Google Cloud Platform Essential Training for Administrators

Explore the Google cloud. Learn how to leverage Google Cloud Platform services—including serverless computing, data storage, and machine learning—for your organization.

Is Google Cloud Platform (GCP) right for your business? Explore the offerings of this leading cloud services provider. This course is designed for IT professionals—architects, network admins, and technology stakeholders—evaluating GCP for their organizations as well as those tasked with getting apps up and running on the Google cloud. Learn how to set up an account and use the console, APIs, Cloud Shell, and other GCP tools. Then explore the core services—serverless computing, data storage, and machine learning—and the developer tools that Google provides for building your own custom solutions. Along the way, instructor Lynn Langit shows how to use GCP to manage virtual machines, Docker containers, Kubernetes clusters, functions, relational data stores, NoSQL data, and more. She also shares practical tips for saving money and planning deployments, and reviews examples of common architectural patterns.

Introduction

• Hosting your application on GCP
• What you should know
• A note about working with cloud services

1. Why Use the Google Cloud?

• Understanding Google Cloud Platform
• Save time and money with GCP
• Autoscale on GCP
• Compliance
• Service categories: Compute, data, and more
• Tools and libraries

2. Getting Started

• Set up Google Cloud Platform account
• Naviagate the Google Cloud Platform console
• Work with projects
• Use APIs
• Use regions and zones
• Understand Google Cloud billing
• Use Google Cloud Security/IAM
• Use integrated Google Cloud console
• Use local Google Cloud

3. Compute

• Google Compute Engine
• Google Cloud Platform Marketplace to set up MySQL
• Google Compute Engine resources
• Google Cloud Functions
• App Engine
• Google Cloud Run
• Kubernetes Engine and GKE applications
• Kubernetes Engine and GKE cluster objects
• Anthos for Kubernetes

4. Storage and Database

• Google Cloud Storage
• Google Cloud SQL
• BigQuery
• GCP Marketplace data sets
• Cloud Bigtable
• Cloud Memorystore
• Cloud Firestore, formerly Cloud Datastore
• Cloud Pub/Sub

5. Machine Learning and Data Movement

• Cloud Dataprep
• Cloud Data Fusion
• Data Studio
• AI Platform and AI Hub
• Jupyter notebooks
• TensorFlow 2.0 in Colab notebooks
• Vision API
• Cloud AutoML Tables
• Data science VM

6. Developer Tools

• Deployment Manager and Marketplace
• Cloud Scheduler and Cloud Tasks
• Cloud Code
• Cloud Logging
• Continuous deployment with Cloud Build

7. Key Architectures

• GCP architecture concepts
• Web single-page and API-based architectures
• Web blog: Managed databases
• Mobile development with AI
• Big data log processing

Conclusion

• Next steps