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Title: Google Professional-Cloud-DevOps-Engineer Exam Questions - Tips To Pass [Print This Page]
Author: rickall310    Time: yesterday 19:02
Title: Google Professional-Cloud-DevOps-Engineer Exam Questions - Tips To Pass
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What is the duration, language, and format of Google Professional Cloud DevOps Engineer ExamThe Professional-Cloud-DevOps-Engineer certification exam covers a broad range of topics, including agile and Scrum methodologies, containerization, microservices, infrastructure as code, and monitoring and logging. Professional-Cloud-DevOps-Engineer exam consists of multiple-choice and multiple-select questions and requires candidates to demonstrate their knowledge of DevOps practices and how they can be applied on the Google Cloud Platform. Professional-Cloud-DevOps-Engineer Exam Duration is two hours, and the passing score is 70%.
Google Professional-Cloud-DevOps-Engineer Certification Exam is an essential certification for professionals who want to validate their skills and expertise in Cloud DevOps engineering. It demonstrates to potential employers that the candidate has the necessary knowledge and experience to design, deploy, and manage applications on the Google Cloud platform. If you're a DevOps engineer looking to take your career to the next level, this certification is definitely worth considering.
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q182-Q187):NEW QUESTION # 182
Your company operates in a highly regulated domain that requires you to store all organization logs for seven years You want to minimize logging infrastructure complexity by using managed services You need to avoid any future loss of log capture or stored logs due to misconfiguration or human error What should you do?
Answer: D

NEW QUESTION # 183
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: D
Explanation:
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 # 184
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?
Answer: D
Explanation:
Explanation
https://cloud.google.com/build/docs/deploying-builds/deploy-gke
https://cloud.google.com/build/d ... ed-service-accounts

NEW QUESTION # 185
You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?
Answer: B

NEW QUESTION # 186
Your company runs an e-commerce business. The application responsible for payment processing has structured JSON logging with the following schema:
Capture and access of logs from the payment processing application is mandatory for operations, but the jsonPayload.user_email field contains personally identifiable information (PII). Your security team does not want the entire engineering team to have access to PII. You need to stop exposing PII to the engineering team and restrict access to security team members only. What should you do?
Answer: B
Explanation:
To restrict access to specific sensitive log fields (e.g. PII), Google Cloud offers Log field-level access control
. You can apply field-level restrictions and then assign the Log Field Accessor role only to trusted personnel.
"You can use field-level access control to restrict access to certain fields in your logs. For example, you can restrict access to jsonPayload.user_email."
- Cloud Logging Field-Level Access
"Grant the roles/logging.fieldAccessor role to principals that require access to these restricted fields."
- Log Field Accessor Role
This lets your operations team continue using logs while ensuring that PII is only visible to the security team
, fulfilling your compliance obligations.

NEW QUESTION # 187
......
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