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To achieve good results in the Google Professional Cloud DevOps Engineer certification exam, the candidates need to develop a comprehensive understanding of its domains. The detailed outline of the topics and subtopics covered in the test is available on the official platform. Their brief overview is provided below:
Here the applicants will be asked to show that they have the capacity to manage the Stackdriver Logging and Stackdriver Monitoring platforms. They should also know how to manage application logs as well as application metrics using Stackdriver Monitoring. Additionally, the individuals will require the competency in implementing logging & monitoring access control.
This subject area measures the skills of the professionals in ensuring healthy collaboration for operations, including preventing burnout (for example, setting up automation procedures to prevent burnout) as well as fostering a learning culture & culture of blamelessness. Besides that, the candidates need to possess the expertise in managing the service life cycle as well as balancing the service change, velocity, and reliability.
To answer the questions related to this part of the certification test, the students need to have the skills in coordinating roles and implementing the channels of communication in the course of the service incident. In addition, they need to have an understanding of how to perform the analysis of incident symptoms affecting the users. The test takers should also know how to mitigate the impact of an incident on the users. Finally, they need to have the sufficient competency in resolving issues (for example, Cloud Build, Jenkins, etc.) and documenting an issue in the postmortem.
The second topic focuses on the ability of the examinees to manage various development environments (for instance, staging, production, etc.), manage infrastructure as code, as well as manage configuration & secrets. Moreover, the test takers are required to demonstrate their proficiency in designing & implementing CI/CD pipelines, deploying CI/CD tooling, and securing the deployment pipeline.
Within this module, the learners need to show that they are capable of optimizing resource utilization, including determining resource costs, defining resource utilization levels, developing a plan to optimize areas of the lowest utilization/greatest cost, managing preemptible Virtual Machines, considering network pricing, and so on. They must also possess the skills in debugging application code as well as determining service performance issues.
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Preparation Guide for Google Professional Cloud DevOps Engineer Exam
Introduction
Google has designed a track for IT professionals to endorse as a cloud DevOps Engineer on the GCP platform. This accreditation program gives Google cloud professionals a way to endorse their skills. The evaluation relies on a meticulous exam using the industry-standard methodology to conclude whether or not an aspirant meets Google's proficiency standards.
According to Google, a Google Professional Cloud DevOps Engineer Exam test facilitates organizations to influence Google Cloud technologies. By leveraging experience implementing VPCs, DevOps services, hybrid connectivity, and security for established DevOps architectures, this individual ensures successful cloud implementations using the Google Cloud Platform Console or the command-line interface.
Certification is evidence of your skills, expertise in those areas in which you like to work. If a candidate wants to work as Google Professional Cloud DevOps Engineer and prove his knowledge, certification is offered by Google. This Google Professional Cloud DevOps Engineer Certification helps a candidate to validates his skills in Google Professional Cloud DevOps Engineer Technology.
In this guide, we will cover the Google Professional Cloud DevOps Engineer practice exams, Google Professional Cloud DevOps Engineer Certified Professionals salary, and all aspects of the Google Professional Cloud DevOps Engineer Certification.
Reference: https://cloud.google.com/certification/cloud-devops-engineer
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| Section | Weight | Objectives |
|---|---|---|
| Microservices Architecture | 14% | - API management
|
| Cloud Infrastructure Automation | 24% | - Infrastructure as Code (IaC)
|
| Reliability and Site Reliability Engineering (SRE) | 24% | - Incident management
|
| Monitoring, Logging, and Debugging | 12% | - Log management
|
| CI/CD Pipeline Development | 26% | - Containerization and Docker
|
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