In today’s tech world, jobs in IT are super popular for people switching careers or learning new skills. Being certified in IT is valuable not just in IT companies but also in other types of companies. All companies want really skilled and certified workers to make sure the job gets done well and efficiently. The Google Professional Cloud DevOps Engineer (GCP) Exam is amongst the top-rated certification exams that require proper preparation and learning resources to qualify for the exam. It is regarded as the Best Cloud Engineer Certification currently.
Yet studying for a test is no simple task. In preparation, you must be completely committed and persistent. The most crucial question is now at hand: How challenging is the exam to pass? Yet, it is crucial to review all the preparational elements before looking for replies. Now let’s look at the exam specifics first.
About Google Professional Cloud DevOps Engineer (GCP)
The Google Professional Cloud DevOps Engineer (GCP) certification exam tests an individual’s knowledge and skills in using GCP to design, develop, and manage cloud-based solutions. The exam covers the following areas:
- Continuous integration and delivery (CI/CD)
- Infrastructure as code
- Monitoring and logging
- Configuration management and security
- Networking and load balancing
- Containers and orchestration
- Scalability and reliability
The Google Professional Cloud DevOps Engineer Certification exam was created to evaluate technical abilities relevant to the position. Applicants should have practical experience before taking the test.
Target Audience:
The Google Professional Cloud DevOps Engineer (GCP) exam is designed for IT professionals who have experience in developing and managing applications and infrastructure on the Google Cloud Platform (GCP) and want to validate their expertise in DevOps practices and principles.
Specifically, the exam is intended for individuals who have experience in the following areas:
- Designing, building, and deploying applications on GCP
- Managing and monitoring GCP infrastructure and services
- Implementing DevOps practices using GCP tools and services
- Designing and implementing CI/CD pipelines on GCP
- Implementing security and compliance measures on GCP
- Troubleshooting and optimizing GCP deployments
Although there aren’t strict requirements for the GCP DevOps Engineer exam, it’s a good idea for candidates to have around three years of industry experience, including at least one year with GCP. It’s also important for candidates to know about DevOps principles, have experience with automation tools, and be familiar with scripting languages.
Exam Details
The Google Professional Cloud Devops Engineer Certification Exam Questions will be in multiple-choice, and multiple select format. Candidates will be assessed on the basis of these questions. Furthermore, As far as the exam duration is concerned, this exam will be for a duration of 4 hours. Also, An application fee of $200 (plus tax where applicable) is to be paid to take the exam.
| 1. Exam Name Google Professional Cloud DevOps Engineer | 2. Exam Code GCP |
| 3. Exam Duration 2 hours | 4. Exam Format Multiple Choice and Multi-Response Questions |
| 5. Exam Type Proctored Exam | 6. Passing Score NA |
| 7. Eligibility/Pre-Requisite None | 8. Exam Fee $200 USD* |
| 9. Exam Language English | 10. Recommended Experience Three+ years of industry experience including one+ years managing solutions on GCP |
Now that we are fully equipped with all the details of the exam, let us now dive into the course structure and the preparation guide of the exam along with figuring out the difficulty level of the exam.
