Oracle 1z0-1084-24 Oracle Cloud Infrastructure 2024 Developer Professional Exam Practice Test

Explanation

Which TWO statements are correct regarding Docker images and containers? (Choose two.) Writing and building a new Dockerfile is the only way you can create new Docker images. A container can exist without an image but an image cannot exist without a container. Only one container can be spawned from a given image at a time. If multiple containers are spawned from the same image, then they all use the same copy of that image in memory. (Correct) An image is a collection of immutable layers whereas a container is a running instance of an image. (Correct) ChatGPT The correct statements regarding Docker images and containers are: If multiple containers are spawned from the same image, then they all use the same copy of that image in memory. This statement is correct. When multiple containers are created from the same Docker image, they share the underlying layers of the image in memory. Each container has its own isolated filesystem and runtime environment, but they all use the same base image, which helps in efficient resource utilization. An image is a collection of immutable layers whereas a container is a running instance of an image. This statement is also correct. Docker images are composed of multiple layers, with each layer representing a specific change or addition to the previous layer. These layers are read-only and can be shared among multiple containers. On the other hand, a container is a lightweight and isolated runtime instance created from a specific image. It is a running process that has its own filesystem, network, and runtime configuration. The statements "Writing and building a new Dockerfile is the only way you can create new Docker images" and "A container can exist without an image but an image cannot exist without a container" are incorrect. Docker images can be created in various ways, including using Dockerfiles, importing from existing images, or pulling from registries. Additionally, a container requires an image to run, so an image must exist before a container can be created from it.

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 correct answer is: Test using an API mock of service B. To test service A without deploying all of its dependencies, including service B, you can use an API mock of service B. An API mock is a simulated version of the API that mimics the behavior of the actual service. By using an API mock, you can isolate the testing of service A and simulate the responses and behavior of service B's APIs. With an API mock, you can define the expected responses and behavior of service B's APIs, allowing you to test the integration between service A and the mocked version of service B. This approach enables you to verify the functionality of service A without relying on the availability or changes in the actual service B. By decoupling the dependencies and using an API mock, you can perform independent testing of service A, ensuring its functionality in isolation.

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.

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.

Fn Project is the open source engine that is used by OCI to power Oracle Functions1. Fn Project is an open source, container native, serverless platform that can be run anywhere - any cloud or on-premises1. Fn Project is easy to use, extensible, and performant. You can download and install the open source distribution of Fn Project, develop and test a function locally, and then use the same tooling to deploy that function to Oracle Functions1. Verified References: Overview of Functions

Explanation

The statement that is incorrect is: "The request does not require an Authorization header." In order to POST messages to a stream in the OCI Streaming service using OCI APIs, the request does require an Authorization header. The Authorization header is used to provide authentication and ensure the request is authorized to access the stream. The correct approach is to include the Authorization header in the request, along with other required headers such as x-content-sha256, content-type, and content-length. Therefore, the incorrect statement is that the request does not require an Authorization header.\

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.

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.

API mocking is a technique that simulates the behavior of real APIs without requiring the actual implementation or deployment of the dependent services1. API mocking allows you to test changes to service A without deploying all of its dependencies, such as service B, by creating mock responses for the APIs that service A relies on1. API mocking has several benefits, such as1:

Faster testing: You can test your service A without waiting for service B to be ready or available, which reduces the testing time and feedback loop.

Isolated testing: You can test your service A in isolation from service B, which eliminates the possibility of external factors affecting the test results or causing errors.

Controlled testing: You can test your service A with different scenarios and edge cases by creating mock responses that mimic various situations, such as success, failure, timeout, etc.

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.

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.

In the shared responsibility model, Oracle is responsible for securing the underlying cloud infrastructure and platform services, while customers are responsible for securing their data and applications within the cloud4. For provisioned OKE clusters, Oracle manages the control plane (master nodes) of the Kubernetes cluster, while customers manage the data plane (worker nodes) of the cluster5. Therefore, it is the responsibility of the customer to perform patching, upgrading, and maintaining of the worker nodes in provisioned OKE clusters5. Customers can use tools such as Terraform or kubectl to automate these tasks5.

Explanation

The correct answers are: Set up the following dynamic group for your function's OCID: Name: read-file-dg Rule: resource.id = "ocid1.fnfunc.oc1.phx.aaaaaaaakeaobctakezjz5i4ujj7g25q7sx5mvr55pms6f4da" Set up a policy with the following statement to grant read access to the bucket: Statement: allow dynamic-group read-file-dg to read objects in compartment qa-compartment where target.bucket.name = 'input-bucket' Explanation: To implement the use case of reading a JSON file object from an Object Storage bucket using Resource Principals with Oracle Functions, you need to configure the following: Create a dynamic group named "read-file-dg" and associate it with your function's OCID. This dynamic group helps identify the function as a member of the group for policy enforcement. Create a policy that grants read access to the bucket. The policy statement should allow the dynamic group "read-file-dg" to read objects in the compartment "qa-compartment" and specify the target bucket name as "input-bucket". This policy ensures that the function has the necessary permissions to access the specified bucket. By setting up the dynamic group and policy, you ensure that the function, as a member of the dynamic group, has the required read access to the specified Object Storage bucket in the specified compartment.

