1z0-1084-24 Practice Exam Questions with Answers Oracle Cloud Infrastructure 2024 Developer Professional Certification

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.

Explanation

The maximum execution time of Oracle Functions is 300 seconds, which is equivalent to 5 minutes. This means that a function running within Oracle Functions cannot exceed a runtime of 5 minutes. If a function requires longer execution times, alternative approaches such as invoking external services asynchronously or using long-running processes should be considered. It is important to design functions with this execution time limitation in mind to ensure optimal performance and efficiency within the Oracle Functions platform.

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. Explanation: 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.

Explanation

The two true statements for serverless computing and serverless architectures are: Applications running on a FaaS (Functions as a Service) platform: Serverless architectures typically involve running code in the form of functions on a serverless platform. These functions are event-driven and executed in response to specific triggers or events. Serverless function execution is fully managed by a third party: In serverless computing, the cloud provider takes care of the infrastructure management and resource provisioning. The execution of serverless functions is handled automatically by the platform, relieving developers from the responsibility of managing servers or infrastructure. It's important to note that long running tasks are not typically suited for serverless architectures due to the event-driven nature of serverless functions. Also, while serverless functions may have state, it is recommended to avoid external storage dependencies and instead leverage stateless functions whenever possible. Additionally, scaling in serverless architectures is typically handled automatically by the platform, rather than being the responsibility of the application DevOps team.

Explanation

The correct answer is: "Edit the tenancy global retention policy." To ensure that container images never get deleted from the Oracle Cloud Infrastructure Registry (OCIR), you should edit the tenancy global retention policy. The tenancy global retention policy is a setting that determines the retention behavior for all the images in the OCIR across the entire tenancy. By editing this policy, you can define the retention behavior that suits your requirements. To edit the tenancy global retention policy, you would typically perform the following steps: Access the Oracle Cloud Infrastructure Console and navigate to the OCIR service. Go to the "Policies" section or "Settings" section in the OCIR service. Locate the tenancy global retention policy settings. Modify the retention policy to specify the desired retention behavior. In this case, you would set the policy to retain all images, ensuring they are never deleted from the repository. By setting the global policy of image retention to "Retain All Images," you can ensure that the container images in your OCIR repository are permanently retained and not subject to deletion based on any default or automatic retention rules. The other options mentioned are not directly related to ensuring that container images are never deleted from the repository: Creating a group and assigning a policy to perform lifecycle operations on images or writing a policy to limit access to the specific repository in your compartment are access control measures and do not address the retention of images. Setting the global policy of image retention to "Retain All Images" is the correct action to achieve the desired outcome of preventing image deletion from the repository.

Explanation

The step that is NOT required for setting up the Container Engine for Kubernetes (OKE) cluster access using a local installation of kubectl is to generate an Auth token from the OCI console. The authentication for accessing the OKE cluster using kubectl can be performed using the OCI CLI configuration, specifically the API signing key pair and the kubeconfig file. Here are the correct steps for setting up the OKE cluster access using a local installation of kubectl: Set up the kubeconfig file: The kubeconfig file contains the necessary information to authenticate and access the OKE cluster using kubectl. It includes details such as the cluster endpoint, authentication method, and credentials. Generate an API signing key pair (if you do not already have one) and upload the public key of the API signing key pair: The API signing key pair is used for authentication with the OCI services. The public key of the key pair needs to be uploaded to the OCI Console to associate it with your user account. Install and configure the Oracle Cloud Infrastructure (OCI) CLI: The OCI CLI provides a command-line interface to interact with the OCI services. It needs to be installed and configured with your OCI credentials, including the user's OCID, tenancy OCID, region, and the path to the API signing key pair. By completing these steps, you can configure kubectl to access and manage your OKE clusters from your local machine using the OCI CLI authentication configuration.

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.

