Preparing for Google Cloud Certification: Cloud DevOps Engineer

Advance your career as a data engineer with this Google Cloud platform certification training and prepare for the industry-recognized Google Cloud Professional DevOps Engineer certification.

In this Google Cloud course, you will practice key job skills using Google Cloud to build software delivery pipelines, deploy and monitor services and manage and learn from incidents. You will learn to apply SRE principles to a service, techniques for monitoring, troubleshooting, improving infrastructure and application performance, and more.

This Google Cloud certification path uses Qwiklabs for practical hands-on experience with concepts thoroughly explained throughout the modules.

Cloud DevOps Engineering

Prepare for the Google Cloud Professional Cloud DevOps Engineer Certification Exam


Learn techniques for monitoring, troubleshooting and improving infrastructure and application performance in Google Cloud guided by principles of SRE


Understand the purpose and intent of the Professional Cloud DevOps Engineer certification and its relationship to other Google Cloud certifications

Professional Certificate Programs enable you to become empowered and successful in every phase of your job!

Dana Baker

Dana Baker, Executive Director of Regional Campuses

"We are committed to developing current and relevant coursework to help transform our next generation of leaders."

Preparing for Google Cloud Certification: Cloud DevOps Engineer

100% Online

Learn on your own schedule

Flexible Schedule

Set and maintain flexible deadlines

Entry Level

No previous experience required

6-Months to Complete

Suggested pace of 10 hours/week; 5 Courses

Preparing for Google Cloud Certification: Cloud DevOps Engineer Professional Certificate Courses

Google Cloud Platform Fundamentals: Core Infrastructure

This course introduces you to important concepts and terminology for working with the Google Cloud Platform (GCP).

By the end of this course, you will be able to:

  • Compare many of the computing and storage services available in Google Cloud Platform, including Google App Engine, Google Compute Engine, Google Kubernetes Engine, Google Cloud Storage, Google Cloud SQL and BigQuery.
  • Learn about important resource and policy management tools, such as the Google Cloud Resource Manager hierarchy and Google Cloud Identity and Access Management.
  • Gain foundational skills for working with GCP through hands-on labs.

Developing a Google SRE Culture

This course is intended for business leaders interested in embracing SRE philosophy.  Operations managers or engineers, software engineers, service managers or product managers may find it interesting as an introduction to SRE.  Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support.

Key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption will be discussed.

By the end of this course, you will be able to:

  • Discuss Google’s view on DevOps philosophy and the relationship between DevOps and SRE.
  • Articulate Google’s technical and cultural fundamentals of SRE and understand the value they can provide to your IT operations.
  • Identify what skills to look for in an SRE and how to train your existing workforce.
  • Assess your organization’s maturity level in adopting SRE and understand how Google can help jumpstart SRE in your organization.

Reliable Google Cloud Infrastructure: Design and Process

Through a combination of presentations, design activities and hands-on labs, you will learn to define and balance business and technical requirements and design Google Cloud deployments that are highly reliable, highly available, secure and cost-effective.

This course requires hands-on experience with the technologies covered in Architecting with Google Compute Engines or Architecting with Google Kubernetes Engines.

By the end of this course, you will be able to:

  • Define application requirements and express as KPIs, SLOs, and SLIs.
  • Build microservice applications and architect cloud and hybrid networks.
  • Choose appropriate Google Cloud storage and deployment services.
  • Secure cloud applications, data, and infrastructure, and monitor service levels.

Logging, Monitoring and Observability in Google Cloud

Learn how to monitor, troubleshoot, and improve your infrastructure and application performance. Guided by the principles of site reliability engineering (SRE), this course features a combination of lectures, demos, hands-on labs and real-world case studies.

In this course, you will gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, and profiling CPU and memory usage.

It is strongly recommended that you’ve taken the prior courses in this program, or already have knowledge of Python and Linux so that you can follow along with the troubleshooting examples.

By the end of this course, you will be able to:

  • Plan and implement a well-architected logging and monitoring infrastructure.
  • Define service level indicators (SLIs) and service level objectives (SLOs).
  • Create effective monitoring dashboards and alerts.
  • Monitor, troubleshoot and improve Google Cloud infrastructure.

Getting Started with Google Kubernetes

In this course, which includes hands-on labs, you will build on your ability to interact with GKE. You will be introduced to a range of Google Cloud services and features, to help you choose the right Google Cloud services to create your own cloud solution. You’ll learn about creating a container using Cloud Build and store a container in Container Registry. You will compare the features of Kubernetes and Google Kubernetes Engine, also referred to as GKE. In addition to conceptualizing the Kubernetes architecture, you’ll deploy a Kubernetes cluster using GKE, deploy Pods to a GKE cluster, and view and manage Kubernetes objects.

By the end of this course, you will be able to:

  • Understand the difference among Google Cloud compute platforms.
  • Understand the components and architecture of Kubernetes.
  • Store container images in Container Registry.
  • Understand the components that are used to manage Kubernetes workloads.

Skills you will gain: