1z0-1084-24 Oracle Cloud Infrastructure 2024 Developer Professional Questions and Answers

Explanation

Oracle Cloud Infrastructure (OCI) API Gateway supports various backend-types to handle incoming requests and route them to the appropriate backend service. However, "ORACLE_STREAMS_BACKEND" is not a valid backend-type in OCI API Gateway. "STOCK_RESPONSE_BACKEND" is a valid backend-type that allows you to configure static responses directly in the API Gateway without routing requests to any specific backend service. This can be useful for handling simple requests or returning predefined responses. "HTTP BACKEND" is another valid backend-type that enables routing requests to an HTTP backend service. "ORACLE_FUNCTIONS_BACKEND" is a valid backend-type that allows you to route requests to Oracle Functions, which are serverless functions that can be used to execute specific logic or operations. However, "ORACLE_STREAMS_BACKEND" is not a valid backend-type in OCI API Gateway. The API Gateway does not have native support for Oracle Streams as a backend service. Oracle Streams is a feature of Oracle Database that provides a publish-subscribe mechanism for data replication and distribution within an Oracle Database environment. It is not directly integrated as a backend service in OCI API Gateway.

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.

OCI Queue is a fully managed serverless service that helps decouple systems and enable asynchronous operations2. Queue handles high-volume transactional data that requires independently processed messages without loss or duplication2. A valid use case for OCI Queue is building decoupled and scalable systems, such as event-driven architectures or microservices-based applications2. For example, you can use Queue to decouple your application and build an event-driven architecture. Decoupling ensures that individual application components can scale independently and that you can future-proof your design so that as new application components are built, they can publish or subscribe to the queue2.

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

OCI API Gateway supports the following authentication methods for accessing an API deployment3:

HTTP Basic: The client sends a username and password with each request. The credentials are validated against a user database in Oracle Identity Cloud Service (IDCS).

API Key: The client sends an API key with each request. The API key is validated against a list of keys stored in IDCS or OCI Vault.

OAuth: The client obtains an access token from an authorization server (such as IDCS) and sends it with each request. The access token is validated against the authorization server and optionally checked for required scopes.

JWT Token: The client obtains a JSON Web Token (JWT) from an identity provider (such as IDCS or OCI IAM) and sends it with each request. The JWT is validated against the identity provider’s public key and optionally checked for required claims. SAML Token is not a valid authentication method for accessing an OCI API Gateway deployment. SAML is an XML-based standard for exchanging authentication and authorization data between different parties, such as a service provider and an identity provider4. SAML tokens are typically used for web browser single sign-on (SSO) scenarios, not for API access4.

A pod is the smallest and simplest unit in the Kubernetes object model that you create or deploy2. A pod represents a single instance of a running process in your cluster. Pods contain one or more containers, such as Docker containers. When you create a pod, you define how much CPU and memory (RAM) each container needs. A pod can also include storage volumes, IP addresses, options that govern how the container(s) should run, and more2. Pods are the basic building blocks of larger Kubernetes constructs such as deployments, replica sets, and services2.

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.

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 utilizes 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 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.\

 Cloud native is the software approach of building, deploying, and managing modern applications in cloud computing environments3. Cloud native apps are designed and built to exploit the scale, elasticity, resiliency, and flexibility the cloud provides4. Cloud native technologies support fast and frequent changes to applications without impacting service delivery, providing adopters with an innovative, competitive advantage3. Therefore, cloud native refers to the design and deployment of applications that are optimized for cloud infrastructure. Verified References: What is Cloud Native? - Everything you need to know, What is Cloud Native? | Microsoft Learn

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.

Explanation

The correct answer is: "Tightly coupled." Tightly coupling is not a criterion that is usually met by a microservice. In fact, microservices are designed to be loosely coupled. Loosely coupling refers to reducing dependencies and minimizing the direct interactions between different components or services. Microservices promote independence and autonomy, allowing each service to operate independently without being tightly bound to other services. The other options listed are criteria that are typically met by microservices: Organized around business capabilities: Microservices architecture suggests designing services around specific business capabilities or functionalities. This allows for focused and specialized services that align with the organization's business needs. Independently deployable: Microservices are designed to be independently deployable units. Each microservice can be developed, tested, and deployed separately, without impacting other services. This enables agility and scalability in the deployment process. Highly maintainable: Microservices are often designed to be highly maintainable. They are smaller in scope and focused on specific tasks, making it easier to manage and maintain individual services. Additionally, microservices can be updated, patched, or replaced without affecting the entire system, facilitating easier maintenance and evolution of the application. Therefore, the criterion that is NOT typically met by a microservice is being tightly coupled.