Explanation

The valid statements regarding the OCI Container Engine for Kubernetes (OKE) service are: OKE automatically creates and configures new network resources for the new cluster. When creating a new OKE cluster, the service automatically provisions and configures the necessary network resources, such as VCNs, subnets, route tables, security lists, and load balancers, to support the cluster. Your tenancy must have sufficient quota on different types of resources. Before creating an OKE cluster, you need to ensure that your Oracle Cloud Infrastructure (OCI) tenancy has sufficient quota for the required resources, such as compute instances, block storage, networking resources, and load balancers. You must have access to an Oracle Cloud Infrastructure tenancy. To use the OKE service, you need to have access to an OCI tenancy. This means you must have a valid OCI account and the necessary permissions to create and manage resources within the tenancy. The following statements are not valid: OKE cannot use existing network resources for the creation of a new cluster. OKE creates new network resources specifically for the cluster, and it does not support using existing network resources. There is a limit of three clusters within each region, but there is no limit on the number of nodes and pods you can create within each cluster. This statement is incorrect. There is no specific limit on the number of clusters you can create within a region in OKE. However, there may be certain limits or quotas on resources that can impact the number of clusters you can create.

Explanation

The testing strategy that achieves high velocity of deployments and releases of cloud native applications is "Automated testing." Automated testing involves the use of automated tools and frameworks to execute tests, validate functionality, and detect issues or bugs in an application. By automating the testing process, developers and DevOps teams can rapidly test and validate code changes, ensuring that new features and updates are functioning correctly before being deployed to production. This approach helps increase the speed and efficiency of the testing process, allowing for faster and more frequent deployments of cloud native applications.

Explanation

The necessary configuration to provide access to a private repository in OCI Registry (OCIR) from OCI Container Engine for Kubernetes (OKE) is to create a docker-registry secret for OCIR with an identity Auth Token on the cluster and specify the imagePullSecret property in the application deployment manifest. Here's the breakdown of the steps: Create a docker-registry secret for OCIR with an identity Auth Token: In order to authenticate with the private repository in OCIR, you need to create a secret in your OKE cluster that contains the necessary credentials. This can be done by generating an identity Auth Token from the OCI Console and creating a secret in the cluster using the kubectl command. Specify the imagePullSecret property in the application deployment manifest: In your application's deployment manifest (such as a Kubernetes Deployment or StatefulSet YAML file), you need to include the imagePullSecret property and specify the name of the secret you created in the previous step. This allows the OKE cluster to use the credentials from the secret to pull the docker image from the private repository in OCIR during deployment. By following these steps, you can ensure that your OKE cluster has the necessary access to the private repository in OCIR, and your application can successfully pull the required docker image during deployment.

Explanation

The use case that is NOT a valid use case for leveraging the Oracle Cloud Infrastructure (OCI) Events service is "Capturing the OCI Monitoring service alarms and invoking autoscaling of compute instances." The OCI Events service is designed to provide event-driven architecture and enable automated responses to events occurring within the Oracle Cloud Infrastructure. It allows you to react to changes and activities happening within your OCI resources. The Events service can be used to trigger actions based on events like file uploads, resource changes, or task completions. However, capturing the OCI Monitoring service alarms and invoking autoscaling of compute instances is not a direct functionality provided by the OCI Events service. Autoscaling based on monitoring metrics is typically handled by the OCI Autoscaling service, which is specifically designed for that purpose. The OCI Monitoring service provides monitoring and alerting capabilities, while the Autoscaling service handles the dynamic scaling of compute instances based on predefined policies and thresholds.

Explanation

The correct answers are: Amount of RAM used by a function: Oracle Functions collects and reports the amount of memory (RAM) used by a function during its execution. This metric helps in monitoring and optimizing the resource consumption of functions. Length of time a function runs: Oracle Functions captures and provides the duration of function executions. This metric allows you to track the performance and responsiveness of your functions and identify any potential bottlenecks or delays. These metrics provide valuable insights into the resource utilization and performance of your functions, enabling you to monitor and optimize their behavior in the Oracle Cloud Infrastructure (OCI) environment.

