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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Native Applications and Containerization | 33% | - Container Orchestration
|
| Topic 2: Monitoring & Troubleshooting Cloud Native Applications | 10% | - Monitoring, Logging, and Tracing
|
| Topic 3: Testing and Securing Cloud Native Applications | 13% | - Cloud Native Testing
|
| Topic 4: Cloud Native Fundamentals | 11% | - Cloud Native Principles
|
| Topic 5: Leveraging Serverless Technologies for Cloud Native Development | 33% | - OCI Queue
|
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NEW QUESTION # 108
Which is ONE of the differences between a microservice and a serverless function?
Answer: D
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.
NEW QUESTION # 109
To effectively test your cloud native applications for " unknown unknowns " , you need to employ various testing and deployment strategies. Which strategy involves exposing new functionality or features to only a small set of users?
Answer: A
Explanation:
The strategy that involves exposing new functionality or features to only a small set of users is called Canary Deployment. Canary deployment is a technique used in software development and deployment where a new version of an application or feature is released to a small subset of users or a specific group of servers. This allows for testing and gathering feedback on the new functionality in a controlled and limited environment before making it available to a wider audience. In a canary deployment, a small portion of the traffic is routed to the new version while the majority of the traffic still goes to the stable version. This allows for monitoring and evaluation of the new functionality in real-world conditions while minimizing the impact of any potential issues or bugs. If the new version performs well and meets the desired criteria, it can then be gradually rolled out to a larger user base or all servers. By exposing the new functionality or features to a small set of users initially, canary deployment helps in identifying any unforeseen issues, gathering feedback, and ensuring the stability and reliability of the application before a full deployment.
NEW QUESTION # 110
Which testing measure should be considered when using test cases that simultaneously validate a deployment and perform a selected set of functional tasks?
Answer: A
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.
NEW QUESTION # 111
Your team has created a serverless application deployed in Oracle Functions. It uses a Python function leveraging the Oracle Cloud Infrastructure (OCI) Python SDK to stop any OCI compute instance that does not comply with your corporate security standards. Although there are three non-compliant OCI compute instances, when you invoke this function, none of the instances were stopped. With respect to this issue, which of the following is a valid troubleshooting strategy?
Answer: D
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.
NEW QUESTION # 112
Which node configuration in Oracle Cloud Infrastructure Container Engine for Kubernetes provides a serverless experience with granular pod-level elasticity and billing?
Answer: A
Explanation:
OKE Virtual Nodes provide Oracle ' s serverless Kubernetes execution model. Oracle manages the underlying node infrastructure, eliminating the need for customers to provision, patch, upgrade, scale, or troubleshoot conventional worker-node infrastructure. Resource allocation and elasticity occur at the pod level, allowing workloads to scale without planning the capacity of a conventional node pool. Oracle also describes Virtual Nodes as providing pay-per-use pricing based on the compute resources consumed by each Kubernetes pod rather than charging for entire worker servers that might contain unused capacity. Managed, bare metal, and self-managed nodes remain infrastructure-oriented worker-node models and therefore do not provide the same serverless pod-level operating model. Consequently, Virtual Nodes are the configuration designed for granular elasticity and pod-oriented consumption.
NEW QUESTION # 113
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