Course Structure
Google Professional Cloud Devops Engineer Course covers the following topics –
Topic 1: Bootstrapping a Google Cloud organization for DevOps (17%)
1.1 Designing the overall resource hierarchy for an organization. Considerations include:
- Projects and folders (Google Documentation: Creating and managing Folders)
- Shared networking (Google Documentation: Shared VPC)
- Identity and Access Management (IAM) roles and organization-level policies (Google Documentation: IAM overview)
- Creating and managing service accounts (Google Documentation: Create a service account)
1.2 Managing infrastructure as code. Considerations include:
- Infrastructure as code tooling (e.g., Cloud Foundation Toolkit, Config Connector, Terraform, Helm) (Google Documentation: Config Connector overview, Infrastructure as Code on Google Cloud)
- Making infrastructure changes using Google-recommended practices and infrastructure as code blueprints (Google Documentation: Using Recommendations for Infrastructure as Code)
- Immutable architecture (Google Documentation: Best practices for operating containers)
1.3 Designing a CI/CD architecture stack in Google Cloud, hybrid, and multi-cloud environments. Considerations include:
- CI with Cloud Build (Google Documentation: Cloud Build, Cloud Build documentation)
- CD with Google Cloud Deploy (Google Documentation: Cloud Build documentation)
- Widely used third-party tooling (e.g., Jenkins, Git, ArgoCD, Packer)
- Security of CI/CD tooling (Google Documentation: Building a secure CI/CD pipeline using Google Cloud built-in services)
1.4 Managing multiple environments (e.g., staging, production). Considerations include:
- Determining the number of environments and their purpose (Google Documentation: Create Cloud Composer environments)
- Creating environments dynamically for each feature branch with Google Kubernetes Engine (GKE) and Terraform (Google Documentation: Create a GKE cluster and deploy a workload using Terraform, Modern CI/CD with GKE: Build a CI/CD system)
- Config Management (Google Documentation: Configurations Overview)
Topic 2: Building and implementing CI/CD pipelines for a service (23%)
2.1 Designing and managing CI/CD pipelines. Considerations include:
- Artifact management with Artifact Registry (Google Documentation: Artifact Registry overview)
- Deployment to hybrid and multi-cloud environments (e.g., Anthos, GKE) (Google Documentation: GKE Multi-Cloud documentation, Anthos)
- CI/CD pipeline triggers (Google Documentation: Cloud Build triggers)
- Testing a new application version in the pipeline (Google Documentation: Test and deploy your application)
- Configuring deployment processes (e.g., approval flows) (Google Documentation: Setting up a CI/CD pipeline for your data-processing workflow)
- CI/CD of serverless applications (Google Documentation: Cloud Build)
2.2 Implement CI/CD pipelines:
- Auditing and tracking deployments (e.g., Artifact Registry, Cloud Build, Google Cloud Deploy, Cloud Audit Logs) (Google Documentation: Artifact Registry audit logging, Cloud Audit Logs overview)
- Deployment strategies (e.g., canary, blue/green, rolling, traffic splitting)
- Rollback strategies (Google Documentation: Rollbacks, gradual rollouts, and traffic migration)
- Troubleshooting deployment issues (Google Documentation: Troubleshooting deployments)
2.3 Managing CI/CD configuration and secrets. Considerations include:
- Secure storage methods and key rotation services (e.g., Cloud Key Management Service, Secret Manager) (Google Documentation: Secret Manager)
- Secret management (Google Documentation: Secret Manager)
- Build versus runtime secret injection (Google Documentation: Configure secrets, Use secrets from Secret Manager)
2.4 Securing the CI/CD deployment pipeline. Considerations include:
- Vulnerability analysis with Artifact Registry Artifact analysis and vulnerability scanning)
- Binary Authorization (Google Documentation: Binary Authorization)
- IAM policies per environment
Section 3: Applying site reliability engineering practices to a service (23%)
3.1 Balancing change, velocity, and reliability of the service. Considerations include:
- Discovering SLIs (e.g., availability, latency) (Google Documentation: Choose your service level indicators (SLIs))
- Defining SLOs and understanding SLAs (Google Documentation: SRE fundamentals: SLIs, SLAs and SLOs)
- Error budgets (Google Documentation: Concepts in service monitoring)
- Toil automation
- Opportunity cost of risk and reliability (e.g., number of “nines”)
3.2 Managing service lifecycle. Considerations include:
- Service management (e.g., introduction of a new service by using a pre-service onboarding checklist, launch plan, or deployment plan, deployment, maintenance, and retirement) (Google Documentation: Google Cloud setup checklist)
- Capacity planning (e.g., quotas and limits management) (Google Documentation: Quotas & limits)
- Autoscaling using managed instance groups, Cloud Run, Cloud Functions, or GKE (Google Documentation: Autoscaling groups of instances)
- Implementing feedback loops to improve a service (Google Documentation: Feedback prebuilt component)
3.3 Ensuring healthy communication and collaboration for operations. Considerations include:
- Preventing burnout (e.g., setting up automation processes to prevent burnout)
- Fostering a culture of learning and blamelessness (Google Documentation: Postmortem Culture: Learning from Failure)
- Establishing joint ownership of services to eliminate team silos (Google Documentation: Guide to Cloud Billing Resource Organization & Access Management)
