Pass the Oracle Oracle Cloud Infrastructure 1z0-1084-26 Questions and answers with CertsForce

DevOps principles directly address automation across the software delivery lifecycle. Oracle describes DevOps as collaboration between development and operations teams aimed at continuous delivery, with automation applied throughout planning, coding, building, testing, releasing, deploying, operating, and monitoring. OCI specifically identifies CI/CD tooling for automating build, test, release, and deployment activities. Containerization provides consistent application packaging, microservices define an architectural decomposition model, and serverless computing removes much of the underlying infrastructure-management responsibility. None of those technologies by itself defines the automated delivery lifecycle requested in the question. Continuous Integration and Continuous Delivery are core DevOps practices that make software changes repeatable, testable, and deployable at high frequency while reducing manual intervention and release risk. Therefore, the correct cloud-native pillar is DevOps Principles.

Explanation

The correct statements are: A common context to store configuration variables that are available to all functions in the application. A Docker image containing all the functions that share the same configuration. A logical group of functions.Explanation: An Oracle Functions application provides a common context for functions within the application. It allows you to store configuration variables that are accessible by all the functions in the application. Functions within the same application can share the same Docker image, which contains the common configuration and dependencies. An Oracle Functions application serves as a logical group that organizes related functions. Functions within the same application can be managed collectively, and they can interact and share resources within the application context.

OCI Queue is a service for enabling asynchronous (decoupled) communication in a serverless manner3. Queue handles high-volume transactional data that requires independent processing without loss or duplication3. Queue supports ordering of messages within a queue by using the FIFO (first-in-first-out) delivery option3. Therefore, using a single queue to process all transactions ensures that all transactions are processed in order and that no transaction is lost.Verified References: Overview of Queue

The best way to store and use secret information, such as database passwords, in Oracle Functions is to use the OCI Vault service. The OCI Vault service provides encryption and decryption capabilities for sensitive data. You can use the OCI Vault service to encrypt the password and store it as an application-level configuration variable. Then, you can use the generated key to decrypt the password in your function code when you need to access the database. Verified References: Oracle Functions: Using Key Management To Encrypt And Decrypt Configuration Variables

The Strangler Pattern is specifically designed for incremental modernization of a monolithic application. Oracle ' s cloud-native guidance describes it as gradually replacing portions of a monolith with microservices over time, minimizing disruption and avoiding the operational risk of a complete " big bang " rewrite. New functionality or migrated capabilities are implemented as independent services while remaining functionality continues to operate in the existing monolith. Eventually, the legacy application can be retired after its responsibilities have been progressively replaced. The Saga Pattern instead manages distributed transactions, the Sidecar Pattern places supporting functionality beside an application workload, and the Transactional Outbox Pattern provides reliable coordination between database changes and event publishing. Therefore, the pattern matching gradual monolith decomposition is the Strangler Pattern.

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.

Oracle ' s microservices design guidance explicitly identifies responsive behavior, backward compatibility, flexible communication, and idempotency as important requirements. Flexible communication doesnotrequire every microservice to use one synchronous protocol. Oracle states that each microservice can specify the protocol used between clients and the API gateway as well as the protocol used between individual microservices. This flexibility supports loose coupling and allows synchronous or asynchronous communication where appropriate. Oracle also states that microservices should return a response even when the service fails, API changes should remain backward-compatible with existing clients, and repeated calls should produce the same outcome when idempotency is required. Consequently, option C directly contradicts Oracle ' s documented flexible-communication principle and is the NOT valid statement.

The correct command is oci monitoring metric-data summarize-metrics-data. Oracle defines this operation specifically for retrieving aggregated metric data that matches a Monitoring Query Language (MQL) expression. The command accepts parameters including the compartment OCID, metric namespace, and --query-text, which can contain expressions such as CpuUtilization[1m].mean(). The post operation performs the opposite function: it publishes custom metric data into OCI Monitoring rather than retrieving it. query and retrieve are not valid subcommands under oci monitoring metric-data. Therefore, when an automation script must obtain aggregated CPU utilization or another metric series from Monitoring, summarize-metrics-data is the documented OCI CLI operation.

The Saga Design Pattern is specifically intended for distributed transactions across microservices without the extended locking associated with Two-Phase Commit. Oracle explains that a Saga decomposes a business transaction into a sequence of independent local transactions. After completing its local operation, each service publishes an event or message that triggers the next participant. If a subsequent step fails, corresponding compensating transactions reverse previously completed operations and restore consistent business state. This approach shortens lock duration and supports eventual consistency across separate databases. Transactional Outbox solves reliable database-update-and-message-publishing coordination but does not by itself manage the entire distributed transaction sequence. Therefore, the required pattern is the Saga Design Pattern.

Explanation

The two components that are part of the Cloud Native Computing Foundation (CNCF) container runtime are: containerd: containerd is an open-source container runtime that provides a runtime environment for containers, including managing container images, executing containers, and handling container lifecycle events. It is designed to be lightweight and extensible, providing the necessary functionality to run containers efficiently. runc: runc is a lightweight container runtime that serves as a reference implementation of the Open Container Initiative (OCI) runtime specification. It is responsible for launching and managing containers based on OCI specifications, including handling container isolation, namespaces, cgroups, and other low-level container operations. These two components, containerd and runc, are widely used in the container ecosystem and are part of the CNCF ' s efforts to promote and develop open-source technologies for cloud-native computing.