1z0-1084-25 Sample Questions Answers

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

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 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 correct syntax for implementing a rolling update deployment strategy in Kubernetes using the kubectl command is: kubectl rolling-update --image=image:v2 This command initiates a rolling update of the specified deployment by updating the container image to image:v2. The rolling update strategy ensures that the new version of the application is gradually deployed while maintaining availability and minimizing downtime.

Explanation

To obtain a log file from one of the nodes in an Oracle Cloud Infrastructure (OCI) Container Engine for 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 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 option that is not valid for connecting to an Autonomous Transaction Processing (ATP) Database from a container in Kubernetes is: Install the Oracle Cloud Infrastructure Service Broker on the Kubernetes cluster and deploy ServiceInstance and ServiceBinding resources for ATP. Then use the specified binding name as a volume in the application deployment manifest. The Oracle Cloud Infrastructure Service Broker is not used for connecting to an ATP Database from a container in Kubernetes. The Service Broker is used for provisioning and managing cloud services directly from Kubernetes. It allows you to create and manage instances of OCI services using Kubernetes resources like ServiceInstance and ServiceBinding. To connect to an ATP Database from a container in Kubernetes, you can use one of the following valid options: Enable Oracle REST Data Services for the required schemas and connect via HTTPS. This involves enabling and configuring Oracle REST Data Services (ORDS) for the schemas in the ATP Database. You can then connect to the ATP Database using RESTful endpoints provided by ORDS. Use Kubernetes secrets to configure environment variables on the container with ATP instance OCID and OCI API credentials. Then use the CreateConnection API endpoint from the service runtime. This approach involves configuring the necessary environment variables on the container to provide the ATP instance OCID and OCI API credentials. The application can then use the OCI SDK or REST API (such as the CreateConnection endpoint) to establish a connection to the ATP Database. Create a Kubernetes secret with contents from the instance Wallet files. Use this secret to create a volume mounted to the appropriate path in the application deployment manifest. This method involves creating a Kubernetes secret that contains the necessary credentials from the ATP Database's instance wallet files. The secret can then be mounted as a volume in the application deployment, allowing the application to access the required credentials for connecting to the ATP Database. Both options 1 and 3 provide valid approaches for connecting to an ATP Database from a container in Kubernetes, depending on the specific requirements and preferences of the application.

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.

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.

To pull a Docker image from OCI Registry to the client machine, you need to use the docker pull command with the following syntax1: docker pull .ocir.io//: where:

is the key for the OCI Registry region you’re using. For example, iad. See Availability by Region1.

ocir.io is the OCI Registry name.

is the auto-generated Object Storage namespace string of the tenancy that owns the repository from which you want to pull the image (as shown on the Tenancy Information page)1.

is the name of the repository that contains the image you want to pull.

is the tag of the image you want to pull.

Explanation

The valid troubleshooting strategy in this scenario is to enable function logging in the OCI console, add some print statements in your function code, and then view the logs to troubleshoot. Enabling function logging allows you to capture and store logs generated by your function during its execution. By adding print statements or log statements in your function code, you can output relevant information and debug messages to the logs. This helps you understand the execution flow, identify any errors or issues, and gather more information about the function's behavior. To troubleshoot the issue of the Python function not stopping the non-compliant OCI compute instances, you can follow these steps: Enable function logging in the OCI console: Enable logging for your function to ensure that logs are captured during its execution. Modify your function code: Add relevant print statements or log statements at key points in your code to output debug information or verify the execution flow. For example, you can print the instance details that are being evaluated for compliance. Invoke the function: Trigger the function execution either through an event or manually. View the logs: Access the function logs in the OCI console or retrieve them programmatically. Look for the expected print statements or log entries that indicate the status of each instance and the decisions made by the function. By reviewing the logs, you can analyze the output and identify any issues or discrepancies. It can help you determine if the function is correctly evaluating the compliance criteria, retrieving the instance details, or making the necessary API calls to stop the instances. You may need to adjust your code logic or investigate further based on the information provided in the logs. Enabling function remote debugging is not a suitable strategy in this case because it is primarily used for inspecting and debugging the function code during development, rather than troubleshooting issues in a deployed function. Enabling function tracing can provide insights into the execution flow and performance of the function but may not directly address the issue of the instances not being stopped. Ensuring that the application is deployed within the same OCI compartment as the instance is not directly related to troubleshooting the issue with the non-compliant instances. It is a consideration for access and permissions but does not provide specific insights into the problem at hand. Remember to refer to the Oracle Functions documentation and consult the official resources for detailed instructions and best practices on troubleshooting and monitoring Oracle Functions.