3.4 Mitigating incident impact on users. Considerations include:
- Communicating during an incident (Google Documentation: Data incident response process)
- Draining/redirecting traffic (Google Documentation: Enable connection draining)
- Adding capacity (Google Documentation: Scale capacity)
3.5 Conducting a postmortem. Considerations include:
- Documenting root causes (Google Documentation: Error Reporting)
- Creating and prioritizing action items
- Communicating the postmortem to stakeholders (Google Documentation: Postmortem Culture: Learning from Failure)
Topic 4: Implementing service monitoring strategies (21%)
4.1 Managing logs:
- Collecting structured and unstructured logs from Compute Engine, GKE, and serverless platforms using Cloud Logging (Google Documentation: About GKE logs, Structured Logging)
- Configuring the Cloud Logging agent (Google Documentation: Configure the Logging agent)
- Collecting logs from outside Google Cloud (Google Documentation: Route logs to supported destinations)
- Sending application logs directly to the Cloud Logging API (Google Documentation: Cloud Logging API)
- Log levels (e.g., info, error, debug, fatal) (Google Documentation: View and write Cloud Function logs)
- Optimizing logs (e.g., multiline logging, exceptions, size, cost) (Google Documentation: Logging query language)
4.2 Managing metrics with Cloud Monitoring. Considerations include:
- Collecting and analyzing application and platform metrics (Google Documentation: Collect metrics overview)
- Collecting networking and service mesh metrics (Google Documentation: Observability overview, Cloud Service Mesh overview)
- Use metric explorer for ad hoc metric analysis (Google Documentation: Metrics Explorer)
- Creating custom metrics from logs (Google Documentation: Log-based metrics overview)
4.3 Managing dashboards and alerts in Cloud Monitoring. Considerations include:
- Creating a monitoring dashboard (Google Documentation: Create and manage custom dashboards)
- Filtering and sharing dashboards (Google Documentation: Share a custom dashboard)
- Configuring alerting
- Defining alerting policies based on SLOs and SLIs (Google Documentation: Creating an alerting policy)
- Automating alerting policy definition using Terraform (Google Documentation: Create alerting policies with Terraform, Manage alerting policies with Terraform)
- Using Google Cloud Managed Service for Prometheus to collect metrics and set up monitoring and alerting (Google Documentation: Google Cloud Managed Service for Prometheus)
4.4 Managing Cloud Logging platform. Considerations include:
- Enabling data access logs (e.g., Cloud Audit Logs) (Google Documentation: Enable Data Access audit logs)
- Enabling VPC Flow Logs (Google Documentation: Use VPC Flow Logs)
- Viewing logs in the Google Cloud console
- Using basic versus advanced log filters (Google Documentation: Logging query language)
- Logs exclusion versus logs export
- Project-level versus organization-level export
- Managing and viewing log exports (Google Documentation: Viewing activity logs)
- Sending logs to an external logging platform (Google Documentation: Route logs to supported destinations)
- Filtering and redacting sensitive data (e.g., personally identifiable information [PII], protected health information [PHI]) (Google Documentation: De-identifying sensitive data)
4.5 Implementing logging and monitoring access controls. Considerations include:
- Restricting access to audit logs and VPC Flow Logs with Cloud Logging (Google Documentation: VPC audit logging information)
- Restricting export configuration with Cloud Logging (Google Documentation: Scenarios for exporting Cloud Logging: Compliance requirements)
- Allowing metric and log writing with Cloud Monitoring (Google Documentation: Log-based metrics overview)
Topic 5: Optimizing service performance (16%)
5.1 Identify service performance issues:
- Using Google Cloud’s operations suite to identify cloud resource utilization (Google Documentation: Observability in Google Cloud)
- Interpret service mesh telemetry (Google Documentation: The service mesh era)
- Troubleshooting issues with compute resources (Google Documentation: Troubleshooting resource availability errors)
- Troubleshooting deploy time and runtime issues with applications (Google Documentation: Troubleshoot Cloud Run issues, Troubleshoot Cloud Functions)
- Troubleshooting network issues (e.g., VPC Flow Logs, firewall logs, latency, network details (Google Documentation: VPC Flow Logs overview, Using VPC Flow Logs, Using Firewall Rules Logging)
5.2 Implementing debugging tools in Google Cloud. Considerations include:
- Application instrumentation (Google Documentation: Cloud Monitoring)
- Cloud Logging (Google Documentation: Cloud Logging)
- Cloud Trace (Google Documentation: Cloud Trace overview)
- Error Reporting (Google Documentation: Error Reporting)
- Cloud Profiler (Google Documentation: Cloud Profiler)
- Cloud Monitoring (Google Documentation: Cloud Monitoring)
5.3 Optimize resource utilization and costs:
- Preemptible/Spot virtual machines (VMs) (Google Documentation: Preemptible VM instances, Spot VMs)
- Committed-use discounts (e.g., flexible, resource-based) (Google Documentation: Resource-based committed use discounts, Committed use discounts)
- Sustained-use discounts (Google Documentation: Sustained use discounts for Compute Engine)
- Network tiers (Google Documentation: Network Service Tiers overview)
- Sizing recommendations
How difficult is Google Professional Cloud DevOps Engineer (GCP) Exam?
