Oracle 1Z0-1084-23 Exam Questions

In the shared responsibility model, Oracle is responsible for securing the underlying cloud infrastructure and platform services, while customers are responsible for securing their data 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.

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.

Visibility timeout is the concept in OCI Queue that is responsible for hiding a message from other consumers for a predefined amount of time after it has been delivered to a consumer1.The visibility timeout can be set at the queue level when creating a queue, or it can be specified when consuming or updating messages1.If a consumer is having difficulty successfully processing a message, it can update the message to extend its invisibility1.If a message's visibility timeout is not extended, and the consumer does not delete the message, it returns to the queue1. Verified Reference:Overview of Queue

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.

The correct answer is: Enable monitoring for all worker nodes in the cluster. Enabling monitoring for all worker nodes in the cluster is not required to collect and parse application logs using Oracle Cloud Infrastructure (OCI) Logging. Monitoring is a separate feature that allows you to collect metrics and monitor the health and performance of the worker nodes. To collect and parse application logs, you need to perform the following tasks: Set the OCI Logging option to Enabled for the cluster: This enables the OCI Logging service for the cluster. Create a dynamic group with a rule that includes all worker nodes in the cluster: This helps in targeting the logs generated by the worker nodes. Configure a custom log in OCI Logging with the appropriate agent configuration: This involves specifying the log source, log path, and log format to parse and collect the application logs. By completing these tasks, you can collect and parse the application logs generated by the applications running on the worker node compute instances in the OKE cluster.