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NEW QUESTION # 33
A developer has created another version of a microservice and wants 10% of the traffic to flow towards it for testing purposes. The application is already configured using OCI (Oracle Cloud Infrastructure) Service Mesh.
Which of the following steps is the right approach to achieve this goal?
- A. Use Kubernetes HPA (Horizontal Pod Autoscaler) to scale the new version of the microservice to handle
10% of the traffic automatically. - B. Create a new Kubernetes deployment for the new version of the microservice and set the trafficsplitting percentage to 10% in the Kubernetes service manifest.
- C. Create a new entry in the routeRules field of the ingress gateway route table manifest to configure traffic splitting between the old and new versions of the microservice and set the percentage to 10%.
- D. Create a new entry in the routeRules field of the virtual service route table manifest to configure traffic splitting between the old and new versions of the microservice and set the percentage to 10%.
Answer: D
NEW QUESTION # 34
Which technique is used for testing the entire user flow as well as the moving parts of a cloud native app, ensuring that there are no high-level discrepancies?
- A. Unit Testing
- B. Integration Testing
- C. Contract Testing
- D. End-to-end Testing
- E. Component Testing
Answer: D
Explanation:
End-to-end testing is a technique that involves checking the entire user flow as well as the moving parts of a cloud native app, ensuring that there are no high-level discrepancies3. End-to-end testing simulates real user scenarios and validates the functionality, performance, reliability, and security of the app from start to finish3. End-to-end testing has several benefits, such as3:
Comprehensive testing: You can test your app as a whole and verify that all the components work together as expected.
User-centric testing: You can test your app from the user's perspective and ensure that it meets the user's needs and expectations.
Quality assurance: You can test your app in a realistic environment and identify any issues or defects before releasing it to the users.
NEW QUESTION # 35
Which concept in OCI Queue is responsible for hiding a message from other consumers for a predefined amount of time after it has been delivered to a consumer?
- A. Maximum retention period
- B. Visibility timeout
- C. Delivery count
- D. Polling timeout
Answer: B
Explanation:
Visibility timeout is the concept in OCI Queue that is responsible for hiding a message from other consumers for a predefined amount of time after it has been delivered to a consumer1. The visibility timeout can be set at the queue level when creating a queue, or it can be specified when consuming or updating messages1. If a consumer is having difficulty successfully processing a message, it can update the message to extend its invisibility1. If a message's visibility timeout is not extended, and the consumer does not delete the message, it returns to the queue1. Verified Reference: Overview of Queue
NEW QUESTION # 36
In the DevOps lifecycle, what is the difference between continuous delivery and continuous deployment?
(Choose two.)
- A. Continuous delivery utilizes automatic deployment to a development environment, while continuous deployment involves automatic deployment to a production environment.
- B. Continuous delivery requires more automatic linting, while continuous deployment testing must be run manually.
- C. Continuous delivery involves automation of developer tasks, while continuous deployment involves manual operational tasks.
- D. Continuous delivery is a process that initiates deployment manually, while continuous deployment is based on automating the deployment process.
Answer: A,D
Explanation:
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 # 37
(CHK_1>3) You have an e-commerce application that loads customers' transactional data into the Oracle Cloud Infrastructure (OCI) Streaming service. The data must now be extracted and transformed before sending it to a third-party REST endpoint. You have been directed to leverage the OCI Service Connector Hub to automate this process. Which configuration option would address this requirement?
- A. Configure a new service connector as follows: * Source: Streaming * Task: API Gateway * Target: Functions
- B. Configure a new service connector as follows: * Source: Streaming * Task: None * Target: Notifications
- C. Configure a new service connector as follows: * Source: Streaming * Task: Functions * Target: Functions
- D. Configure a new service connector as follows: * Source: Streaming * Task: Functions * Target: API Gateway
- E. Configure a new service connector as follows: * Source: Streaming * Task: API Gateway * Target: Notifications
Answer: B
Explanation:
To address the requirement of extracting and transforming data from the Oracle Cloud Infrastructure (OCI) Streaming service and sending it to a third-party REST endpoint using the OCI Service Connector Hub, the best configuration option is: Configure a new service connector as follows: * Source: Streaming * Task: None * Target: Notifications By selecting the Streaming service as the source, you can capture the transactional data from the stream. Since there is a need to transform and send the data to a third-party REST endpoint, you don't need to specify any specific task in the connector. The target is set to Notifications, which allows you to send the transformed data to an endpoint outside of the OCI environment. Notifications can be configured to deliver the data to various supported destinations, including HTTP endpoints, email addresses, and more. This configuration enables you to automate the process of extracting data from the streaming service and sending it to the desired third-party REST endpoint, fulfilling the requirement of extracting, transforming, and forwarding the data.
NEW QUESTION # 38
In the DevOps lifecycle, what is the difference between continuous delivery and continuous deployment? (Choose two.)
- A. Continuous delivery utilizes automatic deployment to a development environment, while continuous deployment involves automatic deployment to a production environment.
