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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Testing and Securing Cloud Native Applications | 13% | - Secrets management with OCI Vault - Application security best practices - Testing strategies and secure deployment configurations |
| Topic 2: Leveraging Serverless Technologies for Cloud Native Development | 33% | - API-driven architectures using API Gateway - Oracle Functions development and management - Event-driven architecture with OCI Events, Streaming, and Queue |
| Topic 3: Cloud Native Applications and Containerization | 33% | - Building containerized applications with Docker - Deployment and management with Oracle Kubernetes Engine (OKE) - Oracle Container Registry (OCIR) usage |
| Topic 4: Cloud Native Fundamentals | 11% | - OCI developer services and tools overview - DevOps concepts and CI/CD workflows - Cloud-native principles and microservices architecture |
| Topic 5: Monitoring & Troubleshooting Cloud Native Applications | 10% | - Centralized logging and metrics collection - Application performance monitoring and tracing - Troubleshooting containerized and serverless workloads |
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NEW QUESTION # 83
You are developing an asynchronous, decoupled billing microservice that consumes payment messages from an Oracle Cloud Infrastructure (OCI) Queue. You notice that some corrupted payment payloads are causing the consumer application to fail and restart repeatedly, leaving the messages unprocessed and blocking the queue. To isolate these toxic messages, you want to redirect them to a Dead Letter Queue (DLQ) after 5 failed delivery attempts.
Which TWO configuration steps or characteristics must you apply to implement this solution?
Answer: A,C
Explanation:
The supplied Word answer key requires correction here. Current Oracle Queue documentation explicitly states that adead letter queue is automatically created when a queue is created. Therefore, option C is correct and option B is not. Oracle also provides the Maximum delivery attempts setting, which controls how many unsuccessful deliveries can occur before a problematic message is transferred to the DLQ. Setting that value to 5 implements the requested retry threshold. No separately provisioned target queue is required, consumer groups are optional and unrelated to enabling DLQ functionality, and administrators do not create an IAM policy authorizing a source queue resource to write to its automatically associated DLQ. Consequently, the verified current answer isA, C, not the Word file ' s A, B.
NEW QUESTION # 84
You are developing a Python microservice that needs to consume real-time telemetry data from a specific OCI Stream partition, beginning only with new messages that are published after your consumer client connects.
Which cursor type must you specify when invoking the create_cursor API call?
Answer: C
Explanation:
The LATEST cursor type positions the consumer at the most recent point in the stream so that it receives only messages published after the cursor is created. Oracle explicitly states that a cursor based on the most recent message allows consumption only of messages subsequently added to the stream. TRIM_HORIZON has the opposite behavior: it begins with the oldest message still available inside the stream ' s retention period.
AFTER_OFFSET begins immediately after a supplied partition offset, while AT_TIME begins from a specified timestamp. Because the requirement is to ignore all historical telemetry already retained in the partition and consume only newly arriving records, LATEST is the correct cursor type for the CreateCursor operation.
NEW QUESTION # 85
Your team has been tasked with debugging a Cloud Native application developed using the following Oracle Cloud Infrastructure (OCI) services: Object Storage, Events, Functions, API Gateway, and Autonomous Database. Which of these is NOT a valid option for troubleshooting issues in OCI? (Choose the best answer.)
Answer: E
Explanation:
To troubleshoot issues in OCI, the option that is not valid is: Trace performance issues in the Application Performance Monitoring service by enabling Function traces. While the Application Performance Monitoring service in OCI allows you to monitor and trace the performance of your applications, it is specifically designed for monitoring OCI Functions (serverless functions) and does not directly apply to all types of applications. The other options mentioned, such as configuring logs in the OCI Logging service, leveraging OCI Cloud Guard for debug logs, viewing service metrics in the OCI Monitoring service, and using OCI Service Connector Hub for log forwarding, are valid options for troubleshooting and monitoring applications in OCI.
NEW QUESTION # 86
Which node configuration in Oracle Cloud Infrastructure Container Engine for Kubernetes provides a serverless experience with granular pod-level elasticity and billing?
Answer: A
Explanation:
OKE Virtual Nodes provide Oracle ' s serverless Kubernetes execution model. Oracle manages the underlying node infrastructure, eliminating the need for customers to provision, patch, upgrade, scale, or troubleshoot conventional worker-node infrastructure. Resource allocation and elasticity occur at the pod level, allowing workloads to scale without planning the capacity of a conventional node pool. Oracle also describes Virtual Nodes as providing pay-per-use pricing based on the compute resources consumed by each Kubernetes pod rather than charging for entire worker servers that might contain unused capacity. Managed, bare metal, and self-managed nodes remain infrastructure-oriented worker-node models and therefore do not provide the same serverless pod-level operating model. Consequently, Virtual Nodes are the configuration designed for granular elasticity and pod-oriented consumption.
NEW QUESTION # 87
What is the difference between continuous delivery and continuous deployment in the DevOps methodology?
(Choose the best answer.)
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 # 88
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