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| Section | Weight | Objectives |
|---|---|---|
| Cloud Native Applications and Containerization | 33% | - Oracle Cloud Infrastructure Registry
|
| Testing and Securing Cloud Native Applications | 13% | - Cloud Native Testing
|
| Leveraging Serverless Technologies for Cloud Native Development | 33% | - OCI Streaming
|
| Cloud Native Fundamentals | 11% | - Cloud Native Principles
|
| Monitoring and Troubleshooting Cloud Native Applications | 10% | - OCI Logging
|
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NEW QUESTION # 85
Which is ONE of the differences between a microservice and a serverless function?
Answer: B
Explanation:
The correct answer is: Microservices are used for long running operations while serverless functions are used for short running operations. One of the key differences between microservices and serverless functions is the duration of their execution. Microservices are typically designed to handle long-running operations and may continuously run and process requests as part of a larger system. They are often deployed and managed as long-lived services. On the other hand, serverless functions are designed to handle short-lived operations or tasks that execute in response to specific events or triggers. They are event-driven and execute only when invoked, providing a lightweight and ephemeral computing model. Serverless functions are often used for executing small, isolated pieces of code without the need for managing infrastructure or scaling concerns.
While both microservices and serverless functions can be stateless or stateful depending on the specific implementation, the key distinction lies in the typical duration and execution pattern of these components within an application architecture.
NEW QUESTION # 86
Oracle Functions monitors all deployed functions and collects and reports various metrics. Which is NOT available when viewing the Application metrics in the Oracle Cloud Infrastructure (OCI) Console?
Answer: D
Explanation:
The option that is NOT available when viewing the Application metrics in the Oracle Cloud Infrastructure (OCI) Console is: " The number of retries made by the function before failing due to an error. " When viewing the Application metrics in the OCI Console for Oracle Functions, you can typically see metrics related to the performance and usage of your functions. These metrics provide insights into how your functions are performing and being utilized. The following metrics are usually available: The number of requests to invoke a function that failed due to throttling: This metric indicates the number of requests that were not processed by the function due to reaching the configured concurrency limit or throttling settings. The length of time a function runs for: This metric represents the duration of each function invocation, measuring the time it takes for the function to complete its execution. The number of requests to invoke a function that failed with an error response: This metric counts the number of requests that encountered an error during the function invocation, resulting in a failed response. However, the number of retries made by the function before failing due to an error is not typically available as part of the Application metrics in the OCI Console.
The retries made by the function are usually handled at the invoker level, and the specific details of retries may not be captured as part of the application-level metrics. It ' s important to note that the availability of metrics and their specific details may vary depending on the version and configuration of Oracle Functions and the monitoring setup. It is recommended to refer to the Oracle Functions documentation and consult the official documentation for accurate and up-to-date information on available metrics.
NEW QUESTION # 87
In the shared responsibility model, who should perform patching, upgrading, and maintaining of the worker nodes in provisioned Oracle Container Engine for Kubernetes (OKE) clusters?
Answer: C
Explanation:
In the shared responsibility model, Oracle is responsible for securing the underlying cloudinfrastructure and platform services, while customers are responsible for securing theirdata and applications within the cloud4. For provisioned OKE clusters, Oracle manages the control plane (master nodes) of the Kubernetes cluster, while customers manage the data plane (worker nodes) of the cluster5. Therefore, it is the responsibility of the customer to perform patching, upgrading, and maintaining of the worker nodes in provisioned OKE clusters5. Customers can use tools such as Terraform or kubectl to automate these tasks5.
NEW QUESTION # 88
When utilizing the OCI Monitoring PostMetricData API to publish custom metrics, what is the default batch atomicity behavior applied to input validation for the metric objects?
Answer: A
Explanation:
Oracle explicitly defines the default batchAtomicity setting for PostMetricData asNON_ATOMIC. With NON_ATOMIC validation, at least one metric object in the request must pass validation for valid metric objects to be accepted. Individual objects that fail validation are rejected and identified in the returned summary with their associated errors. By comparison, ATOMIC requires every metric object in the batch to pass validation; if one object fails, the whole request fails validation. PARTIAL_COMMIT and TRANSACTIONAL are not supported values for the batchAtomicity parameter. The supported enumeration consists of ATOMIC and NON_ATOMIC, with NON_ATOMIC being the documented default. Therefore, B accurately reflects OCI Monitoring ' s default custom-metric ingestion behavior.
NEW QUESTION # 89
What is the difference between continuous delivery and continuous deployment in the DevOps methodology?
(Choose the best answer.)
Answer: B
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 utilizes 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.
NEW QUESTION # 90
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