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| Section | Weight | Objectives |
|---|---|---|
| Monitoring & Troubleshooting Cloud Native Applications | 10% | - Centralized logging and metrics collection - Troubleshooting containerized and serverless workloads - Application performance monitoring and tracing |
| Cloud Native Fundamentals | 11% | - OCI developer services and tools overview - Cloud-native principles and microservices architecture - DevOps concepts and CI/CD workflows |
| Testing and Securing Cloud Native Applications | 13% | - Application security best practices - Testing strategies and secure deployment configurations - Secrets management with OCI Vault |
| Leveraging Serverless Technologies for Cloud Native Development | 33% | - Oracle Functions development and management - API-driven architectures using API Gateway - Event-driven architecture with OCI Events, Streaming, and Queue |
| Cloud Native Applications and Containerization | 33% | - Oracle Container Registry (OCIR) usage - Building containerized applications with Docker - Deployment and management with Oracle Kubernetes Engine (OKE) |
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NEW QUESTION # 24
Your cloud-native banking microservice retrieves API tokens stored in OCI Vault. To meet strict security compliance standards, you must configure secret rules on these vault secrets. The security policies mandate that the secret contents must automatically expire and have their retrieval blocked 30 days after creation, and any previously used token content must never be allowed for reuse, even if the older secret version containing that content has been deleted. Which TWO configurations must you specify within the secret rules to satisfy these compliance requirements?
Answer: D,E
Explanation:
OCI Vault provides both Secret Expiry Rules and Secret Reuse Rules. secret_version_expiry_interval uses an ISO 8601 duration, so P30D establishes a 30-day validity period. Setting is_secret_content_retrieval_blocked_on_expiry to true ensures secret contents cannot be retrieved after expiry, satisfying the first requirement. For the second requirement, a SECRET_REUSE_RULE prevents previously used secret contents from being reused across versions. Oracle ' s SDK documentation confirms that is_enforced_on_deleted_secret_versions=true extends that restriction even when the previous secret version has been deleted. Setting either Boolean to false would weaken the stated controls.
HSM_PURGE_RULE is not one of the documented OCI Vault secret-rule types. Therefore, C and D jointly satisfy both requirements.
NEW QUESTION # 25
Which statement is NOT valid regarding autoscaling configurations in Oracle Cloud Infrastructure Container Engine for Kubernetes (OKE)?
Answer: C
Explanation:
Oracle explicitly lists Kubernetes Cluster Autoscaler among the deploymentsnot supported when using OKE virtual nodes. Virtual nodes provide a serverless data-plane model in which Oracle manages the underlying compute capacity, so customers do not resize a conventional virtual-node pool through Kubernetes Cluster Autoscaler. Cluster Autoscaler remains applicable to managed node pools, where worker-node capacity can be increased or decreased according to scheduling demand. Oracle also identifies Vertical Pod Autoscaler as unsupported on virtual nodes, while Metrics Server is supported through a deployment method adapted for virtual nodes. Horizontal Pod Autoscaler operates at the pod/deployment level and can adjust replica counts without requiring customers to resize virtual-node infrastructure. Therefore, B is the NOT valid statement because it incorrectly claims Cluster Autoscaler can resize both managed and virtual node pools.
NEW QUESTION # 26
Which statement about microservices is FALSE?
Answer: D
Explanation:
The correct answer is: " Multiple microservices can run in one process. " The statement that is FALSE about microservices is: " Multiple microservices can run in one process. " Microservices are designed to be independent and autonomous services that can be deployed, scaled, and managed separately. Each microservice typically runs as its own separate process. This separation allows for loose coupling and independent scalability of individual services. Running multiple microservices in a single process would violate the fundamental principle of microservices architecture, which emphasizes the isolation and independence of services. Combining multiple microservices into a single process would tightly couple them, making it difficult to independently manage, scale, and update each service. The other statements provided are true about microservices: It is fairly common for microservices to communicate with HTTP: Microservices often communicate with each other using lightweight protocols like HTTP/REST. This allows for interoperability, flexibility, and ease of communication between microservices. Microservices are typically designed around business capabilities: Microservices architecture advocates designing services based on specific business capabilities or functionalities. Each microservice focuses on a specific business domain or task, enabling modular and scalable development. They are independently deployable: Microservices are designed to be independently deployable units. This means that each microservice can be developed, tested, deployed, and updated separately without affecting other services. This flexibility allows for faster development cycles and more efficient scalability.
NEW QUESTION # 27
To effectively test your cloud native applications for " unknown unknowns " , you need to employ various testing and deployment strategies. Which strategy involves exposing new functionality or features to only a small set of users?
Answer: B
Explanation:
The strategy that involves exposing new functionality or features to only a small set of users is called Canary Deployment. Canary deployment is a technique used in software development and deployment where a new version of an application or feature is released to a small subset of users or a specific group of servers. This allows for testing and gathering feedback on the new functionality in a controlled and limited environment before making it available to a wider audience. In a canary deployment, a small portion of the traffic is routed to the new version while the majority of the traffic still goes to the stable version. This allows for monitoring and evaluation of the new functionality in real-world conditions while minimizing the impact of any potential issues or bugs. If the new version performs well and meets the desired criteria, it can then be gradually rolled out to a larger user base or all servers. By exposing the new functionality or features to a small set of users initially, canary deployment helps in identifying any unforeseen issues, gathering feedback, and ensuring the stability and reliability of the application before a full deployment.
NEW QUESTION # 28
Your development team has deployed a fleet of web application servers across three fault domains in a specific compartment in OCI. To simplify operational dashboards, you must construct a single Monitoring Query Language (MQL) expression that calculates the average CPU utilization for each individual fault domain, rather than plotting each server individually. The expression must output exactly three lines, one for each fault domain, on the resulting Metrics Explorer chart.
Which MQL expression correctly fulfills these requirements?
Answer: A
Explanation:
Oracle Monitoring documents groupBy(x) specifically for aggregating metric streams according to a shared dimension. Oracle ' s own fault-domain example uses the exact expression CpuUtilization[1m].groupBy (faultDomain).mean(). The resulting chart contains one aggregated metric stream for each fault domain, which means a compartment containing three fault domains produces three lines rather than one line per Compute instance. grouping() combines all selected metric streams into a single aggregate instead of retaining separate fault-domain groups. filter(faultDomain) is not the appropriate MQL grouping operation, and split() is not the documented operator for this requirement. Because the scenario requires mean CPU utilization separately aggregated for each value of the faultDomain dimension, option B exactly matches Oracle ' s documented MQL pattern.
NEW QUESTION # 29
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