Download Full Version 1z0-1084-23 Oracle Exam

Explanation

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 thatthe 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.

Explanation

The correct answer is: "Tightly coupled." Tightly coupling is not a criterion that is usually met by a microservice. In fact, microservices are designed to be loosely coupled. Loosely coupling refers to reducing dependencies and minimizing the direct interactions between different components or services. Microservices promote independence and autonomy, allowing each service to operate independently without being tightly bound to other services. The other options listed are criteria that are typically met by microservices: Organized around business capabilities: Microservices architecture suggests designing services around specific business capabilities or functionalities. This allows for focused and specialized services that align with the organization's business needs. Independently deployable: Microservices are designed to be independently deployable units. Each microservice can be developed, tested, and deployed separately, without impacting other services. This enables agility and scalability in the deployment process. Highly maintainable: Microservices are often designed to be highly maintainable. They are smaller in scope and focused on specific tasks, making it easier to manage and maintain individual services. Additionally, microservices can be updated, patched, or replaced without affecting the entire system, facilitating easier maintenance and evolution of the application. Therefore, the criterion that is NOT typically met by a microservice is being tightly coupled.

Explanation

The valid troubleshooting strategy in this scenario is to enable function logging in the OCI console, add some print statements in your function code, and then view the logs to troubleshoot. Enabling function logging allows you to capture and store logs generated by your function during its execution. By adding print statements or log statements in your function code, you can output relevant information and debug messages to the logs. This helps you understand the execution flow, identify any errors or issues, and gather more information about the function's behavior. To troubleshoot the issue of the Python function not stopping the non-compliant OCI compute instances, you can follow these steps: Enable function logging in the OCI console: Enable logging for your function to ensure that logs are captured during its execution. Modify your function code: Add relevant print statements or log statements at key points in your code to output debug information or verify the execution flow. For example, you can print the instance details that are being evaluated for compliance. Invoke the function: Trigger the function execution either through an event or manually. View the logs: Access the function logs in the OCI console or retrieve them programmatically. Look for the expected print statements or log entries that indicate the status of each instance and the decisions made by the function. By reviewing the logs, you can analyze the output and identify any issues or discrepancies. It can help you determine if the function is correctly evaluating the compliance criteria, retrieving the instance details, or making the necessary API calls to stop the instances. You may need to adjust your code logic or investigate further based on the information provided in the logs. Enabling function remote debugging is not a suitable strategy in this case because it is primarily used for inspecting and debugging the function code during development, rather than troubleshooting issues in a deployed function. Enabling function tracing can provide insights into the execution flow and performance of the function but may not directly address the issue of the instances not being stopped. Ensuring that the application is deployed within the same OCI compartment as the instance is not directly related to troubleshooting the issue with the non-compliant instances. It is a consideration for access and permissions but does not provide specific insights into the problem at hand. Remember to refer to the Oracle Functions documentation and consult the official resources for detailed instructions and best practices on troubleshooting and monitoring Oracle Functions.

Idle-timeout is the parameter that is used to configure the time period during which an idle function will remain in memory before Oracle Functions removes its container image from memory2. The idle-timeout parameter is specified in seconds and can be set when creating or updating a function2. The default value for idle-timeout is 30 seconds and the maximum value is 900 seconds (15 minutes)2. If a function has the --provisioned-concurrency option enabled, the idle-timeout parameter is ignored and the function instances are always kept in memory3.Verified References: Creating Functions, Provisioned Concurrency