Explanation

The correct answer is: Controlling access to the backend OCI resources. OCI API Gateway does not provide direct control over access to backend OCI resources. It primarily focuses on managing and securing access to APIs exposed through the gateway. The gateway acts as a front-end for APIs and provides features such as authentication, authorization, rate limiting, and CORS support. While you can configure authentication and authorization policies, limit the number of requests, and enable CORS support in OCI API Gateway, it does not directly control access to backend OCI resources. Access to backend resources is typically managed through other means, such as IAM policies, network security rules, or resource-specific access controls.

Explanation

The appropriate logging approach for services running in Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE) is: "All services log to standard output only." When running services in a containerized environment like OKE, it is recommended to follow the Twelve-Factor App methodology, which suggests treating logs as event streams. According to this methodology, services should write their log events to standard output (stdout) instead of writing to log files. By logging to standard output, the container runtime (such as Kubernetes) can collect and aggregate the logs generated by the services. These logs can then be accessed and managed through the container runtime's logging infrastructure. Logging to standard output offers several advantages in a containerized environment: Simplicity and consistency: Standardizing on logging to stdout ensures a consistent approach across different services, making it easier to manage and analyze logs. Log aggregation: The container runtime can collect the logs from all the running containers and provide centralized log management, allowing you to access and search logs from different services in one place. Scalability: Since logs are written to stdout, they can be easily handled by the container runtime's log management system, which can scale to handle large volumes of log data. Separation of concerns: By logging to stdout, the responsibility of managing log files and their rotation is shifted to the container runtime, allowing the services to focus on their core functionality. While it is possible to log to log files or external logging systems, the recommended approach in a containerized environment like OKE is to log to standard output and leverage the logging infrastructure provided by the container runtime.

Explanation

The correct answer is: Invoke from the Docker CLI. Explanation: Executing a function deployed in Oracle Functions is typically done using the following options: Invoke from the Fn Project CLI: The Fn Project CLI provides a command-line interface specifically designed for interacting with Oracle Functions. You can use commands like fn invoke to invoke a function. Trigger by an event in the Oracle Cloud Infrastructure (OCI) Events service: You can configure events in OCI to trigger your function based on various criteria, such as object storage events, resource state changes, or scheduled events. Invoke from the OCI CLI: The OCI CLI (Command Line Interface) allows you to interact with various services in Oracle Cloud Infrastructure, including Oracle Functions. You can use the fn invoke command to invoke a function. Send signed HTTP requests to the function's invoke endpoint: Oracle Functions provides an HTTP endpoint that can be used to invoke functions. You can send signed HTTP requests to this endpoint using tools or programming languages that support making HTTP requests. On the other hand, invoking a function deployed in Oracle Functions using the Docker CLI is not a valid option. The Docker CLI is primarily used for managing Docker containers and images, and it does not provide a direct mechanism for invoking functions in Oracle Functions.

Explanation

A valid concern that needs to be further investigated in this scenario is whether the OKE cluster has a secret with the credentials of the Oracle Cloud Infrastructure Registry (OCIR) repository and if that secret is being used in the Kubernetes deployment manifest. Here's why this concern is relevant: Access to the OCIR repository: In order for the OKE cluster to pull images from the OCIR repository, it needs proper authentication credentials. These credentials are typically provided in the form of a secret, which contains the necessary information to authenticate with the registry. Secret in the deployment manifest: The Kubernetes deployment manifest defines how the application containers should be deployed. It includes specifications such as the container image, resource requirements, and environment variables. To pull images from a private repository like OCIR, the deployment manifest needs to reference the appropriate secret that contains the registry credentials. If the images are not being pulled from the designated OCIR repository, it suggests that either the secret with the OCIR credentials is missing or it is not properly referenced in the deployment manifest. Further investigation should focus on verifying the presence and correctness of the secret, as well as confirming that it is correctly referenced in the deployment manifest for the application containers. By ensuring the presence of the secret and proper configuration in the deployment manifest, the OKE cluster will have the necessary credentials to access the OCIR repository and successfully deploy the application containers.

