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
1.1 Designing the overall resource hierarchy for an organization. Considerations include:
- Projects and folders
- Shared networking
- Identity and Access Management (IAM) roles and organization-level policies
- Creating and managing service accounts
1.2 Managing infrastructure as code. Considerations include:
- Infrastructure as code tooling (e.g., Cloud Foundation Toolkit, Config Connector, Terraform, Helm)
- Making infrastructure changes using Google-recommended practices and infrastructure as code blueprints
- Immutable architecture
1.3 Designing a CI/CD architecture stack in Google Cloud, hybrid, and multi-cloud environments. Considerations include:
- CI with Cloud Build
- CD with Google Cloud Deploy
- Widely used third-party tooling (e.g., Jenkins, Git, ArgoCD, Packer)
- Security of CI/CD tooling
1.4 Managing multiple environments (e.g., staging, production). Considerations include:
- Determining the number of environments and their purpose
- Creating environments dynamically for each feature branch with Google Kubernetes Engine (GKE) and Terraform
- Anthos Config Management
Topic 2: Building and implementing CI/CD pipelines for a service
2.1 Designing and managing CI/CD pipelines. Considerations include:
- Immutable artifacts with Container Registry (Google Documentation: Help secure software supply chains on Google Kubernetes Engine, Managing images)
- Artifact management with Artifact Registry
- Deployment to hybrid and multi-cloud environments (e.g., Anthos, GKE)
- CI/CD pipeline triggers
- Testing a new application version in the pipeline
- 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
2.2 Implement CI/CD pipelines:
- Auditing and tracking deployments (e.g., Artifact Registry, Cloud Build, Google Cloud Deploy, Cloud Audit Logs)
- Deployment strategies (e.g., canary, blue/green, rolling, traffic splitting)
- Rollback strategies
- Troubleshooting deployment issues
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: Cloud storage)
- Secret management
- Build versus runtime secret injection
2.4 Secure the deployment pipeline:
- Vulnerability analysis with Container Registry (Google Documentation: Getting vulnerabilities and metadata for images)
- Binary Authorization (Google Documentation: Binary Authorization)
- IAM policies per environment (Google Documentation: Policy)
Section 3: Applying site reliability engineering practices to a service
3.1 Balancing change, velocity, and reliability of the service. Considerations include:
- Discovering SLIs (e.g., availability, latency)
- Defining SLOs and understanding SLAs
- Error budgets
- 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)
- Capacity planning (e.g., quotas and limits management)
- Autoscaling using managed instance groups, Cloud Run, Cloud Functions, or GKE
- Implementing feedback loops to improve a service
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
- Establishing joint ownership of services to eliminate team silos
3.4 Mitigating incident impact on users. Considerations include:
- Communicating during an incident
- Draining/redirecting traffic
- Adding capacity
3.5 Conducting a postmortem. Considerations include:
- Documenting root causes
- Creating and prioritizing action items
- Communicating the postmortem to stakeholders
Topic 4: Implementing service monitoring strategies
4.1 Manage logs:
- Collecting structured and unstructured logs from Compute Engine, GKE, and serverless platforms using Cloud Logging
- Configuring the Cloud Logging agent
- Collecting logs from outside Google Cloud
- Sending application logs directly to the Cloud Logging API
- Log levels (e.g., info, error, debug, fatal)
- Optimizing logs (e.g., multiline logging, exceptions, size, cost)
4.2 Managing metrics with Cloud Monitoring. Considerations include:
- Collecting and analyzing application and platform metrics
- Collecting networking and service mesh metrics
- Use metric explorer for ad hoc metric analysis (Google Documentation: Metrics Explorer)
- Creating custom metrics from logs
4.3 Managing dashboards and alerts in Cloud Monitoring. Considerations include:
- Creating a monitoring dashboard
- Filtering and sharing dashboards
- Configuring alerting
- Defining alerting policies based on SLOs and SLIs
- Automating alerting policy definition using Terraform
- Using Google Cloud Managed Service for Prometheus to collect metrics and set up monitoring and alerting
4.4 Managing Cloud Logging platform. Considerations include:
- Enabling data access logs (e.g., Cloud Audit Logs)
- Enabling VPC Flow Logs
- Viewing logs in the Google Cloud console
- Using basic versus advanced log filters
- Logs exclusion versus logs export
- Project-level versus organization-level export
- Managing and viewing log exports
- Sending logs to an external logging platform
- Filtering and redacting sensitive data (e.g., personally identifiable information [PII], protected health information [PHI])
4.5 Implementing logging and monitoring access controls. Considerations include:
- Restricting access to audit logs and VPC Flow Logs with Cloud Logging
- Restricting export configuration with Cloud Logging
- Allowing metric and log writing with Cloud Monitoring
Topic 5: Optimizing service performance
5.1 Identify service performance issues:
- Using Google Cloud’s operations suite to identify cloud resource utilization
- Interpret service mesh telemetry (Google Documentation: The service mesh era)
- Troubleshooting issues with compute resources
- Troubleshooting deploy time and runtime issues with applications
- 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
- Cloud Trace
- Error Reporting
- Cloud Profiler
- Cloud Monitoring
5.3 Optimize resource utilization and costs:
- Preemptible/Spot virtual machines (VMs)
- Committed-use discounts (e.g., flexible, resource-based)
- Sustained-use discounts
- Network tiers
- 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.
