Infrastructure & Automation
Build and run the platform. Compute, GKE, Terraform, observability and FinOps — the day-one architecture and the day-two operations that follow it.
11 courses
AI Infrastructure Essentials
This course provides a foundational overview of the hardware, software, and networking components required to develop and manage AI models at scale. It explores Google Cloud's AI Hypercomputer architecture, compares compute accelerators like GPUs and TPUs, and examines the critical data pipelines and storage solutions necessary to maximize training performance. It is designed for IT decision-makers and infrastructure architects seeking to understand enterprise-grade AI deployment.
Application Development with Cloud Run
This course introduces you to the fundamentals, practices, capabilities and tools for modern cloud application development with Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you learn how to develop and deploy applications on Google Cloud by using Cloud Run. This version of the course consists of three separate courses that include topics on creating containers, developing applications with Cloud Run, and Cloud Run functions.
Architecting with Google Cloud: Design and Process
This course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective. This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course.
Architecting with Google Compute Engine
This course will familiarize you with Google Cloud's flexible infrastructure and platform services, with a specific focus on Compute Engine. This course uses a combination of lectures, demos, and hands-on labs to explore and deploy solution elements, including infrastructure components like networks, systems, and application services. You'll also learn how to deploy practical solutions such as hybrid networking, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
Architecting with Google Kubernetes Engine
Learn how to deploy and manage containerized applications on Google Kubernetes Engine (GKE). Learn how to use other tools on Google Cloud that interact with GKE deployments. This course features a combination of lectures, demos, and hands-on labs to help you explore and deploy solution elements-including infrastructure components like pods, containers, deployments, and services-along with networks and application services. You'll also learn how to deploy practical solutions, including security and access management, resource management, and resource monitoring.
Essentials of Monitoring Critical Systems
This course provides an overview of Google Cloud Monitoring. Participants will learn to monitor across multiple projects, build insightful dashboards, and create uptime checks for resource availability. They will explore querying with Prometheus Query Language (PromQL) for advanced analysis and learn how to enhance observability using the AI-powered capabilities of Google Cloud Gemini.
Getting Started with Google Kubernetes Engine
This course covers an introduction to Kubernetes, a software layer that sits between your applications and your hardware infrastructure. Google Kubernetes Engine (GKE) brings you Kubernetes as a managed service on Google Cloud. This course teaches the basics of GKE and how to get applications containerized and running in Google Cloud. The course covers a basic introduction to Google Cloud, an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.
Getting Started with Terraform for Google Cloud
This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as a code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building Google Cloud resources using Terraform.
Google Cloud Infrastructure for Azure Professionals
This is a course for cloud architects and engineers with existing Azure knowledge that compares Google Cloud solutions with Azure and guides professionals on their use. In this course, you'll apply the concepts and technologies knowledge in Azure to explore the similarities and differences with concepts and technologies in Google Cloud. You'll get hands-on practice building and managing Google Cloud resources.
Logging, Monitoring, and Observability in Google Cloud
This course teaches participants techniques for monitoring and improving infrastructure and application performance in Google Cloud. Using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.
Manage Scalable Workloads in GKE Enterprise
Discover how to modernize, manage, and observe applications at scale using Google Kubernetes Engine. This course uses lectures and hands-on labs to help you explore and deploy using Google Kubernetes Engine (GKE), GKE fleets, Cloud Service Mesh, and config controller capabilities that will enable you to work with modern applications, even when they are split among multiple clusters hosted by multiple providers.
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