Professional Cloud Architect Part 2: AI, Security, & Ops Specialization

Master AI, Security, & Monitoring on Google Cloud.

Architect secure, automated, and observable cloud solutions with AI and GKE.

Instructor: Google Cloud Training

Access provided by Vishwakarma Intitutes

9 course series

Get in-depth knowledge of a subject

from 2,925 reviews of courses in this program

Advanced level

Recommended experience

2 months to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

9 course series

Get in-depth knowledge of a subject

from 2,925 reviews of courses in this program

Advanced level

Recommended experience

2 months to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Automate infrastructure provisioning and manage reusable configurations using Terraform modules and state.
Implement advanced security controls, including Cloud IAM, VPC Service Controls, and threat detection with Cloud IDS.
Architect and scale containerized applications using GKE Fleets, Cloud Service Mesh, and serverless Cloud Run environments.
Integrate AI/ML pipelines via Vertex AI and implement full-stack observability with Logging, Monitoring, and Trace.

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Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from Google Cloud

Specialization - 9 course series

This learning path explores the advanced pillars of the Google Cloud Professional Cloud Architect certification. It covers infrastructure automation with Terraform, comprehensive security management, and scaling modern workloads with GKE and Cloud Run. You will also learn to integrate AI/ML and data engineering capabilities while mastering the observability tools required to ensure enterprise-grade reliability.

Applied Learning Project

Learners will engage in advanced hands-on labs, such as building remote Terraform backends and configuring Cloud Service Mesh for microservices. You will solve authentic architectural problems by implementing least-privilege security policies in Cloud Run, building streaming data pipelines, and using Cloud Trace to analyze and resolve application latency in production.

Getting Started with Terraform for Google Cloud

Course 1, 6 hours

What you'll learn

Define the business need for infrastructure as Code and the benefits of using it in your environment.
Explain the features and functionalities of Terraform.
Use Terraform resources, variables, and output values to create Google Cloud infrastructure resources.
Use Terraform modules to build reusable configurations.

Managing Security in Google Cloud

Course 2, 8 hours

What you'll learn

Identify the foundations of Google Cloud security.
Manage administration identities with Google Cloud.
Implement user administration with Identity and Access Management (IAM).
Configure Virtual Private Clouds (VPCs) for isolation, security, and logging.

Manage Scalable Workloads in GKE

Course 3, 22 hours

What you'll learn

Describe the challenges of designing a multi-cluster infrastructure.
Describe the components and architecture of GKE Fleets
Identify and describe the core components of a GKE fleet.
Create, connect, and manage GKE clusters from multiple deployment environments.

Developing Applications with Cloud Run on Google Cloud: Fundamentals

Course 4, 5 hours

What you'll learn

Understand the fundamentals of Cloud Run that include the resource model, container lifecycle, and autoscaling.
Develop and test applications locally before deploying to Cloud Run.
Use service identity and IAM with Cloud Run.
Integrate Cloud Run applications with Google Cloud services.

Introduction to Data Engineering on Google Cloud

Course 5, 9 hours

What you'll learn

Understand the role of a data engineer.
Identify data engineering tasks and core components used on Google Cloud.
Understand how to create and deploy data pipelines of varying patterns on Google Cloud.
Identify and utilize various automation techniques on Google Cloud.

Introduction to AI and Machine Learning on Google Cloud

Course 6, 9 hours

What you'll learn

Recognize the data-to-AI technologies and tools offered by Google Cloud.
Use generative AI capabilities in applications.
Choose between different options to develop an AI project on Google Cloud.
Build ML models end-to-end by using Vertex AI.

Logging and Monitoring in Google Cloud

Course 7, 14 hours

What you'll learn

Explain the purpose and capabilities of Google Cloud Observability.
Implement monitoring for multiple cloud projects.
Create effective monitoring dashboards and alerts. Create alerting policies, uptime checks and alerts.
Explain how to collect logs using Cloud Logging and export for further analysis.

Observability in Google Cloud

Course 8, 11 hours

What you'll learn

Install and manage Ops Agent to collect logs for Compute Engine.
Explain Cloud Operations for GKE.
Analyze VPC Flow Logs and firewall rules logs.
Analyze resource utilization cost for monitoring related components within Google Cloud.

Preparing for your Professional Cloud Architect Journey

Course 9, 6 hours

What you'll learn

List the five domains covered on the Professional Cloud Architect certification exam.
Identify gaps in your knowledge and skills for each domain and create a study plan.