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.

The correct answer is: 'Robust Deployment.' When using test cases that simultaneously validate a deployment and perform a selected set of functional tasks, the testing measure that should be considered is 'Robust Deployment.' Robust Deployment refers to the ability of an application or system to be deployed reliably and consistently, without errors or failures. It involves ensuring that the deployment process is well-defined, automated, and able to handle different scenarios and configurations. When conducting testing that combines the validation of deployment and functional tasks, it is crucial to ensure that the deployment itself is robust. This means verifying that the application or system can be successfully deployed and configured without encountering deployment-related issues such as incorrect configurations, missing dependencies, or compatibility problems. By considering 'Robust Deployment' as a testing measure, you can evaluate the reliability and effectiveness of the deployment process, ensuring that the application or system is deployed correctly and ready to perform the selected set of functional tasks.

The Fn Project is an open source serverless computing platform that serves as the engine for Oracle Functions. It provides a runtime environment for executing functions in a serverless architecture. The Fn Project enables developers to build and deploy functions using different programming languages, including Java, Python, Node.js, and more. The Fn Project is designed to be flexible and extensible, allowing developers to define functions as small units of code and execute them in response to events or triggers. It supports event-driven execution, allowing functions to be triggered by various events such as HTTP requests, messages from messaging systems, or changes in data. Oracle Functions leverages the Fn Project as its underlying engine, providing a managed serverless platform within the Oracle Cloud Infrastructure. It allows developers to easily develop, deploy, and manage functions using the familiar Fn Project framework and tooling. With Oracle Functions, developers can focus on writing their function code while leaving the infrastructure management, scaling, and operational tasks to the platform.

The feature that is typically NOT associated with Cloud Native is 'Application Servers.' Cloud Native architecture emphasizes lightweight, scalable, and containerized deployments, which often replace traditional monolithic application servers. Instead of relying on application servers, Cloud Native applications are typically deployed as containerized microservices that can be orchestrated and managed using container orchestration platforms like Kubernetes. This approach enables greater flexibility, scalability, and agility in deploying and managing applications. While application servers have been widely used in traditional application architectures, they are not a characteristic feature of Cloud Native architectures. Cloud Native architectures focus on containerization, declarative APIs, immutable infrastructure, and service meshes to enable efficient and scalable deployment and management of applications.

To push a new image to the Oracle Cloud Infrastructure (OCI) Registry, you would need to perform the following two actions: Assign a tag via Docker CLI to the image: Before pushing the image, you need to assign a tag to it using the Docker CLI. The tag helps identify the image and associate it with a specific version or label. Generate an auth token to complete the authentication via Docker CLI: To authenticate and authorize the push operation, you need to generate an auth token. This token is used to authenticate your Docker CLI with the OCI Registry, allowing you to push the image securely. Note: Generating an API signing key, assigning an OCI defined tag via OCI CLI, and generating an OCI tag namespace are not required steps for pushing a new image to the OCI Registry.