Free Practice Questions for Oracle 1z0-1084-25 Exam

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

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.

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 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 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 in Oracle 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 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.

When configuring an OCI API Gateway deployment, you need to specify the backend type for each route in your API deployment specification3. The backend type determines how the API gateway handles requests to that route and forwards them to the appropriate backend service3. The following backend types are valid options for an OCI API Gateway deployment3:

HTTP_BACKEND: The API gateway forwards requests to an HTTP or HTTPS URL as the backend service.

ORACLE_FUNCTIONS_BACKEND: The API gateway invokes an Oracle Functions function as the backend service.

STOCK_RESPONSE_BACKEND: The API gateway returns a stock response without invoking any backend service. ORACLE STREAMS_BACKEND is not a valid backend type for an OCI API Gateway deployment. Oracle Streams is a fully managed, scalable, and durable messaging service that you can use to ingest and consume large amounts of data in real-time4. However, Oracle Streams is not supported as a backend service for an OCI API Gateway deployment.

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.

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