1z0-1084-23 Questions and Answers

Explanation

The correct answer is: "Multiple microservices can run in one process." The statement that is FALSE about microservices is: "Multiple microservices can run in one process." Microservices are designed to be independent and autonomous services that can be deployed, scaled, and managed separately. Each microservice typically runs as its own separate process. This separation allows for loose coupling and independent scalability of individual services. Running multiple microservices in a single process would violate the fundamental principle of microservices architecture, which emphasizes the isolation and independence of services. Combining multiple microservices into a single process would tightly couple them, making it difficult to independently manage, scale, and update each service. The other statements provided are true about microservices: It is fairly common for microservices to communicate with HTTP: Microservices often communicate with each other using lightweight protocols like HTTP/REST. This allows for interoperability, flexibility, and ease of communication between microservices. Microservices are typically designed around business capabilities: Microservices architecture advocates designing services based on specific business capabilities or functionalities. Each microservice focuses on a specific business domain or task, enabling modular and scalable development. They are independently deployable: Microservices are designed to be independently deployable units. This means that each microservice can be developed, tested, deployed, and updated separately without affecting other services. This flexibility allows for faster development cycles and more efficient scalability.

Explanation

The correct options are: A configured OCI API signing key pair: The API signing key pair is used for authentication and authorization to access OCI resources, including the OKE cluster. The private key should be configured on your local machine to authenticate API requests. An SSH key pair with the public key added to the cluster worker nodes: This is required for secure SSH access to the worker nodes in the OKE cluster. You need to generate an SSH key pair and add the public key to the cluster's worker node pool during cluster creation or update. Therefore, the correct options are having a configured OCI API signing key pair and an SSH key pair with the public key added to the cluster worker nodes.

Explanation

The option that will get you more information on the error when invoking Oracle Functions from your Cloud Shell session is: "DEBUG=1 fn invoke myapp myfunction". Setting the environment variable DEBUG=1 before invoking the function using the fn command allows you to enable debug mode, which provides more detailed information about the execution of the function. This can be useful for troubleshooting and understanding the root cause of the error. By using the command "DEBUG=1 fn invoke myapp myfunction", the function invocation will be executed with debug mode enabled, and additional debug information will be displayed in the console output. This information can include stack traces, detailed error messages, and other relevant details that can help identify and resolve the issue. Using the verbose option (--verbose) or debug option (--debug) with the fn command may also provide additional information, but the specific behavior may depend on the version and configuration of the fn CLI tool. While contacting Oracle support with the error message is always an option, enabling debug mode using the DEBUG=1 environment variable provides immediate access to more detailed information and can help in diagnosing and resolving the error more efficiently.

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.

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.

Explanation

The correct command to rebuild the API docker image and tag it as OCIdevops/api:latest is: docker build -t OCIdevops/api:latest The docker build command is used to build a Docker image from a Dockerfile. The -t flag is used to specify the name and optionally a tag for the image. In this case, the name of the image is OCIdevops/api and the tag is latest. By running this command, the Docker image will be recreated based on the instructions in the Dockerfile and tagged with the specified name and tag.

Explanation

The correct answer is: "A unique OCID is automatically generated for each secret and remains unchanged even when creating a new secret version." The statement that is NOT valid about managing secrets in the OCI Vault service is: "A unique OCID is automatically generated for each secret and remains unchanged even when creating a new secret version." In OCI Vault, a secret is identified by its OCID (Oracle Cloud Identifier), which is a unique identifier for each resource inOracle Cloud Infrastructure. However, when a new secret version is created for an existing secret, the OCID remains the same for the secret itself, but a new OCID is generated for the secret version. This allows you to track and manage different versions of a secret while maintaining a consistent OCID for the secret itself. The other statements mentioned are valid: You can manually create new secrets as well as new secret versions using the OCI Console. This means you have control over creating and managing secrets within the Vault service. A secret reuse rule prevents the use of secret contents across different versions of a secret. This ensures that each secret version maintains its own unique set of contents and avoids accidental reuse or sharing of secrets across versions. By default, new secret versions automatically expire in 90 days unless you configure an expiry rule. This helps enforce good security practices by automatically rotating secrets periodically, reducing the risk of unauthorized access in case of compromise. Therefore, the statement that is NOT valid is the one regarding the uniqueness and consistency of the OCID when creating new secret versions.

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.

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

The user is responsible for patching, upgrading, and maintaining the worker nodes in Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE). In OKE, the user has control over the worker nodes, which are the compute instances that run the Kubernetes worker components. As the user, you are responsible for managing and maintaining these worker nodes, including tasks such as patching the underlying operating system, upgrading Kubernetes versions, and performing any necessary maintenance activities. While Oracle provides the underlying infrastructure and support services, including managing the control plane and ensuring the availability of the OKE service, the responsibility for managing the worker nodes lies with the user. This allows you to have control and flexibility in managing your Kubernetes environment according to your specific needs and requirements.

