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Title: Reliable Professional-Cloud-DevOps-Engineer Exam Answers & Professional-Clou [Print This Page]
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Title: Reliable Professional-Cloud-DevOps-Engineer Exam Answers & Professional-Clou
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The Google Professional Cloud DevOps Engineer certification is designed to equip the specialists with the expertise required to perform the following technical tasks: applying the principles of site reliability engineering to services, optimizing service performance, implementing the strategies for service monitoring, building and implementing CI/CD pipelines for services, as well as managing service incidents. To get the certificate, the candidates need to complete a single exam covering a wide range of knowledge and skills.
To earn the Google Professional-Cloud-DevOps-Engineer certification, you will need to pass a rigorous exam that covers a wide range of topics related to cloud computing, automation, and continuous delivery. Professional-Cloud-DevOps-Engineer exam consists of multiple-choice questions and is designed to evaluate your ability to design, implement, and manage cloud-based solutions using Google Cloud Platform. Professional-Cloud-DevOps-Engineer Exam also tests your understanding of various DevOps tools and methodologies, such as Docker, Kubernetes, Ansible, and Jenkins. By passing Professional-Cloud-DevOps-Engineer exam, you will demonstrate your proficiency in using Google Cloud Platform to build and deploy scalable and reliable applications and gain recognition as a certified professional in cloud DevOps engineering.
Google Professional-Cloud-DevOps-Engineer exam is a certification program designed to validate the skills and knowledge of professionals in the field of DevOps engineering on the Google Cloud Platform. Professional-Cloud-DevOps-Engineer exam is intended for individuals who are experienced in DevOps practices and have expertise in designing, building, and maintaining scalable and reliable cloud solutions.
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q153-Q158):NEW QUESTION # 153
You are building an application that runs on Cloud Run The application needs to access a third-party API by using an API key You need to determine a secure way to store and use the API key in your application by following Google-recommended practices What should you do?
Answer: B
Explanation:
Explanation
The best option for storing and using the API key in your application by following Google-recommended practices is to save the API key in Secret Manager as a secret and reference the secret as an environment variable in the Cloud Run application. Secret Manager is a service that allows you to store and manage sensitive data, such as API keys, passwords, and certificates, in Google Cloud. A secret is a resource that represents a logical secret, such as an API key. You can save the API key in Secret Manager as a secret and use IAM policies to control who can access it. You can also reference the secret as an environment variable in the Cloud Run application by using the ${SECRET_NAME} syntax. This way, you can securely store and use the API key in your application without exposing it in your code or configuration files.

NEW QUESTION # 154
You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?
Answer: A

NEW QUESTION # 155
You recently migrated an ecommerce application to Google Cloud. You now need to prepare the application for the upcoming peak traffic season. You want to follow Google-recommended practices. What should you do first to prepare for the busy season?
Answer: D
Explanation:
The first thing you should do to prepare your ecommerce application for the upcoming peak traffic season is to load test the application to profile its performance for scaling. Load testing is a process of simulating high traffic or user demand on your application and measuring how it responds. Load testing can help you identify any bottlenecks, errors, or performance issues that might affect your application during the busy season1. Load testing can also help you determine the optimal scaling strategy for your application, such as horizontal scaling (adding more instances) or vertical scaling (adding more resources to each instance)2.
There are different tools and methods for load testing your ecommerce application on Google Cloud, depending on the type and complexity of your application. For example, you can use Cloud Load Balancing to distribute traffic across multiple instances of your application, and use Cloud Monitoring to measure the latency, throughput, and error rate of your application3. You can also use Cloud Functions or Cloud Run to create serverless load generators that can simulate user requests and send them to your application4. Alternatively, you can use third-party tools such as Apache JMeter or Locust to create and run load tests on your application.
By load testing your ecommerce application before the peak traffic season, you can ensure that your application is ready to handle the expected load and provide a good user experience. You can also use the results of your load tests to plan and implement other steps to prepare your application for the busy season, such as migrating to a more scalable platform, creating a Terraform configuration for deploying to additional regions, or pre-provisioning additional compute power.
Reference:
1: Load Testing 101: How To Test Website Performance | BlazeMeter
2: Scaling applications | Google Cloud
3: Load testing using Google Cloud | Solutions | Google Cloud
4: Serverless load testing using Cloud Functions | Solutions | Google Cloud

NEW QUESTION # 156
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 # 157
You deploy a new release of an internal application during a weekend maintenance window when there is minimal user traffic. After the window ends, you learn that one of the new features isn't working as expected in the production environment. After an extended outage, you roll back the new release and deploy a fix. You want to modify your release process to reduce the mean time to recovery so you can avoid extended outages in the future. What should you do?
Choose 2 answers
Answer: B,E

NEW QUESTION # 158
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