Oracle 1z0-1084-23 Exam Dumps - Actual Questions Answers

Explanation

The appropriate logging approach for services running in Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE) is: "All services log to standard output only." When running services in a containerized environment like OKE, it is recommended to follow the Twelve-Factor App methodology, which suggests treating logs as event streams. According to this methodology, services should write their log events to standard output (stdout) instead of writing to log files. By logging to standard output, the container runtime (such as Kubernetes) can collect and aggregate the logs generated by the services. These logs can then be accessed and managed through the container runtime's logging infrastructure. Logging to standard output offers several advantages in a containerized environment: Simplicity and consistency: Standardizing on logging to stdout ensures a consistent approach across different services, making it easier to manage and analyze logs. Log aggregation: The container runtime can collect the logs from all the running containers and provide centralized log management, allowing you to access and search logs from different services in one place. Scalability: Since logs are written to stdout, they can be easily handled by the container runtime's log management system, which can scale to handle large volumes of log data. Separation of concerns: By logging to stdout, the responsibility of managing log files and their rotation is shifted to the container runtime, allowing the services to focus on their core functionality. While it is possible to log to log files or external logging systems, the recommended approach in a containerized environment like OKE is to log to standard output and leverage the logging infrastructure provided by the container runtime.

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.

Explanation

The option that is not valid for connecting to an Autonomous Transaction Processing (ATP) Database from a container in Kubernetes is: Install the Oracle Cloud Infrastructure Service Broker on the Kubernetes cluster and deploy ServiceInstance and ServiceBinding resources for ATP. Then use the specified binding name as a volume in the application deployment manifest. The Oracle Cloud Infrastructure Service Broker is not used for connecting to an ATP Database from a container in Kubernetes. The Service Broker is used for provisioning and managing cloud services directly from Kubernetes. It allows you to create and manage instances of OCI services using Kubernetesresources like ServiceInstance and ServiceBinding. To connect to an ATP Database from a container in Kubernetes, you can use one of the following valid options: Enable Oracle REST Data Services for the required schemas and connect via HTTPS. This involves enabling and configuring Oracle REST Data Services (ORDS) for the schemas in the ATP Database. You can then connect to the ATP Database using RESTful endpoints provided by ORDS. Use Kubernetes secrets to configure environment variables on the container with ATP instance OCID and OCI API credentials. Then use the CreateConnection API endpoint from the service runtime. This approach involves configuring the necessary environment variables on the container to provide the ATP instance OCID and OCI API credentials. The application can then use the OCI SDK or REST API (such as the CreateConnection endpoint) to establish a connection to the ATP Database. Create a Kubernetes secret with contents from the instance Wallet files. Use this secret to create a volume mounted to the appropriate path in the application deployment manifest. This method involves creating a Kubernetes secret that contains the necessary credentials from the ATP Database's instance wallet files. The secret can then be mounted as a volume in the application deployment, allowing the application to access the required credentials for connecting to the ATP Database. Both options 1 and 3 provide valid approaches for connecting to an ATP Database from a container in Kubernetes, depending on the specific requirements and preferences of the application.