Explanation

The correct answer is: In blue/green deployment, both old and new applications are in production at the same time. In canary deployment, the application is deployed incrementally to a select group of people. In a blue/green deployment strategy, two identical environments, referred to as blue and green, are set up. The current production environment (blue) continues to serve live traffic while a new version of the application is deployed in the green environment. Once the new version is tested and deemed stable, traffic is routed from the blue environment to the green environment, making it the new production environment. This approach allows for a seamless switch between the old and new versions of the application. On the other hand, in a canary deployment strategy, the new version of the application is deployed incrementally to a small subset of users or a specific group. This allows for testing the new version in a real production environment while minimizing the impact of any potential issues. If the new version performs well and meets the desired criteria, it can be gradually rolled out to a larger audience or the entire user base. In summary, the main difference between blue/green and canary deployment strategies lies in how the deployment is managed. Blue/green involves simultaneous production of both old and new applications, while canary deployment focuses on incremental deployment to a select group of users.

Explanation

The correct answer is: "Resiliency is about recovering from failures without downtime or data loss." Service resiliency, in the context of cloud-native applications, is the ability of a service or system to recover from failures and continue functioning without downtime or data loss. It involves designing and implementing mechanisms to handle failures, such as network outages, hardware failures, or software errors, in a way that minimizes the impact on the overall system. The goal of resiliency isto ensure that the application or service can continue to operate and provide a certain level of functionality, even in the face of failures. This typically involves techniques such as redundancy, fault tolerance, and graceful degradation. By implementing resiliency measures, a cloud-native application can recover and adapt to failures, maintain availability, and preserve data integrity. The other statements are not accurate regarding service resiliency: Resiliency is not about not bringing a service to a functioning state after a failure. Instead, it is about recovering from failures and ensuring continued functionality. Resiliency is not about avoiding failures entirely. While it is desirable to prevent failures, resiliency focuses on the ability to handle and recover from failures when they do occur. Resiliency testing is not limited to a test environment. It is important to test and validate the resiliency measures in both test environments and production environments to ensure the application can effectively handle failures in real-world scenarios.

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, setsthe "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"}".

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 thatthe 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 statements are: A common context to store configuration variables that are available to all functions in the application. A Docker image containing all the functions that share the same configuration. A logical group of functions.Explanation: An Oracle Functions application provides a common context for functions within the application. It allows you to store configuration variables that are accessible by all the functions in the application. Functions within the same application can share the same Docker image, which contains the common configuration and dependencies. An Oracle Functions application serves as a logical group that organizes related functions. Functions within the same application can be managed collectively, and they can interact and share resources within the application context.

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

To obtain a log file from one of the nodes in an Oracle Cloud Infrastructure (OCI) Container Enginefor Kubernetes (OKE) cluster, you should SSH into the nodes using the private key. Here's the step-by-step process: Obtain the private key: The private key is required to authenticate and access the nodes in the OKE cluster. You should obtain the private key from your administrator or the appropriate key pair used to create the cluster. SSH into the node: Use a secure shell (SSH) client, such as OpenSSH, to connect to the desired node in the cluster. The SSH command typically includes the private key file path and the public IP address or hostname of the node. Example command: ssh -i opc@ Replace with the path to the private key file and with the public IP address of the node you want to access. Navigate to the log file location: Once you have successfully connected to the node, navigate to the directory where the log file is located. The exact location and name of the log file may vary depending on the Kubernetes distribution and configuration. Copy or view the log file: You can either copy the log file from the node to your local machine using the scp command or view the contents directly on the node using tools like cat or less. By following these steps, you will be able to access the log file from the desired node in the OKE cluster for troubleshooting purposes.

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 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 correct answer in this scenario is to use the OCI API Gateway service and configure rate limiting. Using the OCI API Gateway service and configuring rate limiting is an effective approach to address Distributed Denial-of-Service (DDoS) attacks. By implementing rate limiting, you can control the number of requests that can be made to your web service within a specific time frame. This helps to prevent overload and ensures that your service can handle legitimate traffic while mitigating the impact of DDoS attacks. By leveraging the OCI API Gateway service, you can easily configure rate limiting rules to restrict the number of requests per second or per minute. This allows you to set appropriate thresholds and safeguard your web service from being overwhelmed by excessive requests. The API Gateway acts as a protective layer, filtering out malicious traffic and ensuring the smooth operation of your service. While options like OCI Virtual Cloud Network (VCN) segregation and third-party service integrations may contribute to overall security, they do not specifically address DDoS attacks as efficiently as rate limiting. VCN segregation focuses more on network segmentation and isolation, while third-party service integration may introduce additional dependencies and complexities. Re-writing your web service and implementing rate limiting is a viable option, but it may not be feasible considering the time constraints mentioned. Leveraging the OCI API Gateway service provides a quicker and easier solution to implement DDoS attack mitigation through rate limiting.

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.

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

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 orinfrastructure. 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.