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Most Recent Oracle 1Z0-1109-24 Exam Dumps
Prepare for the Oracle Cloud Infrastructure 2024 DevOps Professional exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Oracle 1Z0-1109-24 exam and achieve success.
The questions for 1Z0-1109-24 were last updated on Jun 7, 2026.
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As a DevOps engineer working with OCI DevOps, you are managing artifacts for a microservices application.
Based on your understanding of working with DevOps projects and artifacts, which statement is true?
Making artifacts immutable ensures that the build artifacts are not altered after being published. This is a best practice to maintain the integrity and consistency of the artifacts used in deployments, preventing unintentional changes that could introduce issues during subsequent deployment stages.
A DevOps engineer is asked to access an Oracle Cloud Infrastructure Container Engine for Kubernetes (OKE) cluster to deploy new applications and manage existing ones.
Which two statements are true? (Choose two.)
To access an OKE cluster using kubectl, you need to set up a Kubernetes configuration file (kubeconfig). By default, the kubeconfig file is named config and stored in the $HOME/.kube directory.
When a cluster's Kubernetes API endpoint has a public IP address, you can use Cloud Shell to access the cluster. Setting up a kubeconfig file is required to authenticate and manage the cluster.
A DevOps team is deploying a new version of their application to their production environment using the Canary deployment strategy in the OCI DevOps service. They want to ensure that the production environment is not affected by any potential issues caused by the new version.
Which statement is true in regards to the Canary deployment strategy?
In a Canary deployment strategy, a new version of an application is rolled out to a small subset of the production environment (the canary) first, while the majority of the production environment still runs the current stable version. This approach helps to detect potential issues before the new version is fully deployed.
The Invoke Function stage can be used as an optional step in the deployment pipeline to run additional validation (e.g., automated tests or other checks) on the new version before gradually shifting more traffic to it or moving to full production deployment.
A team wants to deploy artificial intelligence and machine learning workloads in their OCI Container Engine for Kubernetes (OKE) cluster. They prioritize strong isolation, cost-efficiency, and the ability to leverage serverless capabilities.
Which solution is best suited for their requirements?
Virtual nodes in OKE provide a serverless experience for deploying Kubernetes workloads, which means you do not have to manage or scale the underlying infrastructure. This solution is particularly cost-efficient because you only pay for the resources used by the pods, and it provides strong isolation for workloads.
Virtual nodes are well suited for AI/ML workloads as they allow users to easily scale compute resources without being constrained by the limits of individual worker nodes.
How do OCI DevOps Deployment Pipelines reduce risk and complexity of production applications?
OCI DevOps Deployment Pipelines automate the process of deploying applications to production environments. By using automated, repeatable deployment processes, they help reduce the risk of change-driven errors, which are often introduced during manual deployments. This automation reduces human errors and ensures consistency across environments, thus minimizing complexity and risk in production.
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