Explanation

The two "Action Type" options that are NOT available in an Oracle Cloud Infrastructure (OCI) Events rule definition are: Email (Correct) Slack (Correct) The available "Action Type" options in OCI Events rule definition include Functions, Notifications, and Streaming. However, email and Slack are not directly supported as action types in OCI Events. Instead, you can use Notifications to send notifications to various notification channels, including email and Slack, through the OCI Notifications service.

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

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.

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 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 three OCI services that can be leveraged to securely store and version your application's source code, and automate the building, testing, and deployment of applications to the OCI platform are: DevOps: OCI provides a comprehensive set of DevOps services, including Oracle Developer Cloud Service, which allows you to manage source code repositories, automate builds and testing, and streamline the deployment process. Container Engine for Kubernetes: OCI's Container Engine for Kubernetes (OKE) enables you to deploy and manage containerized applications using Kubernetes. It provides a scalable and reliable platform for automating the deployment of your applications. Oracle Cloud Infrastructure Registry: OCI Registry is a fully managed, private container registry that allows you to securely store and manage Docker images. It integrates with other OCI services, such as Container Engine for Kubernetes, to facilitate seamless deployment and orchestration of containerized applications. These services combined provide the necessary tools and infrastructure to support continuous integration and continuous deployment (CI/CD) workflows, enabling efficient and automated application development and deployment processes in the Oracle Cloud Infrastructure environment.

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.

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 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.

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

Explanation

The valid OKE cluster network configuration that meets the requirement of having the least attack surface while still allowing direct access to the deployed applications from the Internet is: Private subnets for nodes and the Kubernetes API endpoint; public subnets for load balancers. By placing the nodes and the Kubernetes API endpoint in private subnets, they are not directly accessible from the Internet, reducing the attack surface. The load balancers, on the other hand, are placed in public subnets, allowing them to be accessed from the Internet and serve as the entry point for accessing the deployed applications. This configuration ensures that the critical components of the cluster, such as the nodes and the API endpoint, are protected within the private network, while still providing accessibility to the applications through the load balancers. It helps to enhance security by limiting direct access to the internal components of the cluster while maintaining the availability of the deployed applications.

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 References: Overview of Queue

Explanation

(OPT) iad.ocir.io/myproject/heyoci/myapp:latest The three valid tags for an image named myapp in the heyoci namespace of the Oracle Cloud Infrastructure Registry (OCIR) in the us-ashburn-1 (iad) region are: iad.ccir.io/heyoci/myapp:latest This tag specifies the latest version of the myapp image in the heyoci namespace in the iad region. iad.ocir.io/heyoci/myapp:0.0.2-beta This tag specifies version 0.0.2-beta of the myapp image in the heyoci namespace in the iad region. us-ashburn-1.ocir.io/heyoci/myapp:0.0.2-beta This tag specifies version 0.0.2-beta of the myapp image in the heyoci namespace in the us-ashburn-1 region. The other options mentioned are not valid tags for the given scenario: us-ashburn-1.ocir.io/heyoci/myapp:0.0.2-beta (incorrect format, missing the namespace) iad.ocir.io/myproject/heyoci/myapp:latest (incorrect format, incorrect order of namespace and project) us-ashburn-1.ocir.io/myproject/heyoci/myapp:latest (incorrect format, incorrect order of namespace and project) The correct format for tagging an image in OCIR is .ocir.io//:.

Explanation

To mandate image verification when deploying container images to Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE) clusters, you should enable image verification policies separately for each OKE cluster. This is enforced at the cluster level. Enabling image verification policies at the cluster level ensures that all container images deployed to the OKE cluster are automatically verified against the specified master encryption key (MEK). This helps maintain the security and integrity of the deployed microservices by ensuring that only signed and trusted container images are used. Enabling image verification policies at the cluster level allows for consistent and centralized enforcement of the verification process across all nodes and node pools within the cluster. It provides a standardized approach to image verification for the entire cluster, simplifying management and ensuring compliance with the organization's mandate. Enabling image verification policies separately for each node pool or at the pod level would introduce complexity and potential inconsistencies in the verification process. Therefore, enforcing image verification at the cluster level is the recommended approach.

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.