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Latest 1Z0-1084-25 Dumps Files, Reliable 1Z0-1084-25 Exam Camp

Latest 1Z0-1084-25 Dumps Files, Reliable 1Z0-1084-25 Exam Camp

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Oracle Cloud Infrastructure 2025 Developer Professional Sample Questions (Q38-Q43):

NEW QUESTION # 38
What is the difference between continuous delivery and continuous deployment in the DevOps methodology? (Choose the best answer.)

  • A. Continuous delivery utilizes automatic deployment to a development environment, whereas continuous deployment involves automatic deployment to a production environment.
  • B. Continuous delivery requires automatic linting, whereas continuous deployment testing must be run manually.
  • C. Continuous delivery involves automation of developer tasks, whereas continuous deployment involves manual operational tasks.
  • D. Continuous delivery is a process that Initiates deployment manually, whereas continuous deployment is based on automating the deployment process.

Answer: A

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 # 39
(CHK_4>3) Your development team decides to create and deploy some business logic to serverless Oracle Functions. You are asked to help facilitate the monitoring, logging, and tracing of these services. Which is NOT valid about troubleshooting Oracle Functions?

  • A. Oracle Functions invocation logs are enabled at the application level.
  • B. Oracle Functions metrics are available at both the function and application level.
  • C. Oracle Functions invocation is enabled by default
  • D. Oracle Functions tracing is enabled at the function level.

Answer: D

Explanation:
The option that is NOT valid about troubleshooting Oracle Functions is: "Oracle Functions tracing is enabled at the function level." In Oracle Functions, tracing is not enabled at the function level. Instead, tracing is enabled at the application level. When you enable tracing for an application, it applies to all the functions within that application. Tracing allows you to capture detailed information about the execution flow and performance of the functions, helping you analyze and debug issues. The other options mentioned are valid: Oracle Functions invocation logs are enabled at the application level. Invocation logs provide visibility into the details of function invocations, including input, output, duration, and any error messages. These logs are generated and stored by Oracle Functions, and you can access them for troubleshooting and monitoring purposes. Oracle Functions invocation is enabled by default. Once you deploy a function, it becomes invocable by default. You can configure different triggers to invoke the function, such as HTTP requests, scheduled events, or events from other Oracle Cloud Infrastructure services. Oracle Functions metrics are available at both the function and application level. Metrics provide insights into the usage, performance, and behavior of functions. They can include metrics such as invocations per minute, average duration, and error counts. These metrics can be viewed in the Oracle Cloud Infrastructure Console or accessed programmatically through APIs. It's important to note that the specific configuration and behavior of monitoring, logging, and tracing in Oracle Functions may depend on the version, configuration, and options you have chosen. It is recommended to refer to the Oracle Functions documentation and consult the official documentation for accurate and up-to-date information on troubleshooting and monitoring Oracle Functions.


NEW QUESTION # 40
Which of these is a valid use case for OCI Queue?

  • A. Building decoupled and scalable systems
  • B. Sending real-time streaming data
  • C. Storing and retrieving large files
  • D. Managing network traffic between services

Answer: A

Explanation:
OCI Queue is a fully managed serverless service that helps decouple systems and enable asynchronous operations2. Queue handles high-volume transactional data that requires independently processed messages without loss or duplication2. A valid use case for OCI Queue is building decoupled and scalable systems, such as event-driven architectures or microservices-based applications2. For example, you can use Queue to decouple your application and build an event-driven architecture. Decoupling ensures that individual application components can scale independently and that you can future-proof your design so that as new application components are built, they can publish or subscribe to the queue2.


NEW QUESTION # 41
Which is the smalled unit of Kubernetes architecture?

  • A. Container
  • B. Cluster
  • C. Node
  • D. Pod

Answer: D

Explanation:
The smallest unit of Kubernetes architecture is a Pod. A Pod is a logical grouping of one or more containers that are deployed together on the same host and share the same network namespace, storage, and other resources. It represents the smallest deployable unit in Kubernetes and is used to encapsulate and manage one or more closely related containers. Containers within a Pod are scheduled and deployed together, allowing them to communicate and share resources efficiently.


NEW QUESTION # 42
With the volume of communication that can happen between different components in cloud-native applications, it is vital to not only test functionality, but also service resiliency. Which statement is true regarding service resiliency?

  • A. Resiliency testing can be done only in a test environment.
  • B. Resiliency is about avoiding failures.
  • C. Resiliency is about not bringing a service to a functioning state after a failure.
  • D. Resiliency is about recovering from failures without downtime or data loss.

Answer: D

Explanation:
The correct answer is: "Resiliency is about recovering from failures without downtime or data loss." Service resiliency, in the context of cloud-native applications, is the ability of a service or system to recover from failures and continue functioning without downtime or data loss. It involves designing and implementing mechanisms to handle failures, such as network outages, hardware failures, or software errors, in a way that minimizes the impact on the overall system. The goal of resiliency is to ensure that the application or service can continue to operate and provide a certain level of functionality, even in the face of failures. This typically involves techniques such as redundancy, fault tolerance, and graceful degradation. By implementing resiliency measures, a cloud-native application can recover and adapt to failures, maintain availability, and preserve data integrity. The other statements are not accurate regarding service resiliency: Resiliency is not about not bringing a service to a functioning state after a failure. Instead, it is about recovering from failures and ensuring continued functionality. Resiliency is not about avoiding failures entirely. While it is desirable to prevent failures, resiliency focuses on the ability to handle and recover from failures when they do occur. Resiliency testing is not limited to a test environment. It is important to test and validate the resiliency measures in both test environments and production environments to ensure the application can effectively handle failures in real-world scenarios.


NEW QUESTION # 43
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