Well, certainly we know that it will require a lot of hard work to prepare for Google Professional Cloud DevOps Engineer (GCP) Exam, as it is not a piece of cake to crack. But this also does not mean that it is not possible to crack this exam. This exam might be challenging to pass because it covers a wide range of topics, and you have to understand how to apply what you’ve learned.
Further, the difficulty level of the Google Professional Cloud DevOps Engineer (GCP) exam can vary depending on an individual’s prior experience with cloud computing, DevOps practices, and GCP. However, in general, it is considered to be a challenging exam that requires a strong understanding of cloud computing, DevOps practices, and GCP.
To pass the Google Professional Cloud DevOps Engineer exam, you should have a solid understanding of the following topics:
- GCP Services: Knowledge of the various GCP services, including computing, storage, networking, and security.
- DevOps Practices: Knowing about DevOps practices, like continuous integration, continuous delivery, and infrastructure as code, is important.
- Cloud Architecture: Knowledge of cloud architecture concepts, including scalability, availability, and security.
- Monitoring and Logging: Understanding of monitoring and logging techniques, and the use of tools such as Stackdriver and Cloud Logging.
- Application Deployment: Knowledge of application deployment, including containerization and orchestration using Kubernetes.
Let us now look at the preparation resources that you can use to ace the exam. For more details about the exam, you can also visit the online tutorials on Google Professional Cloud DevOps Engineer (GCP) Exam by testpreptraining.com.
Learning resources for GCP Cloud DevOps Engineer Exam
You have access to an infinite number of resources for preparation. It may be challenging to pass this exam on your first try. Yet, if you use the appropriate materials and practice hard, you can pass the test in one sitting. As a result, you should choose your resources carefully. You can choose from offline classes, online classes, sample tests, manuals, online discussion boards, books, and other resources. Simply select the set that seems the most comfortable to you. Let’s examine a few tools that may be utilized in conjunction with the Google Professional Cloud Devops Engineer Study Guide to ace the test.
Review the Exam Guide
Before you start preparing, make sure you understand the main goals of the Google Professional Cloud DevOps Engineer Exam. Google Cloud Platform (GCP) gives candidates a clear exam guide. Knowing these objectives is crucial for getting a good idea of what the exam will be like. So visit the Official website of GCP, to have a clearer view of the exam guide.
Online classes and instructor-led training courses
First off, the Google Professional Cloud Devops Engineer Training is offered as instructor-led courses and online seminars. These are among the most engaging methods of exam preparation. Numerous trustworthy websites provide really wonderful teachers and top-notch preparation materials. As most of us are used to learning in a classroom, online programs can act as a near alternative with the benefit of being available anywhere.
Join study groups or communities
Joining a study group or community of other individuals preparing for the GCP DevOps Engineer exam can provide valuable insights and support as you prepare for the exam.
Stay up-to-date with GCP updates
Keep yourself informed about the latest changes and updates in Google Cloud Platform (GCP), as it is always evolving. Read the GCP blog regularly and attend webinars or conferences to stay up-to-date.
Evaluate with Practice Test
Your study skills have a big role in how well you perform on the test. Take as many practice tests and exam series for Google Professional Cloud Devops Engineer as you can. These will aid you in assessing your degree of preparedness, locating any gaps, and pinpointing the areas that require additional attention. There are several trustworthy educational websites that offer fantastic knowledge and support your pursuit of greatness. Try a free practice test now!
Expert Corner
It is very essential to build your own strategy for studying. Additionally, sort the topics into those that need conceptual understanding and those with theoretical aspects. Emphasize gaining hands-on experience. Consult various sources for challenging parts of the exam. Establish a study schedule and minimize distractions. Create concise revision notes and schedule periodic practice tests. Stick to your plan and execute it as intended. Successfully implementing your strategy is crucial for passing the exam.
The Google Cloud DevOps Engineer Exam is worth a try. If you clear the exam you will get a way to get yourself recognized globally. This is a step forward to getting the dream job. With the right set of resources, you will surely crack the exam.
