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| Section | Weight | Objectives |
|---|---|---|
| Cloud Native Fundamentals | 11% | - Cloud Native Principles
|
| Monitoring & Troubleshooting Cloud Native Applications | 10% | - OCI Monitoring
|
| Cloud Native Applications and Containerization | 33% | - Docker and Containerization
|
| Leveraging Serverless Technologies for Cloud Native Development | 33% | - OCI Queue
|
| Testing and Securing Cloud Native Applications | 13% | - Cloud Native Testing
|
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NEW QUESTION # 123
A developer using Oracle Cloud Infrastructure (OCI) API Gateway needs to authenticate the API requests to their web application. The authentication process must be implemented using a custom scheme which accepts string-based parameters from the API caller. Which approach should the developer use in this scenario?
Answer: B
Explanation:
In the given scenario, the developer should use the approach of creating an authorizer function using token- based authorization. Token-based authorization is a commonly used approach for authenticating API requests.
It involves generating and issuing tokens to API callers, which they can then include in the requests they make to the API. The tokens serve as proof of authentication and are validated by the server to ensure the caller ' s identity and access rights. By creating an authorizer function using token-based authorization, the developer can implement a custom scheme that accepts string-based parameters from the API caller. This allows the developer to define their own authentication logic and validate the provided tokens according to their requirements. The authorizer function can be configured in the OCI API Gateway to be invoked before forwarding the request to the web application. It will perform the necessary token validation and authentication checks, allowing only authorized requests to access the protected resources of the web application.
NEW QUESTION # 124
Your DevOps team wants to configure a critical alert in OCI Monitoring for a payment gateway microservice application. The security architecture mandate requires that an alert must only fire if the average transaction latency exceeds 500 milliseconds over a sliding 15-minute interval. To avoid individual instance alerts, the query must aggregate all resource metrics within the target compartment together into a single unified stream before checking the threshold.
Which Monitoring Query Language (MQL) expression correctly satisfies all these requirements?
Answer: B
Explanation:
In OCI Monitoring Query Language, grouping() aggregates multiple matching metric streams into a common result rather than retaining separate streams for individual resources. Oracle ' s documentation demonstrates this syntax with expressions such as IopsRead[1m]{...}.grouping().max(). Here, [15m] establishes the metric aggregation interval, .mean() calculates the average transaction latency, and > 500 supplies the alarm threshold. groupBy(resourceId) would preserve separate result streams by resource ID, which directly contradicts the requirement to evaluate all resource metrics as one unified stream. filter(resourceId) is not valid grouping syntax, and absent() is designed to detect missing metric data rather than evaluate latency values. Therefore, TransactionLatency[15m].grouping().mean() > 500 correctly implements the stated aggregation and threshold logic.
NEW QUESTION # 125
Which term describes a group formed by a master machine and a worker machine in a Kubernetes architecture?
Answer: B
Explanation:
The term that describes a group formed by a master machine and a worker machine in a Kubernetes architecture is " Cluster " . A cluster in Kubernetes consists of one or more master machines and multiple worker machines (also known as nodes). The master machine manages the overall control plane and orchestrates the deployment and management of containers on the worker nodes. The worker nodes are responsible for running the containers and executing the workloads. The cluster is the fundamental unit of organization and management in Kubernetes, providing the infrastructure and resources to run and manage containerized applications. It ensures high availability, scalability, and fault tolerance for the applications deployed within it.
NEW QUESTION # 126
Your organization mandates that all containerized workloads deployed to Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE) must utilize Kubernetes NetworkPolicy resources, such as Calico, to enforce strict micro-segmentation of traffic. You have deployed these workloads to an enhanced OKE cluster using virtual node pools to minimize infrastructure maintenance. During testing, you discover that the Calico installation fails because NetworkPolicy resources and third-party CNI policy integrations are completely unsupported on this specific node configuration. How should you resolve this security implementation challenge while continuing to use VCN-Native Pod Networking?
Answer: D
Explanation:
Oracle explicitly states that virtual nodes do not support Kubernetes NetworkPolicy resources or network providers such as Calico and Cilium that provide NetworkPolicy enforcement. Virtual nodes support only OCI VCN-Native Pod Networking and cannot use Flannel or other third-party CNI plugins. By contrast, Calico can be installed with managed node pools while retaining VCN-native pod networking. This combination enables Kubernetes NetworkPolicy objects to enforce pod-level traffic controls and micro- segmentation. An IAM policy or network security list cannot substitute for Kubernetes NetworkPolicy because OCI network controls and Kubernetes pod policy enforcement operate at different layers. Therefore, when Calico-based NetworkPolicy enforcement is mandatory, migrating the workload from virtual nodes to managed node pools is the supported OKE architecture.
NEW QUESTION # 127
Kubernetes includes various elements such as compute, network, and storage. Compute is essentially CPU (units) and memory (bytes). Within an OKE cluster, what is considered to be the smallest unit of deployment with respect to compute?
Answer: A
Explanation:
A pod is the smallest and simplest unit in the Kubernetes object model that you create or deploy2. A pod represents a single instance of a running process in your cluster. Pods contain one or more containers, such as Docker containers. When you create a pod, you define how much CPU and memory (RAM) each container needs. A pod can also include storage volumes, IP addresses, options that govern how the container(s) should run, and more2. Pods are the basic building blocks of larger Kubernetes constructs such as deployments, replica sets, and services2.
NEW QUESTION # 128
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