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| Section | Weight | Objectives |
|---|
| Topic 1: Testing and Securing Cloud Native Applications | 13% | - Cloud Native Testing
- 1. Analyze and evaluate cloud native testing methodologies and develop effective strategies for testing cloud native applications
- OCI Vault
- 1. Use OCI Vault to securely store and manage encryption keys and sensitive configuration information
- Cloud Native Security
- 1. Apply security measures to overcome challenges with cloud native development
|
| Topic 2: Leveraging Serverless Technologies for Cloud Native Development | 33% | - Oracle Functions
- 1. Develop serverless applications with Oracle Functions
- OCI Streaming
- 1. Create integration between systems using OCI Streaming Service
- OCI Events
- 1. Build event-driven serverless applications using OCI Events Service
- OCI Queue
- 1. Facilitate asynchronous messaging for microservices with OCI Queue
- API Gateway
- 1. Create API gateways to process traffic from API clients and route it to back-end services
|
| Topic 3: Cloud Native Applications and Containerization | 33% | - Oracle Kubernetes Engine
- 1. Develop and deploy containerized applications on Oracle Kubernetes Engine
- OCI Registry
- 1. Use OCI Registry to pull and push container images
- Docker and Containerization
- 1. Explain Docker and the concepts around its architecture and components
- Container Orchestration
- 1. Discuss the role of container orchestration
|
| Topic 4: Monitoring & Troubleshooting Cloud Native Applications | 10% | - OCI Monitoring
- 1. Utilize OCI Monitoring Service to view metrics
- Monitoring, Logging, and Tracing
- 1. Perform tasks around monitoring, logging, and tracing
- OCI Logging
- 1. Use OCI Logging Service to enable, manage, and search logs
|
| Topic 5: Cloud Native Fundamentals | 11% | - Microservices Architecture
- 1. Explain the microservices architecture and discuss the design methodology of microservices
- Cloud Native Principles
- 1. Explain the fundamentals of cloud native and discuss the key pillars of cloud native development
|
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Oracle Cloud Infrastructure Developer Professional Sample Questions (Q162-Q167):
NEW QUESTION # 162
You have a containerized application that requires access to an Autonomous Transaction Processing (ATP) Database. Which option is NOT valid when the container is deployed in an OKE cluster? (Choose the best answer.)
- A. Create a Kubernetes secret with contents from the instance Wallet files. Use this secret to create a volume mounted to the appropriate path in the application deployment manifest.
- B. Enable Oracle REST Data Services for the required schemas and connect via HTTPS.
- C. Install the Oracle Cloud Infrastructure Service Broker on the Kubernetes cluster and deploy ServiceInstance and ServiceBinding resources for ATP. Then use the specified binding name as a volume in the application deployment manifest.
- D. Use Kubernetes secrets to configure environment variables on the container with ATP instance OCID, and OCI API credentials. Then use the CreateConnection API endpoint from the service runtime.
Answer: C
Explanation:
The option that is not valid for connecting to an Autonomous Transaction Processing (ATP) Database from a container in Kubernetes is: Install the Oracle Cloud Infrastructure Service Broker on the Kubernetes cluster and deploy ServiceInstance and ServiceBinding resources for ATP. Then use the specified binding name as a volume in the application deployment manifest. The Oracle Cloud Infrastructure Service Broker is not used for connecting to an ATP Database from a container in Kubernetes. The Service Broker is used for provisioning and managing cloud services directly from Kubernetes. It allows you to create and manage instances of OCI services using Kubernetes resources like ServiceInstance and ServiceBinding. To connect to an ATP Database from a container in Kubernetes, you can use one of the following valid options: Enable Oracle REST Data Services for the required schemas and connect via HTTPS. This involves enabling and configuring Oracle REST Data Services (ORDS) for the schemas in the ATP Database. You can then connect to the ATP Database using RESTful endpoints provided by ORDS. Use Kubernetes secrets to configure environment variables on the container with ATP instance OCID and OCI API credentials. Then use the CreateConnection API endpoint from the service runtime. This approach involves configuring the necessary environment variables on the container to provide the ATP instance OCID and OCI API credentials. The application can then use the OCI SDK or REST API (such as the CreateConnection endpoint) to establish a connection to the ATP Database. Create a Kubernetes secret with contents from the instance Wallet files. Use this secret to create a volume mounted to the appropriate path in the application deployment manifest. This method involves creating a Kubernetes secret that contains the necessary credentials from the ATP Database ' s instance wallet files. The secret can then be mounted as a volume in the application deployment, allowing the application to access the required credentials for connecting to the ATP Database. Both options 1 and 3 provide valid approaches for connecting to an ATP Database from a container in Kubernetes, depending on the specific requirements and preferences of the application.
NEW QUESTION # 163
In the DevOps lifecycle, what is the difference between continuous delivery and continuous deployment?
(Choose two.)
- A. Continuous delivery requires more automatic linting, while continuous deployment testing must be run manually.
- B. Continuous delivery is a process that initiates deployment manually, while continuous deployment is based on automating the deployment process.
- C. Continuous delivery involves automation of developer tasks, while continuous deployment involves manual operational tasks.
- D. Continuous delivery utilizes automatic deployment to a development environment, while continuous deployment involves automatic deployment to a production environment.
Answer: B,D
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 involves 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 # 164
Which statement is NOT valid regarding testing methodologies for cloud native applications?
- A. Integration testing is conducted exclusively on isolated local workstations and does not validate network-based communications.
- B. API mocking allows developers to validate a service ' s logic by simulating the behavior of dependent microservices that are offline.
- C. Unit testing focuses on validating individual blocks of code in complete isolation from database and external API dependencies.
- D. Performance testing evaluates system responsiveness under concurrent workloads to identify potential resource bottlenecks.
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 # 165
What can you use to dynamically make Kubernetes resources discoverable to public DNS servers? (Choose the best answer.)
- A. DynDNS
- B. kubeDNS
- C. CoreDNS
- D. ExternalDNS
Answer: D
Explanation:
To dynamically make Kubernetes resources discoverable to public DNS servers, you can use ExternalDNS.
ExternalDNS is a Kubernetes add-on that automates the management of DNS records for your Kubernetes services and ingresses. It can be configured to monitor the changes in your Kubernetes resources and automatically update DNS records in a supported DNS provider. By integrating ExternalDNS with your Kubernetes cluster, you can ensure that the DNS records for your services and ingresses are automatically created, updated, or deleted based on changes in your Kubernetes resources. This allows your Kubernetes resources to be discoverable by external systems through public DNS servers.
NEW QUESTION # 166
Which statement is NOT valid regarding autoscaling configurations in Oracle Cloud Infrastructure Container Engine for Kubernetes (OKE)?
- A. The Kubernetes Cluster Autoscaler can be deployed to automatically resize both managed node pools and virtual node pools when pod resource demands change.
- B. The Kubernetes Vertical Pod Autoscaler is restricted to managed node pools and is not supported for adjusting resources on virtual node pools.
- C. The Kubernetes Metrics Server can be deployed as a standalone program to collect resource metrics on both virtual node pools and managed node pools.
- D. The Kubernetes Horizontal Pod Autoscaler is supported for adjusting the replica count of deployments running on both virtual node pools and managed node pools.
Answer: A
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 # 167
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