The Google Professional Cloud DevOps Engineer certification is a professional-level certification offered by Google Cloud Platform (GCP) that validates an individual’s ability to design, develop, and manage GCP-based solutions for continuous integration and delivery. This certification is designed for DevOps experts with experience in using GCP (Google Cloud Platform) tools to apply DevOps methods such as Continuous Integration (CI) and Continuous Deployment (CD) pipelines, automating infrastructure, keeping an eye on performance, and recording system activities.
Having a cheat sheet for the Google Professional Cloud DevOps Engineer certification is crucial because it can help candidates to quickly review and refresh their memory on key concepts, tools, and best practices covered in the certification exam. This can save time and increase their chances of passing the exam on the first attempt. Additionally, a cheat sheet can be used as a quick reference guide for DevOps professionals who are working with GCP on a daily basis.
Firstly, let’s get a quick overview of Professional Cloud DevOps engineers.
Google Professional Cloud DevOps Engineer Exam
The development operations for services that can balance service dependability and delivery speed are handled by Google Cloud Platform Professional Cloud Devops Engineers. They are adept in managing problems, deploying and monitoring services, and creating software delivery pipelines using the Google Cloud Platform. The Cloud DevOps Engineer Exam’s primary objective is to evaluate a professional’s ability to implement the strategies of the cloud platform. In order to construct software delivery pipelines, deploy and monitor services, manage issues, and learn from them, you need to master the use of the Google Cloud Platform.
Next, there are skills that the exam will validates as per the skills and abilities you have. This will also help you to review the skills so that you are not left with any of it.
Skills Validated:
The Google Professional Cloud DevOps Engineer certification validates skills and expertise in designing, building, and managing robust, scalable, and highly available cloud-based solutions on Google Cloud Platform (GCP). Some of the key skills that are validated by this certification include:
- Knowledge of DevOps principles and practices: Applicants need to show they know about DevOps ideas and techniques, like continuous integration and continuous delivery (CI/CD), turning infrastructure into code (IaC), watching and recording what’s happening in systems.
- Proficiency in GCP services: Candidates must have a deep understanding of various GCP services, including Compute Engine, Kubernetes Engine, Cloud Storage, Cloud SQL, Cloud Spanner, and BigQuery, among others.
- Experience with automation and scripting: Candidates must have experience with automation and scripting using tools like Terraform, Ansible, and Python.
- Knowledge of security and compliance: Candidates should possess a solid grasp of cloud security and compliance best practices, covering areas such as managing access, safeguarding networks, and ensuring the security of data.
- Experience with containerization and orchestration: Candidates must have experience with containerization technologies like Docker and Kubernetes, and the ability to design and deploy containerized applications on GCP.
- Expertise in troubleshooting and incident management: Candidates must have the ability to troubleshoot complex issues and incidents in cloud-based environments, and implement effective incident management processes.
Quick Cheat Sheet for Google Professional Cloud DevOps Engineer Exam
The greatest exam preparation tools must be used if you want to pass any certification exam. Also, it is crucial to thoroughly review everything in preparation for the Google Professional Cloud DevOps Engineer Test as you move toward a fruitful and fulfilling career on the Google cloud platform. Now let’s start with the planning.
Getting familiar with exam topics
Understanding and getting familiar with the main objectives of the Google Professional Cloud DevOps Engineer Exam is very important. Knowing the exam objectives will provide you an insight into the exam. Moreover, a thorough analysis of the exam guide will let you align yourself more deeply with the major objectives of the exam. And, you will also be able to review and mark the sections and topics you find difficult. However, the topics that are included in the Google Professional Cloud Devops Engineer Course are provided below:
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
Get Familiar With Exam Terms
some of the key terminology used in the context of Google Professional Cloud DevOps Engineer:
- DevOps: DevOps involves a collection of methods that blend software development (Dev) with IT operations (Ops) to boost an organization’s capacity to deliver applications and services quickly.
- Continuous Integration (CI): Continuous Integration (CI) is a method in which developers merge their code updates into a central repository, and the system automatically builds, tests, and confirms the code.
- Continuous Delivery (CD): CD is a practice where code changes are automatically built, tested, and prepared for release to production.
- Infrastructure as Code (IaC): IaC is a practice where infrastructure is managed through code, allowing for faster, more consistent, and more reliable provisioning and management of resources.
- Deployment Manager: Deployment Manager is a Google Cloud service that allows you to create and manage Google Cloud resources through templates.
- Kubernetes: Kubernetes is a widely used open-source system for orchestrating containers, automating the deployment, scaling, and control of applications packaged in containers.
- Istio: Istio is an open-source service mesh platform that provides traffic management, security, and observability features for microservices-based applications.
- Terraform: Terraform is a popular open-source tool for building, changing, and versioning infrastructure safely and efficiently.
- Jenkins: Jenkins is a popular open-source CI/CD tool that automates the building, testing, and deployment of software.
- Prometheus: Prometheus is a free and open-source monitoring system that gathers metrics from the things it’s keeping an eye on and saves them in a time-based database.
Google Professional Cloud Devops Engineer Training
You must know that GCP provides training sources to help you gain knowledge and skills for clearing the exam. So, let’s know about it.
Site Reliability Engineering: Measuring and Managing Reliability
This course, which covers the Service Level Objectives (SLOs) idea, is offered by Google Cloud Platform. You will receive training on how to describe and assess the intended level of service dependability here. This will also explain how to put these ideas into practice while creating the first service level objectives. Moreover, it will instruct you on how to calculate reliability and error budgets using service level indicators (SLIs). The process of making systems dependable, SLIs, SLOs, and SLAs, as well as quantifying risks to and effects of SLOs, may all be covered using this.
Books for reference
If you are dedicated to passing the exam then, you must know the importance of books during the time of preparation. This will help you highlight the part of the topic you find difficult or you want to study later. Moreover, it can be helpful in understanding the core of the topics. GCP provides a set of books on Site Reliability Engineering, which will help sharpen your skills.
- Firstly, Building Secure & Reliable Systems: Best Practices for Designing, implementing and Maintaining Systems
- Secondly, The Site Reliability Workbook: Practical ways to implement SRE
- Lastly, Site Reliability Engineering by Oreilly
Gaining Hands-On Practice
Both knowledge and gaining hands-on practice is an ideal way to crack any certification exam. However, for GCP DevOps Engineer Exam, it is recommended to join hands-on labs that are available on Qwiklabs. And, also the GCP free tier to elevate your proficiency in the cloud platform. The platform includes:
DevOps Essentials – Firstly, this quest will allow you to gain an understanding of the use of Google Cloud. Moreover, with the help of Google Cloud, you will be able to enhance your software delivery capability in parameters like – speed, stability, availability, and security.
Google Cloud Free Tier – Through this platform, GCP provides you with free resources to gain a deeper knowledge of Google Cloud services, by allowing you to get enough practice. Moreover, Google Cloud Free Tier covers the requirements of professionals at different levels – beginners, and experienced professionals.
Evaluate yourself with Practice Exam
Using a Google Professional Cloud DevOps Engineer Practice Test is a great way to evaluate how well you’ve been studying and ensure you do your best on the real exam. It helps you identify where you need to improve. Additionally, practicing with these tests before the Google Cloud DevOps Engineer sample exam will help you become more familiar with the question format and how well you can answer them.
