How to Prepare For Google Professional Cloud DevOps Engineer Exam

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.

Topics of Google Professional Cloud DevOps Engineer Exam

Candidates must know the exam topics before they start preparation because it will help them in hitting the core. Our Professional Cloud DevOps Engineer Dumps will include the following topics:

Applying site reliability engineering principles to a service

• 1.2 Manage service life cycle:
• Agree to consequences of not meeting the error budget
• Construct feedback loops to decide what to build next
• Manage a service (e.g., introduce a new service, deploy it, maintain and retire it)
• Define SLOs and understand SLAs
• Toil automation
• Discover SLIs (availability, latency, etc.)
• Balance change, velocity, and reliability of the service:

Building and implementing CI/CD pipelines for a service

• Immutable artifacts with Container Registry
• Deployment to hybrid and multi-cloud environments with Anthos, Spinnaker, Kubernetes
• Design CI/CD pipelines:
• CI/CD pipeline triggers with Cloud Source Repositories, Cloud Build GitHub App, Cloud Pub/Sub
• Testing a new version with Spinnaker
• Configure deployment processes (e.g., approval flows)
• Artifact versioning strategy with Cloud Build, Container Registry
• Deployment strategies with Cloud Build, Spinnaker
• Artifact repositories with Container Registry

Implementing service monitoring strategies

• Collecting third-party and structured logs with Stackdriver Logging, Fluentd
• Collecting metrics from Compute Engine
• Set ACL to allow metric writing for custom metrics with IAM, Stackdriver Monitoring
• Sending logs to an external logging platform
• Use metric explorer for ad hoc metric analysis
• Understanding the logging exclusion vs. logging export
• Set ACL to restrict export configuration with IAM, Stackdriver Logging
• Viewing export logs in Cloud Storage and BigQuery
• Using basic vs. advanced logging filters
• Enabling data access logs (e.g., Cloud Audit Logs)
• Manage application logs:
• Sending application logs directly to Stackdriver API with Stackdriver Logging
• Implementing a project-level / org-level export
• Set ACL to restrict access to audit logs with IAM, Stackdriver Logging
• Implementing logs-based metrics
• Collecting logs from Compute Engine, GKE with Stackdriver Logging, Fluentd
• Enabling VPC flow logs
• Selecting the options for logging export
• Collecting GKE/Kubernetes metrics
• Viewing logs in the GCP Console

Optimizing service performance

• Work with committed-use discounts
• Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)
• Consider network pricing
• Identify service performance issues:
• TCO considerations
• identify resource costs
• Utilize Stackdriver Trace/Profiler to profile performance characteristics
• Interpret service mesh telemetry
• Develop a plan to optimize areas of greatest cost or lowest utilization
• Troubleshoot issues with the image/OS
• Manage preemptible VMs
• Identify resource utilization levels
• Evaluate and understand user impact (Stackdriver Service Monitoring for App Engine, Istio)
• Utilize Stackdriver to identify cloud resource utilization

Managing service incidents

• Record major changes in incident state (When mitigated? When all clear? etc.)
• Perform an investigation to isolate the most likely actual cause
• Handle requests for impact assessment
• Avoid exhaustion/burnout
• Manage stakeholder relationships
• Identify probable causes of service failure
• Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)
• Provide regular status updates, internal and external
• Identify alternatives to mitigate the issue
• Scaling response team and delegation
• Define roles (incident commander, communication lead, operations lead)
• Coordinate roles and implement communication channels during a service incident:
• Rotate/hand over roles
• Evaluate symptoms against probable causes; the rank probability of cause based on observed behavior

Reference: https://cloud.google.com/certification/cloud-devops-engineer

The Google Professional Cloud DevOps Engineer exam is taken by the specialists who want to obtain international certification and get validated as professional engineers who can manage Cloud DevOps features.

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.