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.

Explanation

The statement that accurately describes the Oracle Cloud Infrastructure (OCI) Load Balancer integration with OCI Container Engine for Kubernetes (OKE) is: "OKE service provisions an OCI Load Balancer instance for each Kubernetes service with LoadBalancer type in the YAML configuration." When you define a Kubernetes service in your YAML configuration with the LoadBalancer type, the OKE service automatically provisions an OCI Load Balancer instance specifically for that service. This Load Balancer instance is dedicated to the Kubernetes service and provides traffic balancing functionality. Each Kubernetes service that requires load balancing will have its own OCI Load Balancer instance provisioned by OKE.

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.

Explanation

The correct answer is: "Robust Deployment." When using test cases that simultaneously validate a deployment and perform a selected set of functional tasks, the testing measure that should be considered is "Robust Deployment." Robust Deployment refers to the ability of an application or system to be deployed reliably and consistently, without errors or failures. It involves ensuring that the deployment process is well-defined, automated, and able to handle different scenarios and configurations. When conducting testing that combines the validation of deployment and functional tasks, it is crucial to ensure that the deployment itself is robust. This means verifying that the application or system can be successfully deployed and configured without encountering deployment-related issues such as incorrect configurations, missing dependencies, or compatibility problems. By considering "Robust Deployment" as a testing measure, you can evaluate the reliability and effectiveness of the deployment process, ensuring that the application or system is deployed correctly and ready to perform the selected set of functional tasks.

Explanation

The correct answer is: Microservices are used for long running operations while serverless functions are used for short running operations. One of the key differences between microservices and serverless functions is the duration of their execution. Microservices are typically designed to handle long-running operations and may continuously run and process requests as part of a larger system. They are often deployed and managed as long-lived services. On the other hand, serverless functions are designed to handle short-lived operations or tasks that execute in response to specific events or triggers. They are event-driven and execute only when invoked, providing a lightweight and ephemeral computing model. Serverless functions are often used for executing small, isolated pieces of code without the need for managing infrastructure or scaling concerns. While both microservices and serverless functions can be stateless or stateful depending on the specific implementation, the key distinction lies in the typical duration and execution pattern of these components within an application architecture.

Explanation

The correct value for the "type" field in the API deployment specification is "STOCK_RESPONSE_BACKEND". By setting the "type" to "STOCK_RESPONSE_BACKEND", you are indicating that the backend for the specified route should return a pre-defined response. This type of backend is commonly used when you want a specific response to be returned consistently, regardless of the actual backend service implementation. In this case, the API deployment specification is configured to have a single route with the path "/hello" and the method "GET". The backend section specifies the type as "STOCK_RESPONSE_BACKEND". Additionally, it defines the response status code as 200, sets the "Content-Type" header to "application/json", and provides the JSON content in the "body" field. Using this configuration, any request to the "/hello" path with the "GET" method will always receive a consistent JSON response with the content "{"myjson": "consistent response"}".

To push a new Docker container image to a repository in OCI Registry, you need to use an Auth Token to complete the authentication via the Docker CLI1. An Auth Token is a secure, auto-generated password that you can use to authenticate with OCI services such as OCI Registry1. You can generate an Auth Token in the Console by following these steps1:

In the top-right corner of the Console, open the Profile menu and then click User settings to view the details.

On the Auth Tokens page, click Generate Token.

Enter a friendly description for the auth token. Avoid entering confidential information.

Click Generate Token. The new auth token is displayed.

Copy the auth token immediately to a secure location from where you can retrieve it later, because you won’t see the auth token again in the Console.

Close the Generate Token dialog. After generating an Auth Token, you need to log in to OCI Registry by entering docker login .ocir.io in a terminal window on the client machine running Docker, where corresponds to the key for the OCI Registry region you’re using1. When prompted for a username, enter your username in the format /, where is the auto-generated Object Storage namespace string of your tenancy1. When prompted for a password, enter the Auth Token you copied earlier1.