- B. Continuous delivery requires more automatic linting, while continuous deployment testing must be run manually.
- C. Continuous delivery involves automation of developer tasks, while continuous deployment involves manual operational tasks.
- D. Continuous delivery is a process that initiates deployment manually, while continuous deployment is based on automating the deployment process.
Answer: A,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 # 39
What is the open source engine for Oracle Functions?
- A. OpenFaas
- B. Fn Project
- C. Knative
- D. Apache OpenWhisk
Answer: B
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 # 40
Which TWO are part of the Cloud Native Computing Foundation (CNCF) container runtime? (Choose two.)
- A. runc
- B. getcd
- C. rkt-o
- D. containerd
Answer: A,D
Explanation:
The two components that are part of the Cloud Native Computing Foundation (CNCF) container runtime are: containerd: containerd is an open-source container runtime that provides a runtime environment for containers, including managing container images, executing containers, and handling container lifecycle events. It is designed to be lightweight and extensible, providing the necessary functionality to run containers efficiently. runc: runc is a lightweight container runtime that serves as a reference implementation of the Open Container Initiative (OCI) runtime specification. It is responsible for launching and managing containers based on OCI specifications, including handling container isolation, namespaces, cgroups, and other low-level container operations. These two components, containerd and runc, are widely used in the container ecosystem and are part of the CNCF's efforts to promote and develop open-source technologies for cloud-native computing.
NEW QUESTION # 41
A DevOps engineer is troubleshooting the Meshifyd application, which is running in an Oracle Cloud Infrastructure (OCI) environment. The engineer has set up the OCI Logging service to store access logs for the application but notices that the logs from the Meshifyd application are not showing up in the logging service.
The engineer suspects that there might be an issue with the logging configuration. Which two statements are potential reasons for logs from the Meshifyd application not showing up in the OCI Logging service?
- A. The logconfig.json file has incorrect or missing information in the application namespace in the src field.
- B. The OCI Logging service is set up to pre access logs by creating a log group and custom log within the same compartment.
- C. The logconfig.json file has incorrect or missing OCID for the custom log group in the logGroupObjectId field.
- D. The logconfig.json file has incorrect or missing information in the application namespace in the paths field.
- E. The logconfig.json file has incorrect or missing OCID for the custom log in the logobjectId field.
Answer: C,E
Explanation:
Explanation
The logconfig.json file is a configuration file that specifies how the Unified Monitoring Agent collects and uploads custom logs to the OCI Logging service2. The logconfig.json file contains an array of objects, each representing a custom log configuration2. Each custom log configuration object has the following fields2:
* logGroupObjectId: The OCID of the log group where the custom log is stored.
* logObjectId: The OCID of the custom log.
* paths: An array of paths to files or directories containing the custom logs.
* src: A regular expression that matches the files containing the custom logs.
* parser: A parser definition that specifies how to parse the custom logs. If the logconfig.json file has incorrect or missing OCID for the custom log in the logobjectId field, or incorrect or missing OCID for the custom log group in the logGroupObjectId field, then the Unified Monitoring Agent will not be able to upload the custom logs to the OCI Logging service2. Therefore, these are potential reasons for logs from the Meshifyd application not showing up in the OCI Logging service. Verified References: Unified Monitoring Agent Configuration File
NEW QUESTION # 42
What are the TWO main reasons you would choose to implement a serverless architecture? (Choose two.)
- A. Automatic horizontal scaling
- B. Improved in-function state management
- C. No need for integration testing
- D. Easier to run long-running operations
- E. Reduced operational cost
Answer: A,E
Explanation:
The two main reasons to choose a serverless architecture are: Automatic horizontal scaling: Serverless architectures allow for automatic scaling of resources based on demand. The infrastructure automatically provisions and scales resources as needed, ensuring that applications can handle varying workloads efficiently. This eliminates the need for manual scaling and optimizes resource utilization. Reduced operational cost: Serverless architectures follow a pay-per-use model, where you are billed only for the actual execution time and resources consumed by your functions. This leads to cost savings as you don't have to pay for idle resources. Additionally, serverless architectures remove the need for managing and maintaining servers, reducing operational overhead and associated costs. No need for integration testing: Integration testing is still necessary in serverless architectures to ensure that functions integrate correctly with other components and services. Serverless functions can interact with various event sources, databases, and APIs, and testing is required to verify the integration points. Improved in-function state management: Serverless architectures typically encourage stateless functions that operate on short-lived requests or events. While there are mechanisms to manage state within a function, serverless architectures are designed to be stateless by default, promoting scalability and fault tolerance. Easier to run long-running operations: Serverless functions are generally designed for short-lived operations rather than long-running tasks. If you have a requirement for long-running operations, a serverless architecture may not be the ideal choice, as it has execution time limits and may not provide the necessary resources for extended execution.
