The Oracle Cloud Infrastructure 2025 DevOps Professional exam (1Z0-1109-25) is designed for cloud engineers and DevOps practitioners who implement and manage infrastructure automation, containerization, and CI/CD pipelines on Oracle Cloud Infrastructure. This certification validates your ability to design and deploy modern DevOps solutions using Oracle Cloud services. This page provides a structured study roadmap, practical exam guidance, and resources to help you prepare efficiently and confidently.
Use this topic map to guide your study for Oracle 1Z0-1109-25 (Oracle Cloud Infrastructure 2025 DevOps Professional) within the Oracle Cloud and Oracle Cloud Infrastructure path.
The 1Z0-1109-25 exam uses multiple question types to assess both conceptual knowledge and practical decision-making in real-world DevOps scenarios.
Questions increase in complexity and emphasize practical application, ensuring you can make informed decisions in production DevOps workflows.
An effective study plan maps each topic to weekly goals, incorporates hands-on practice, and builds confidence through progressive testing. Allocate study time proportionally to topic weight and your current knowledge gaps.
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CI/CD configuration and Container Orchestration typically account for the largest portion of exam questions, followed by Infrastructure as Code and Monitoring. However, all six domains are tested, so balanced preparation across all topics is essential. Review the official exam guide and adjust study time based on your current experience level.
Infrastructure as Code (Terraform, Resource Manager) defines your cloud resources, while CI/CD pipelines automate the deployment of both infrastructure changes and application code. On the exam, expect questions that show how IaC templates are versioned in source control, triggered by CI/CD stages, and deployed to multiple environments. Understanding this integration is critical for scenario-based questions.
Hands-on experience significantly improves retention and confidence. Prioritize labs that involve creating a CI/CD pipeline end-to-end, deploying a containerized application to OKE, setting up monitoring and alarms, and using Terraform to provision infrastructure. If you have limited lab access, focus on understanding the concepts deeply through practice questions and scenario walkthroughs.
Frequent errors include confusing Kubernetes resource types, misunderstanding DevSecOps integration points (e.g., where to scan for vulnerabilities in the pipeline), overlooking monitoring best practices for distributed systems, and underestimating the importance of proper RBAC and security group configuration. Review explanations carefully during practice tests to avoid repeating these mistakes on exam day.
In the final week, focus on high-value activities: review all scenario-based questions and your weak-point topics, do one full-length timed practice test, and study explanations for any questions you missed. Avoid cramming new material; instead, reinforce understanding of core concepts and build confidence through targeted review. Get adequate sleep the night before the exam.
As a DevOps Engineer, you are tasked with securely storing and versioning your application's source code and automatically build, test, and deploy your application to Oracle Cloud Infrastructure (OCI) platform.
You are told to automate manual tasks and help software teams in managing complex environments at scale.
Which three OCI services can you choose to accomplish these tasks? (Choose three.)
Oracle Cloud Infrastructure Registry: This service allows you to securely store container images. It is essential for managing the container images used for deployment, making it an important part of the DevOps workflow.
DevOps project: OCI DevOps project is specifically designed to manage the CI/CD pipeline. It helps in automating tasks like building, testing, and deploying applications, which are key activities for managing complex environments and promoting agility in software development.
Container Engine for Kubernetes: Oracle Container Engine for Kubernetes (OKE) is used to deploy applications in a containerized environment. It provides a robust platform for deploying, managing, and scaling containerized applications, which is essential for handling complex environments at scale.
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 can you scale a deployment named nodejs-deployment to have two replicas?
The kubectl scale command is used to scale the number of replicas in a deployment. By specifying the --replicas flag, you define the desired number of replicas for the deployment.
(kubectl set replicas) is not the correct syntax for scaling a deployment.
(kubectl resize) is not a valid command for scaling a deployment.
(kubectl adjust) is also not a valid Kubernetes command.
As a cloud engineer, you are responsible for managing a Kubernetes cluster on the Oracle Cloud Infrastructure (OCI) platform for your organization. You are looking for ways to ensure reliable operations of Kubernetes at scale while minimizing the operational overhead of managing the worker node infrastructure.
Which cluster option is the best fit for your requirement?
Step 1: Understanding the Requirement
The goal is to ensure reliable operations of Kubernetes at scale while minimizing the operational overhead of managing worker node infrastructure. In this context, a solution is needed that abstracts away the complexity of managing, scaling, and maintaining worker nodes.
Step 2: Explanation of the Options
A . Using OCI OKE managed nodes with cluster autoscalers
While this option provides managed node pools and uses cluster autoscalers to adjust resources based on demand, it still requires some level of management for the underlying worker nodes (e.g., patching, upgrading, monitoring).
Operational overhead: Moderate.
B . Using OCI OKE virtual nodes
Virtual nodes in OCI OKE are a serverless option for running Kubernetes pods. They remove the need to manage underlying worker nodes entirely.
OCI provisions resources dynamically, allowing scaling based purely on pod demand.
There's no need for node management, patching, or infrastructure planning, which perfectly aligns with the requirement to minimize operational overhead.
Operational overhead: Minimal.
Best Fit for This Scenario: Since the requirement emphasizes minimizing operational overhead, this is the ideal solution.
C . Using Kubernetes cluster add-ons to automate worker node management
Kubernetes add-ons like Cluster Autoscaler or Node Problem Detector help in automating some aspects of worker node management. However, this still requires managing worker node infrastructure at the core level.
Operational overhead: Moderate to high.
D . Creating and managing worker nodes using OCI compute instances
This involves manually provisioning and managing compute instances for worker nodes, including scaling, patching, and troubleshooting.
Operational overhead: High.
Not Suitable for the Requirement: This option contradicts the goal of minimizing operational overhead.
Step 3: Why Virtual Nodes Are the Best Fit
Virtual Nodes in OCI OKE:
Virtual nodes provide serverless compute for Kubernetes pods, allowing users to run workloads without provisioning or managing worker node infrastructure.
Scaling: Pods are automatically scheduled, and the required infrastructure is dynamically provisioned behind the scenes.
Cost Efficiency: You only pay for the resources consumed by the running workloads.
Use Case Alignment: Eliminating the burden of worker node infrastructure management while ensuring Kubernetes reliability at scale.
Step 4: References and OCI Resources
OCI Documentation:
OCI Container Engine for Kubernetes Overview
Best Practices for Kubernetes on OCI:
Best Practices for OCI Kubernetes Clusters
As a DevOps engineer working on containerizing a microservices-based application to be hosted on OCI Cloud platforms, which step can help ensure that the container images have not been modified after being pushed to Oracle Cloud Infrastructure Registry (OCIR)?
To ensure that container images have not been modified after being pushed to the Oracle Cloud Infrastructure Registry (OCIR), you should sign the image. This involves using the Container Registry CLI to create a digital signature for the image, which associates the image with a master encryption key and key version stored in the OCI Vault service. This signature can then be verified at the time of deployment, ensuring that the image has not been tampered with since it was signed.
