Oracle Updated 1z0-1084-23 Exam Questions and Answers by presley

API mocking is a technique that simulates the behavior of real APIs without requiring the actual implementation or deployment of the dependent services1. API mocking allows you to test changes to service A without deploying all of its dependencies, such as service B, by creating mock responses for the APIs that service A relies on1. API mocking has several benefits, such as1:

• Faster testing: You can test your service A without waiting for service B to be ready or available, which reduces the testing time and feedback loop.
• Isolated testing: You can test your service A in isolation from service B, which eliminates the possibility of external factors affecting the test results or causing errors.
• Controlled testing: You can test your service A with different scenarios and edge cases by creating mock responses that mimic various situations, such as success, failure, timeout, etc.

Explanation

The two correct differences between continuous delivery and continuous deployment in the DevOps lifecycle are: Continuous delivery is a process that initiates deployment manually, while continuous deployment is based on automating the deployment process. In continuous delivery, the software is ready for deployment, but the decision to deploy is made manually by a human. On the other hand, continuous deployment automates the deployment process, and once the software passes all the necessary tests and quality checks, it is automatically deployed without human intervention. Continuous delivery involves automatic deployment to a development environment, while continuous deployment involves automatic deployment to a production environment. In continuous delivery, the software is automatically deployed to a development or staging environment for further testing and validation. However, the actual deployment to the production environment is performed manually. In continuous deployment, the software is automatically deployed to the production environment, eliminating the need for manual intervention in the deployment process. These differences highlight the level of automation and human involvement in the deployment process between continuous delivery and continuous deployment approaches in the DevOps lifecycle.

Explanation

The correct answer is: "Multiple microservices can run in one process." The statement that is FALSE about microservices is: "Multiple microservices can run in one process." Microservices are designed to be independent and autonomous services that can be deployed, scaled, and managed separately. Each microservice typically runs as its own separate process. This separation allows for loose coupling and independent scalability of individual services. Running multiple microservices in a single process would violate the fundamental principle of microservices architecture, which emphasizes the isolation and independence of services. Combining multiple microservices into a single process would tightly couple them, making it difficult to independently manage, scale, and update each service. The other statements provided are true about microservices: It is fairly common for microservices to communicate with HTTP: Microservices often communicate with each other using lightweight protocols like HTTP/REST. This allows for interoperability, flexibility, and ease of communication between microservices. Microservices are typically designed around business capabilities: Microservices architecture advocates designing services based on specific business capabilities or functionalities. Each microservice focuses on a specific business domain or task, enabling modular and scalable development. They are independently deployable: Microservices are designed to be independently deployable units. This means that each microservice can be developed, tested, deployed, and updated separately without affecting other services. This flexibility allows for faster development cycles and more efficient scalability.

Explanation

The testing strategy that achieves high velocity of deployments and releases of cloud native applications is "Automated testing." Automated testing involves the use of automated tools and frameworks to execute tests, validate functionality, and detect issues or bugs in an application. By automating the testing process, developers and DevOps teams can rapidly test and validate code changes, ensuring that new features and updates are functioning correctly before being deployed to production. This approach helps increase the speed and efficiency of the testing process, allowing for faster and more frequent deployments of cloud native applications.