GUARANTEED PROFESSIONAL-CLOUD-DEVOPS-ENGINEER PASSING, PROFESSIONAL-CLOUD-DEVOPS-ENGINEER TRAINING TOOLS

Guaranteed Professional-Cloud-DevOps-Engineer Passing, Professional-Cloud-DevOps-Engineer Training Tools

Guaranteed Professional-Cloud-DevOps-Engineer Passing, Professional-Cloud-DevOps-Engineer Training Tools

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Introduction to Google Professional Cloud DevOps Engineer Exam

Google Professional Cloud DevOps Engineer Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud DevOps engineer in the IT industry.

After passing this Professional Cloud DevOps Engineer Exam test, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud DevOps Engineer to their clients and employers.

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Google Professional-Cloud-DevOps-Engineer certification is recognized globally and is highly valued by employers. It demonstrates that the candidate has the knowledge and skills required to design, implement, and manage cloud-based solutions. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification also indicates that the candidate is proficient in using Google Cloud Platform tools and technologies to optimize the development and deployment of software applications. Overall, the Google Professional-Cloud-DevOps-Engineer Certification is an excellent investment for professionals who are looking to advance their careers in the technology industry.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q171-Q176):

NEW QUESTION # 171
You are performing a semi-annual capacity planning exercise for your flagship service You expect a service user growth rate of 10% month-over-month for the next six months Your service is fully containerized and runs on a Google Kubemetes Engine (GKE) standard cluster across three zones with cluster autoscaling enabled You currently consume about 30% of your total deployed CPU capacity and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth o' as a result of zone failure while you avoid unnecessary costs How should you prepare to handle the predicted growth?

  • A. Because you deployed the service on GKE and are using a cluster autoscaler your GKE cluster will scale automatically regardless of growth rate
  • B. Because you are only using 30% of deployed CPU capacity there is significant headroom and you do not need to add any additional capacity for this rate of growth
  • C. Proactively add 80% more node capacity to account for six months of 10% growth rate and then perform a load test to ensure that you have enough capacity
  • D. Verify the maximum node pool size enable a Horizontal Pod Autoscaler and then perform a load lest to verify your expected resource needs

Answer: D

Explanation:
The best option for preparing to handle the predicted growth is to verify the maximum node pool size, enable a Horizontal Pod Autoscaler, and then perform a load test to verify your expected resource needs. The maximum node pool size is a parameter that specifies the maximum number of nodes that can be added to a node pool by the cluster autoscaler. You should verify that the maximum node pool size is sufficient to accommodate your expected growth rate and avoid hitting any quota limits. The Horizontal Pod Autoscaler is a feature that automatically adjusts the number of Pods in a deployment or replica set based on observed CPU utilization or custom metrics. You should enable a Horizontal Pod Autoscaler for your application to ensure that it runs enough Pods to handle the load. A load test is a test that simulates high user traffic and measures the performance and reliability of your application. You should perform a load test to verify your expected resource needs and identify any bottlenecks or issues.


NEW QUESTION # 172
Your company runs applications in Google Kubernetes Engine (GKE). Several applications rely on ephemeral volumes. You noticed some applications were unstable due to the DiskPressure node condition on the worker nodes. You need to identify which Pods are causing the issue, but you do not have execute access to workloads and nodes.
What should you do?

  • A. Check the metric by using Metrics Explorer.
  • B. Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
  • C. Locate all the Pods with emptyDir volumes. use the df-h command to measure volume disk usage.
  • D. Locate all the Pods with emptyDir volumes. Use the du -sh * command to measure volume disk usage.

Answer: B

Explanation:
The correct answer is A. Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
The node/ephemeral_storage/used_bytes metric reports the total amount of ephemeral storage used by Pods on each node1.You can use Metrics Explorer to query and visualize this metric and filter it by node name, namespace, or Pod name2. This way, you can identify which Pods are consuming the most ephemeral storage and causing disk pressure on the nodes. You do not need to have execute access to the workloads or nodes to use Metrics Explorer.
The other options are incorrect because they require execute access to the workloads or nodes, which you do not have.The df -h and du -sh * commands are Linux commands that can measure disk usage, but you need to run them inside the Pods or on the nodes, which is not possible in your scenario34.


