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To earn the Google Professional-Cloud-DevOps-Engineer Certification, candidates must pass a rigorous exam that consists of multiple-choice and multiple-select questions. Professional-Cloud-DevOps-Engineer exam is designed to test the candidate's ability to apply their knowledge to real-world scenarios and use cases. Candidates must demonstrate their ability to design, develop, and deploy applications using GCP tools and services, as well as their ability to troubleshoot and optimize their applications for performance and scalability.
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Upon successful completion of the certification exam, candidates will receive a Google Cloud Certified - Professional Cloud DevOps Engineer certificate, which demonstrates their proficiency in cloud-based DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is recognized globally and is highly valued by employers, making it an excellent investment for professionals seeking to advance their career in this field.
NEW QUESTION # 13
You work for a global organization and are running a monolithic application on Compute Engine You need to select the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps You want to use historical system metncs to identify the machine type for the application to use You want to follow Google-recommended practices What should you do?
Answer: B
Explanation:
The best option for selecting the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps is to use the Recommender API and apply the suggested recommendations.
The Recommender API is a service that provides recommendations for optimizing your Google Cloud resources, such as Compute Engine instances, disks, and firewalls. You can use the Recommender API to get recommendations for changing the machine type of your Compute Engine instances based on historical system metrics, such as CPU utilization. You can also apply the suggested recommendations by using the Recommender API or Cloud Console. This way, you can optimize CPU utilization by using the most suitable machine type for your application with minimal effort.
NEW QUESTION # 14
You are the Operations Lead for an ongoing incident with one of your services. The service usually runs at around 70% capacity. You notice that one node is returning 5xx errors for all requests. There has also been a noticeable increase in support cases from customers. You need to remove the offending node from the load balancer pool so that you can isolate and investigate the node. You want to follow Google-recommended practices to manage the incident and reduce the impact on users. What should you do?
Answer: D
Explanation:
The correct answer is A, Communicate your intent to the incident team. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.
This answer follows the Google-recommended practices for incident management, as described in the Chapter 9 - Incident Response, Google SRE Book1. According to this source, some of the best practices are:
Maintain a clear line of command. Designate clearly defined roles. Keep a working record of debugging and mitigation as you go. Declare incidents early and often.
Communicate your intent before taking any action that might affect the service or the incident response. This helps to avoid confusion, duplication of work, or unintended consequences.
Perform a load analysis before removing a node from the load balancer pool, as this might affect the capacity and performance of the service. Scale the pool as necessary to handle the expected load.
Drain traffic from the unhealthy node before removing it from service, as this helps to avoid dropping requests or causing errors for users.
Answer A follows these best practices by communicating the intent to the incident team, performing a load analysis and scaling the pool, and draining traffic from the unhealthy node before removing it.
Answer B does not follow the best practice of performing a load analysis before adding or removing nodes, as this might cause overloading or underutilization of resources.
Answer C does not follow the best practice of communicating the intent before taking any action, as this might cause confusion or conflict with other responders.
Answer D does not follow the best practice of draining traffic from the unhealthy node before removing it, as this might cause errors for users.
Reference:
1: Chapter 9 - Incident Response, Google SRE Book
NEW QUESTION # 15
You are responsible for creating and modifying the Terraform templates that define your Infrastructure. Because two new engineers will also be working on the same code, you need to define a process and adopt a tool that will prevent you from overwriting each other's code. You also want to ensure that you capture all updates in the latest version. What should you do?
Answer: D
NEW QUESTION # 16
You are the on-call Site Reliability Engineer for a microservice that is deployed to a Google Kubernetes Engine (GKE) Autopilot cluster. Your company runs an online store that publishes order messages to Pub/Sub and a microservice receives these messages and updates stock information in the warehousing system. A sales event caused an increase in orders, and the stock information is not being updated quickly enough. This is causing a large number of orders to be accepted for products that are out of stock You check the metrics for the microservice and compare them to typical levels.
You need to ensure that the warehouse system accurately reflects product inventory at the time orders are placed and minimize the impact on customers What should you do?
Answer: A
Explanation:
The best option for ensuring that the warehouse system accurately reflects product inventory at the time orders are placed and minimizing the impact on customers is to increase the number of Pod replicas.
Increasing the number of Pod replicas will increase the scalability and availability of your microservice, which will allow it to handle more Pub/Sub messages and update stock information faster. This way, you can reduce the backlog of undelivered messages and oldest unacknowledged message age, which are causing delays in updating product inventory. You can use Horizontal Pod Autoscaler or Cloud Monitoring metrics- based autoscaling to automatically adjust the number of Pod replicas based on load or custom metrics.
NEW QUESTION # 17
You are configuring a Cl pipeline. The build step for your Cl pipeline integration testing requires access to APIs inside your private VPC network. Your security team requires that you do not expose API traffic publicly. You need to implement a solution that minimizes management overhead. What should you do?
Answer: B
Explanation:
Explanation
Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure1. Cloud Build can be used as a pipeline runner for your CI pipeline, which is a process that automates the integration and testing of your code2. Cloud Build private pools are private, dedicated pools of workers that offer greater customization over the build environment, including the ability to access resources in a private VPC network3.
A VPC network is a virtual network that provides connectivity for your Google Cloud resources and services. By using Cloud Build private pools, you can implement a solution that minimizes management overhead, as Cloud Build private pools are hosted and fully-managed by Cloud Build and scale up and down to zero, with no infrastructure to set up, upgrade, or scale3. You can also implement a solution that meets your security requirement, as Cloud Build private pools use network peering to connect into your private VPC network and do not expose API traffic publicly.
NEW QUESTION # 18
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