making it easier to update and maintain configurations across multiple services.

The primary role of the @Transactional annotation in Spring Data JPA is to manage database transactions. It marks a method, class, or even an interface to indicate that a transaction should be created and managed around the annotated method or methods. This ensures data consistency by committing changes if everything succeeds or rolling back if an exception occurs during the annotated operation. It is essential for maintaining data integrity in a Spring Data JPA application.

Converting a traditional blocking application to a non-blocking reactive application using WebFlux in Spring Boot comes with several challenges. These challenges include managing backpressure to prevent data overflow, understanding reactive operators to compose and transform data streams effectively, and adapting to the asynchronous nature of reactive programming. It is not necessary or practical to eliminate all database calls and replace them with external REST API calls when transitioning to reactive programming. Ensuring strict blocking behavior contradicts the non-blocking nature of WebFlux. Replacing all reactive components with traditional blocking components would defeat the purpose of adopting reactive programming.

The @RequestHeader annotation is used to bind the value of a method parameter to a named HTTP header in a Spring Boot application. By specifying the header name as a parameter to this annotation, you can access the value of the corresponding HTTP header. The other options are not valid annotations for binding HTTP headers in Spring Boot.

To externalize configuration properties in Spring Boot, the "@ConfigurationProperties" annotation is used on a configuration properties class. This annotation binds properties from the configuration files (such as "application.yml" or ".properties") to fields in the configuration class, allowing easy access to configuration values.

To implement custom validation rules that cannot be expressed with standard JSR-303 annotations, you should create custom validation constraints by extending javax.validation.Constraint and implement the validation logic in the isValid method. Then, apply these custom constraints to your Spring components. This approach aligns with best practices for custom validation in Spring Boot applications.

In a microservices architecture with Spring Cloud, client-side load balancing is achieved by using Netflix Ribbon. Ribbon is a client-side load balancer that helps services locate and balance requests across multiple instances of a service.

Option 3 is correct. To minimize garbage collection pause times in a high-throughput Spring Boot application, you can use the G1 Garbage Collector and tune its parameters. The G1 Garbage Collector is designed to provide low-latency and predictable garbage collection behavior. Increasing heap size (Option 1) may not necessarily reduce pause times. Implementing custom garbage collection algorithms (Option 2) is complex and not typically recommended. Avoiding multithreading (Option 4) is not a practical solution for improving performance.

In a YAML configuration file in Spring Boot, a list of values is represented using a sequence, denoted by -. For example, to define a list of values, you would use the format: - value1 - value2 - value3. This format is commonly used for things like specifying multiple profiles or values in a Spring Boot configuration file.

In Spring Boot, you can prioritize different @ControllerAdvice classes by using the @Order annotation on each class. This allows you to control the order in which these classes are applied when handling exceptions. The other options don't provide a direct way to prioritize @ControllerAdvice classes.