NEW QUESTION # 173
You support a service with a well-defined Service Level Objective (SLO). Over the previous 6 months, your service has consistently met its SLO and customer satisfaction has been consistently high. Most of your service's operations tasks are automated and few repetitive tasks occur frequently. You want to optimize the balance between reliability and deployment velocity while following site reliability engineering best practices.
What should you do? (Choose two.)

  • A. Get the product team to prioritize reliability work over new features.
  • B. Change the implementation of your Service Level Indicators (SLIs) to increase coverage.
  • C. Shift engineering time to other services that need more reliability.
  • D. Increase the service's deployment velocity and/or risk.
  • E. Make the service's SLO more strict.

Answer: C,D

Explanation:
Explanation
(https://sre.google/workbook/implementing-slos/#slo-decision-matrix)


NEW QUESTION # 174
You recently noticed that one Of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices.
What should you do?

  • A. Look through other metrics related to the product and find SLOs with remaining error budget. Reallocate the error budgets and allow the feature launch.
  • B. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
  • C. Notify the team about the lack of error budget and ensure that all their tests are successful so the launch will not further risk the error budget.
  • D. Escalate the situation and request additional error budget.

Answer: B

Explanation:
The correct answer is
A, Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
According to the Site Reliability Engineering (SRE) practices, an error budget is the amount of unreliability that a service can tolerate without harming user satisfaction1. An error budget is derived from the service-level objectives (SLOs), which are the measurable goals for the service quality2. When a service exceeds its error budget, it means that it has violated its SLOs and may have negatively impacted the users. In this case, the SRE team should notify the product team that their error budget is used up and negotiate with them for a launch freeze or a lower SLO3. A launch freeze means that no new features are deployed until the service reliability is restored. A lower SLO means that the product team accepts a slightly worse user experience in exchange for launching new features. Both options require a trade-off between reliability and innovation, and should be agreed upon by both teams.
The other options are incorrect because they do not follow the SRE practices. Option B is incorrect because it violates the principle of error budget autonomy, which means that each service should have its own error budget and SLOs, and should not borrow or reallocate them from other services4. Option C is incorrect because it does not address the root cause of the error budget overspend, and may create unrealistic expectations for the service reliability. Option D is incorrect because it does not prevent the possibility of introducing new errors or bugs with the feature launch, which may further degrade the service quality and user satisfaction.
Reference:
Error Budgets, Error Budgets. Service Level Objectives, Service Level Objectives. Error Budget Policies, Error Budget Policies. Error Budget Autonomy, Error Budget Autonomy.


NEW QUESTION # 175
You are configuring Cloud Logging for a new application that runs on a Compute Engine instance with a public IP address. A user-managed service account is attached to the instance. You confirmed that the necessary agents are running on the instance but you cannot see any log entries from the instance in Cloud Logging. You want to resolve the issue by following Google-recommended practices. What should you do?

  • A. Enable Private Google Access on the subnet that the instance is in.
  • B. Update the instance to use the default Compute Engine service account.
  • C. Add the Logs Writer role to the service account.
  • D. Export the service account key and configure the agents to use the key.

Answer: C

Explanation:
The correct answer is A. Add the Logs Writer role to the service account.
To use Cloud Logging, the service account attached to the Compute Engine instance must have the necessary permissions to write log entries. The Logs Writer role (roles/logging.logWriter) provides this permission.You can grant this role to the user-managed service account at the project, folder, or organization level1.
Private Google Access is not required for Cloud Logging, as it allows instances without external IP addresses to access Google APIs and services2.The default Compute Engine service account already has the Logs Writer role, but it is not a recommended practice to use it for user applications3.Exporting the service account key and configuring the agents to use the key is not a secure way of authenticating the service account, as it exposes the key to potential compromise4.
References:
1:Access control with IAM | Cloud Logging | Google Cloud
2: Private Google Access overview | VPC | Google Cloud
3: Service accounts | Compute Engine Documentation | Google Cloud
4: Best practices for securing service accounts | IAM Documentation | Google Cloud


NEW QUESTION # 176
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