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 best answer is: "Use the OCI Logging service and enable VCN flow logs." To meet the requirement of analyzing network communication between two services deployed in different Container Engine for Kubernetes (OKE) clusters within the same Virtual Cloud Network (VCN) in a cost-effective way, you can use the OCI Logging service and enable VCN flow logs. The VCN flow logs feature in OCI allows you to capture and log network traffic information for your VCN resources. By enabling VCN flow logs, you can monitor and analyze the network communication between your services without the need for additional third-party logging services or tools. Enabling VCN flow logs provides visibility into the network traffic, including source and destination IP addresses, ports, protocols, and other relevant details. This information can be collected and stored in the OCI Logging service, where you can analyze and gain insights into the network communication patterns between your services. By leveraging the built-in capabilities of the OCI Logging service and enabling VCN flow logs, you can fulfill the security team's requirement for network communication analysis in a cost-effective manner. This eliminates the need for deploying additional third-party logging services or tools, reducing complexity and potential costs associated with their setup and maintenance. The other options mentioned are not the most cost-effective or suitable solutions for analyzing network communication in this scenario: Deploying a third-party logging service and aggregating the network flow logs would introduce additional costs and complexity, which may not be necessary considering the built-in capabilities provided by OCI. Rewriting the application to send logs to an outside log aggregator would not directly address the requirement of analyzing network communication between the services. It would focus more on application-level logs rather than network-level analysis. Deploying Wireshark and intercepting packets would require additional infrastructure setup and maintenance, which may not be the most cost-effective approach for network analysis in this scenario.

Explanation

The correct answer is: "Adding a custom certificate authority (CA) or custom CA bundle to your gateway's trust store for mTLS is optional unless you need to reject certificates that do not contain particular values (such as a domain name)." The statement that is NOT valid regarding the mTLS options in OCI API Gateway is: "Adding a custom certificate authority (CA) or custom CA bundle to your gateway's trust store for mTLS is optional unless you need to reject certificates that do not contain particular values (such as a domain name)." In OCI API Gateway, adding a custom certificate authority (CA) or custom CA bundle to the gateway's trust store is not optional. It is a necessary step when configuring mTLS authentication. The trust store in the gateway is used to validate the client certificates presented during mTLS authentication. The other options listed are valid regarding the mTLS options in OCI API Gateway: Once the mTLS request policy is enabled, all requests with valid certificates are routed to the backend unless specific values (such as a domain name) are defined. This means that only requests with valid client certificates will be allowed to access the backend microservices. The mTLS request policy can only be enabled at the API deployment specification level, and it applies globally to all routes in that deployment. This ensures consistent mTLS authentication across all routes and endpoints in the API deployment. Custom CA or custom CA bundles can be added to the gateway's trust store, but only if they already exist in the OCI Certificates service. This allows you to include trusted CAs or CA bundles to validate client certificates during mTLS authentication.

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.

To prevent images from being deleted from a repository, you can set the global policy of image retention to “Retain All Images”. This policy applies to all repositories in the tenancy and overrides any individual repository settings. You can also lock the policy to prevent any changes to it. Verified References: Using Retention Rules to Preserve Data

Explanation

The two characteristics of microservices are: Microservices can be independently deployed: One of the key principles of microservices architecture is the ability to independently deploy each microservice. This means that changes or updates to one microservice can be made and deployed without affecting other microservices. It allows for faster and more frequent deployments, enabling agile development and scalability. Microservices communicate over lightweight APIs: Microservices communicate with each other through lightweight APIs (Application Programming Interfaces). This enables loose coupling between microservices, as they can interact with each other using standard protocols like HTTP/REST or messaging systems like RabbitMQ or Kafka. Lightweight APIs facilitate flexibility and interoperability between microservices, making it easier to develop and maintain complex systems. The remaining statement, "All microservices share a data store," is not a characteristic of microservices. Microservices are designed to be autonomous and have their own data storage or database. Each microservice has its own data store, which promotes the principle of bounded contexts and avoids tight coupling between services. This allows for better scalability and independence of data management within each microservice.

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

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.

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 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"}".