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 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 "applicationhttps://www.dumpspedia.com/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

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

To address the requirement of extracting and transforming data from the Oracle Cloud Infrastructure (OCI) Streaming service and sending it to a third-party REST endpoint using the OCI Service Connector Hub, the best configuration option is: Configure a new service connector as follows: • Source: Streaming • Task: None • Target: Notifications By selecting the Streaming service as the source, you can capture the transactional data from the stream. Since there is a need to transform and send the data to a third-party REST endpoint, you don't need to specify any specific task in the connector. The target is set to Notifications, which allows you to send the transformed data to an endpoint outside of the OCI environment. Notifications can be configured to deliver the data to various supported destinations, including HTTP endpoints, email addresses, and more. This configuration enables you to automate the process of extracting data from the streaming service and sending it to the desired third-party REST endpoint, fulfilling the requirement of extracting, transforming, and forwarding the data.

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 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: "read only." The layers of a Docker image are read-only. Once a layer is created, it cannot be modified. Each layer represents a Dockerfile instruction, and it is stacked on top of the previous layer, forming a stack of immutable layers. These layers are designed to be read-only to ensure consistency and integrity of the image. When a Docker image is built, each instruction in the Dockerfile creates a new layer. Each layer represents the changes made by that instruction relative to the previous layer. The layers are stacked on top of each other to form the complete image. This layer-based approach allows for efficient storage and distribution of Docker images. Because the layers are read-only, any changes or modifications to the image result in the creation of new layers rather than modifying the existing ones. This immutability ensures that each layer remains intact and preserves the integrity of the image. It also enables Docker's caching mechanism, where previously built layers can be reused if the corresponding instructions haven't changed, speeding up the image build process. The other options mentioned, such as "write only," "write once," "movable," and "read mostly," do not accurately describe the permission associated with Docker image layers. Docker image layers are specifically designed to be read-only.

Blue/Green deployment strategy allows releasing a new version of an application using two identical environments where one of them is active at a given time. The current version of the application is provisioned on the active environment, whereas the new version gets deployed to the standby environment1. The traffic is shifted from the active to the standby environment by updating the ingress resource2. Therefore, both old and new application versions are deployed to production at the same time, but only one of them receives the traffic. Verified References: Announcing new deployment strategies for OCI DevOps Service, Blue-Green OKE Deployment

Explanation

The correct answer is: "A finely tuned piece of software that performs a single or small collection of tasks." Microservices are a software architectural approach where a system is decomposed into small, independent services that are responsible for performing a specific set of tasks. Each microservice is designed to be focused, finely tuned, and highly cohesive, handling a single or a small collection of related tasks. This granularity allows for better scalability, maintainability, and flexibility in building complex applications. The other options provided do not accurately define microservices: An open-source system for automating deployment, scaling, and management of containerized applications refers to a container orchestration tool like Kubernetes, which can be used to manage microservices but is not a definition of microservices itself. A statically typed and compiled language describes a type of programming language characteristic and is not specific to the concept of microservices. An organized collection of structured information or data, typically stored electronically in a computer system is a definition of a database or data storage system and is unrelated to microservices.

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 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 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.

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

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.