A rolling update is a deployment strategy that gradually replaces the old version of an application with the new version without any downtime4. OKE supports rolling updates by using the kubectl rollout command4. A rolling update allows you to roll back to the previous version if something goes wrong with the new version4. Therefore, using a rolling update strategy with kubectl ensures that you can roll back to the previous version of your Python application if the new image does not work once deployed. Verified References: Deploy Oracle Container Engine for Kubernetes

Explanation

The correct approach to receive an email each time a Terraform action begins in Oracle Cloud Infrastructure (OCI) Resource Manager without writing any code is as follows: Create an OCI Notification topic and email subscription with the destination email address. This will define the email delivery configuration. Create an OCI Events rule that matches the "Resource Manager Job - Create" condition. This rule will be triggered when a Resource Manager job is created. In the OCI Events rule, select the notification topic that was created in step 1 as the action for the corresponding event. This will ensure that the notification is sent to the specified email address. By following these steps, you can configure the OCI Events service to send an email notification whenever a Resource Manager job is created in OCI Resource Manager.

Explanation

Oracle Functions does not currently support PL/SQL as a language for writing function code. PL/SQL is a procedural language used in Oracle Database for developing stored procedures, triggers, and other database-related code. However, Oracle Functions supports several other popular programming languages such as Go, Node.js, Python, and Java, allowing developers to choose the language that best suits their application requirements and their familiarity with the language. While PL/SQL is powerful for working with the Oracle Database, it is not an option for writing function code in the Oracle Functions serverless architecture.

An action is a response that you define for the rule to perform when the filter finds a matching event1. The action type specifies the service that you want to invoke by delivering the event message1. The following action types are available in OCI Events rule definition1:

Streaming: Send to a stream from Oracle Streaming Service.

Notifications: Send to an Oracle Notification Service topic.

Functions: Send to an Oracle Functions Service endpoint. Email is not a valid action type for OCI Events rule definition. To send an email as an action, you need to use the Notifications service and subscribe to a topic with an email protocol2.

Explanation

The option that is NOT available when viewing the Application metrics in the Oracle Cloud Infrastructure (OCI) Console is: "The number of retries made by the function before failing due to an error." When viewing the Application metrics in the OCI Console for Oracle Functions, you can typically see metrics related to the performance and usage of your functions. These metrics provide insights into how your functions are performing and being utilized. The following metrics are usually available: The number of requests to invoke a function that failed due to throttling: This metric indicates the number of requests that were not processed by the function due to reaching the configured concurrency limit or throttling settings. The length of time a function runs for: This metric represents the duration of each function invocation, measuring the time it takes for the function to complete its execution. The number of requests to invoke a function that failed with an error response: This metric counts the number of requests that encountered an error during the function invocation, resulting in a failed response. However, the number of retries made by the function before failing due to an error is not typically available as part of the Application metrics in the OCI Console. The retries made by the function are usually handled at the invoker level, and the specific details of retries may not be captured as part of the application-level metrics. It's important to note that the availability of metrics and their specific details may vary depending on the version and configuration of Oracle Functions and the monitoring setup. It is recommended to refer to the Oracle Functions documentation and consult the official documentation for accurate and up-to-date information on available metrics.

Explanation

The correct answer is: fn deploy --app travel-app --all Explanation: To build and deploy multiple Oracle Functions as part of a single application named "travel-app," you can use the fn deploy command with the appropriate options. The command fn deploy --app travel-app --all is the correct syntax. Here's what each part of the command does: fn deploy: This command is used to deploy functions and applications in Oracle Functions. --app travel-app: This option specifies the application name as "travel-app," indicating that you want to deploy functions to this application. --all: This option indicates that you want to deploy all the functions within the application. By using fn deploy --app travel-app --all, you can build and deploy all the functions in your travel application across different programming languages (Java, Python, and Node.js) to the "travel-app" application in Oracle Functions.