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| Section | Weight | Objectives |
|---|---|---|
| Cloud Native Applications and Containerization | 33% | - Container Orchestration
|
| Monitoring & Troubleshooting Cloud Native Applications | 10% | - OCI Monitoring
|
| Leveraging Serverless Technologies for Cloud Native Development | 33% | - API Gateway
|
| Cloud Native Fundamentals | 11% | - Microservices Architecture
|
| Testing and Securing Cloud Native Applications | 13% | - Cloud Native Security
|
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NEW QUESTION # 28
Which term describes a group formed by a master machine and a worker machine in a Kubernetes architecture?
Answer: D
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 # 29
Which statement is NOT valid regarding testing methodologies for cloud native applications?
Answer: A
Explanation:
Statement D is NOT valid. Oracle ' s cloud application architecture guidance explicitly describes integration testing as validating interactions and data flow between components, modules, and services. In a cloud-native architecture, those interactions commonly occur through network-based APIs, service endpoints, databases, and messaging systems. Oracle recommends test environments that resemble production rather than restricting integration testing to isolated developer workstations. Unit testing does focus on individual units of code and typically isolates dependencies. API mocking can emulate unavailable dependent services, while performance testing evaluates responsiveness, scalability, and stability under varying workloads such as load and stress conditions. Therefore, the claim that integration testing is exclusively local and does not validate network communication contradicts the actual purpose of integration testing.
NEW QUESTION # 30
What is the open source engine for Oracle Functions?
Answer: A
Explanation:
The Fn Project is an open source serverless computing platform that serves as the engine for Oracle Functions. It provides a runtime environment for executing functions in a serverless architecture. The Fn Project enables developers to build and deploy functions using different programming languages, including Java, Python, Node.js, and more. The Fn Project is designed to be flexible and extensible, allowing developers to define functions as small units of code and execute them in response to events or triggers. It supports event- driven execution, allowing functions to be triggered by various events such as HTTP requests, messages from messaging systems, or changes in data. Oracle Functions leverages the Fn Project as its underlying engine, providing a managed serverless platform within the Oracle Cloud Infrastructure. It allows developers to easily develop, deploy, and manage functions using the familiar Fn Project framework and tooling. With Oracle Functions, developers can focus on writing their function code while leaving the infrastructure management, scaling, and operational tasks to the platform.
NEW QUESTION # 31
You are deploying a microservices-based application to an Oracle Cloud Infrastructure Container Engine for Kubernetes cluster running a modern Kubernetes release. You need to identify the underlying container runtime interface implementation that manages and runs your Open Container Initiative-compliant images within the worker nodes.
Which container runtime interface is utilized by the cluster for this purpose?
Answer: C
Explanation:
OKE transitioned from Docker toCRI-Obeginning with Kubernetes 1.20.8. Oracle documents CRI-O as its Kubernetes Container Runtime Interface implementation for modern OKE worker nodes. CRI-O is purpose- built for Kubernetes and runs Open Container Initiative-compliant images, so existing Docker-format images remain usable even though Docker Engine itself is no longer the underlying Kubernetes runtime. Oracle ' s current OKE documentation continues to reference CRI-O on modern node pools, including current releases where runtime configuration changes can affect container behavior. containerd is common in other Kubernetes distributions but is not the runtime identified by Oracle for these OKE nodes. rkt is obsolete, and Docker Engine was used only by older OKE versions. Therefore, D is correct.
NEW QUESTION # 32
As a developer, you have been tasked with implementing a microservices-based application. Which THREE technologies are best suited to accomplish the task? (Choose three.)
Answer: B,C,D
Explanation:
The three technologies best suited for implementing a microservices-based application are: Service Mesh: A service mesh is a dedicated infrastructure layer that provides features like service discovery, load balancing, encryption, authentication, and observability for microservices. It helps in managing the communication and interactions between microservices in a scalable and secure manner. Kubernetes: Kubernetes is an open- source container orchestration platform that enables the deployment, scaling, and management of containerized applications. It provides features like automated scaling, service discovery, load balancing, and self-healing capabilities, which are essential for managing microservices in a distributed environment.
Docker: Docker is a popular containerization platform that allows packaging applications and their dependencies into lightweight containers. It provides a consistent and portable environment for running microservices, enabling easy deployment and scalability. Docker also facilitates isolation and resource efficiency, making it an ideal choice for deploying microservices. While Big Data, Anomaly Detection, and Terraform are valuable technologies, they are not specifically focused on enabling the implementation of microservices-based applications.
NEW QUESTION # 33
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