100% PASS PERFECT GOOGLE - PROFESSIONAL-CLOUD-DEVOPS-ENGINEER ACCURATE ANSWERS

100% Pass Perfect Google - Professional-Cloud-DevOps-Engineer Accurate Answers

100% Pass Perfect Google - Professional-Cloud-DevOps-Engineer Accurate Answers

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How to study the Google Professional Cloud DevOps Engineer Exam

Preparation of certification exams could be covered with two resource types. The first one is the study guides, reference books, and study forums that are elaborated and appropriate for building information from the ground up. Apart from the video tutorials and lectures are a good option to ease the pain of through study and are relatively make the study process more interesting nonetheless these demand time and concentration from the learner. Smart candidates who wish to create a solid foundation altogether examination topics and connected technologies typically mix video lectures with study guides to reap the advantages of each but practice exams or practice exam engines is one important study tool which goes typically unnoted by most candidates.

Professional Cloud DevOps Engineer practice test is designed by our experts to make exam prospects test their knowledge on skills attained in the course, as well as prospects become comfortable and familiar with the real exam environment. Statistics have indicated exam anxiety plays a much bigger role in students' failure in the exam than the fear of the unknown. Prep4sureGuide expert team recommends preparing some notes on these topics along with it don't forget to practice Professional Cloud DevOps Engineer exam dumps which had been written by our expert team, each of these can assist you loads to clear this exam with excellent marks.

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To prepare for the exam, candidates are advised to take relevant training courses, read the official study guide, and practice using the Google Cloud Platform. They should also have hands-on experience working with DevOps tools and technologies, such as Docker, Kubernetes, Jenkins, and Terraform. With the right preparation, candidates can pass the Google Professional-Cloud-DevOps-Engineer exam and join the elite group of Cloud DevOps experts who are in high demand in the IT industry.

To become a Certified Professional Cloud DevOps Engineer, the candidate must have a deep understanding of agile and DevOps methodologies, as well as proficiency in GCP services such as Kubernetes, Google Cloud Build, Google Cloud Functions, Google Cloud Monitoring, and more. Professional-Cloud-DevOps-Engineer Exam also tests the candidate's ability to design and implement continuous integration/continuous delivery (CI/CD) pipelines, automate infrastructure deployments, and monitor and optimize application performance using GCP tools.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q152-Q157):

NEW QUESTION # 152
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (PII) is leaking into certain log entry fields. All PII entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

  • A. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
  • B. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
  • C. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a log exclusion with userinfo as a filter.
  • D. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.

Answer: B


NEW QUESTION # 153
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?

  • A. Use the Recommender API and apply the suggested recommendations
  • B. Install the Ops Agent in a fleet of VMs by using the gcloud CLI
  • C. Review the Cloud Monitoring dashboard for the VM and choose the machine type with the lowest CPU utilization
  • D. Create an Agent Policy to automatically install Ops Agent in all VMs

Answer: A

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 # 154
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to a Kubernetes cluster in the production environment. The security auditor is concerned that developers or operators could circumvent automated testing and push code changes to production without approval. What should you do to enforce approvals?

  • A. Leverage Kubernetes Role-Based Access Control (RBAC) to restrict access to only approved users.
  • B. Configure the build system with protected branches that require pull request approval.
  • C. Use an Admission Controller to verify that incoming requests originate from approved sources.
  • D. Enable binary authorization inside the Kubernetes cluster and configure the build pipeline as an attestor.

Answer: D

Explanation:
The keywords here is "developers or operators". Option A the operators could push images to production without approval (operators could touch the cluster directly and the cluster cannot do any action against them). Rest same as francisco_guerra.


NEW QUESTION # 155
You are creating and assigning action items in a postmodern for an outage. The outage is over, but you need to address the root causes. You want to ensure that your team handles the action items quickly and efficiently. How should you assign owners and collaborators to action items?

  • A. Assign collaborators but no individual owners to the items to keep the postmortem blameless.
  • B. Assign multiple owners for each item to guarantee that the team addresses items quickly
  • C. Assign the team lead as the owner for all action items because they are in charge of the SRE team.
  • D. Assign one owner for each action item and any necessary collaborators.

Answer: D

Explanation:
https://devops.com/when-it-disaster-strikes-part-3-conducting-a-blameless-post-mortem/


NEW QUESTION # 156
Your Cloud Run application writes unstructured logs as text strings to Cloud Logging. You want to convert the unstructured logs to JSON-based structured logs. What should you do?

  • A. A Install a Fluent Bit sidecar container, and use a JSON parser.
  • B. Install the log agent in the Cloud Run container image, and use the log agent to forward logs to Cloud Logging.
  • C. Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPay10ad field.
  • D. Configure the log agent to convert log text payload to JSON payload.

Answer: C

Explanation:
The correct answer is D. Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPayload field.
Cloud Logging SDKs are libraries that allow you to write structured logs from your Cloud Run application.
You can use the SDKs to create log entries with a jsonPayload field, which contains a JSON object with the properties of your log entry.The jsonPayload field allows you to use advanced features of Cloud Logging, such as filtering, querying, and exporting logs based on the properties of your log entry1.
To use Cloud Logging SDKs, you need to install the SDK for your programming language, and then use the SDK methods to create and send log entries to Cloud Logging.For example, if you are using Node.js, you can use the following code to write a structured log entry with a jsonPayload field2:
// Imports the Google Cloud client library
const {Logging} = require('@google-cloud/logging');
// Creates a client
const logging = new Logging();
// Selects the log to write to
const log = logging.log('my-log');
// The data to write to the log
const text = 'Hello, world!';
const metadata = {
// Set the Cloud Run service name and revision as labels
labels: {
service_name: process.env.K_SERVICE || 'unknown',
revision_name: process.env.K_REVISION || 'unknown',
},
// Set the log entry payload type and value
jsonPayload: {
message: text,
timestamp: new Date(),
},
};
// Prepares a log entry
const entry = log.entry(metadata);
// Writes the log entry
await log.write(entry);
console.log(`Logged: ${text}`);
Using Cloud Logging SDKs is the best way to convert unstructured logs to structured logs, as it provides more flexibility and control over the format and content of your log entries.
Using a Fluent Bit sidecar container is not a good option, as it adds complexity and overhead to your Cloud Run application.Fluent Bit is a lightweight log processor and forwarder that can be used to collect and parse logs from various sources and send them to different destinations3. However, Cloud Run does not support sidecar containers, so you would need to run Fluent Bit as part of your main container image. This would require modifying your Dockerfile and configuring Fluent Bit to read logs from supported locations and parse them as JSON. This is more cumbersome and less reliable than using Cloud Logging SDKs.
Using the log agent in the Cloud Run container image is not possible, as the log agent is not supported on Cloud Run. The log agent is a service that runs on Compute Engine or Google Kubernetes Engine instances and collects logs from various applications and system components. However, Cloud Run does not allow you to install or run any agents on its underlying infrastructure, as it is a fully managed service that abstracts away the details of the underlying platform.
Storing the password directly in the code is not a good practice, as it exposes sensitive information and makes it hard to change or rotate the password. It also requires rebuilding and redeploying the application each time the password changes, which adds unnecessary work and downtime.
References:
1:Writing structured logs | Cloud Run Documentation | Google Cloud
2:Write structured logs | Cloud Run Documentation | Google Cloud
3: Fluent Bit - Fast and Lightweight Log Processor & Forwarder
Logging Best Practices for Serverless Applications - Google Codelabs
About the logging agent | Cloud Logging Documentation | Google Cloud
Cloud Run FAQ | Google Cloud


NEW QUESTION # 157
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