NEW QUESTION # 43
What can you use to dynamically make Kubernetes resources discoverable to public DNS servers? (Choose the best answer.)
- A. DynDNS
- B. ExternalDNS
- C. CoreDNS
- D. kubeDNS
Answer: B
Explanation:
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 # 44
You want to push a new image in the Oracle Cloud Infrastructure (OCI) Registry. Which TWO actions would you need to perform? (Choose two.)
- A. Assign an OCI defined tag via OCI CLI to the image.
- B. Generate an API signing key to complete the authentication via Docker CLI.
- C. Assign a tag via Docker CLI to the image.
- D. Generate an OCI tag namespace in your repository.
- E. Generate an auth token to complete the authentication via Docker CLI.
Answer: C,E
Explanation:
Explanation
To push a new image to the Oracle Cloud Infrastructure (OCI) Registry, you would need to perform the following two actions: Assign a tag via Docker CLI to the image: Before pushing the image, you need to assign a tag to it using the Docker CLI. The tag helps identify the image and associate it with a specific version or label. Generate an auth token to complete the authentication via Docker CLI: To authenticate and authorize the push operation, you need to generate an auth token. This token is used to authenticate your Docker CLI with the OCI Registry, allowing you to push the image securely. Note: Generating an API signing key, assigning an OCI defined tag via OCI CLI, and generating an OCI tag namespace are not required steps for pushing a new image to the OCI Registry.
NEW QUESTION # 45
Having created a Container Engine for Kubernetes (OKE) cluster, you can use Oracle Cloud Infrastructure (OCI) Logging to view and search the logs of applications running on the worker node compute instances in the cluster. Which task is NOT required to collect and parse applicationlogs? (Choose the best answer.)
- A. Create a dynamic group with a rule that includes all worker nodes In the cluster.
- B. Configure a custom log in OCI Logging with the appropriate agent configuration.
- C. Enable monitoring for all worker nodes in the cluster.
- D. Set the OCI Logging option to Enabled for the cluster.
Answer: C
Explanation:
Explanation
The correct answer is: Enable monitoring for all worker nodes in the cluster. Enabling monitoring for all worker nodes in the cluster is not required to collect and parse application logs using Oracle Cloud Infrastructure (OCI) Logging. Monitoring is a separate feature that allows you to collect metrics and monitor the health and performance of the worker nodes. To collect and parse application logs, you need to perform the following tasks: Set the OCI Logging option to Enabled for the cluster: This enables the OCI Logging service for the cluster. Create a dynamic group with a rule that includes all worker nodes in the cluster: This helps in targeting the logs generated by the worker nodes. Configure a custom log in OCI Logging with the appropriate agent configuration: This involves specifying the log source, log path, and log format to parse and collect the application logs. By completing these tasks, you can collect and parse the application logs generated by the applications running on the worker node compute instances in the OKE cluster.
NEW QUESTION # 46
From a DevOps process standpoint, it is a good practice to keep changes to an application under version control. Which of the following allows changes to a Docker image to be stored in a version control system?
- A. Executing docker commit
- B. Updating Dockerfile
- C. Updating docker-compose.yml
- D. Executing docker save
Answer: A
Explanation:
The option that allows changes to a Docker image to be stored in a version control system is: docker commit The docker commit command is used to create a new image from a container's changes. It takes a running container as input, captures the changes made to it, and creates a new image with those changes. This new image can then be tagged and pushed to a registry, or saved locally. By using docker commit, you can effectively capture the changes made to a container as a new image and store it in a version control system along with the Dockerfile and other project files. This allows for reproducibility and traceability of changes to the Docker image over time.
NEW QUESTION # 47
As a cloud-native developer, you are designing an application that depends on Oracle Cloud Infrastructure (OCI) Object Storage wherever the application is running. Therefore, provisioning of storage buckets should be part of your Kubernetes deployment process for the application. Which of the following should you leverage to meet this requirement? (Choose the best answer.)
- A. Open Service Broker API
- B. OCI Container Engine for Kubernetes
- C. Oracle Functions
- D. OCI Service Broker for Kubernetes
Answer: D
Explanation:
To provision storage buckets as part of your Kubernetes deployment process for an application that depends on Oracle Cloud Infrastructure (OCI) Object Storage, you should leverage the OCI Service Broker for Kubernetes. OCI Service Broker for Kubernetes enables you to provision and manage OCI resources, including Object Storage buckets, directly from Kubernetes. It provides a Kubernetes-native experience for managing OCI services, allowing you to define and manage OCI resources as part of your application deployment process. By using the OCI Service Broker for Kubernetes, you can define the required Object Storage buckets in your Kubernetes manifests, and the service broker will handle the provisioning and management of those buckets in OCI, ensuring that they are available for your application wherever it is running.
NEW QUESTION # 48
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.)
- A. Docker
- B. Big Data
- C. Anomaly Detection
- D. Terraform
- E. Kubemetes
- F. Service Mesh
Answer: A,E,F
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 # 49
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