In Google Cloud Platform Fundamentals: Core Infrastructure, you will learn
Module 1: Introducing Google Cloud Platform
- Explain the advantages of Google Cloud Platform.
- Define the components of Google’s network infrastructure, including: Points of presence, data centers, regions, and zones.
- Understand the difference between Infrastructure-as-a- Service (IaaS) and Platform-as-a-Service (PaaS).
Module 2: Getting Started with Google Cloud Platform
- Identify the purpose of projects on Google Cloud Platform.
- Understand the purpose of and use cases for Identity and Access Management.
- List the methods of interacting with Google Cloud Platform.
- Lab: Getting Started with Google Cloud Platform.
Module 3: Virtual Machines and Networks in the Cloud
- Identify the purpose of and use cases for Google Compute Engine.
- Understand the various Google Cloud Platform networking and operational tools and services.
- Lab: Compute Engine
Module 4: Storage in the Cloud
- Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore.
- Learn how to choose between the various storage options on Google Cloud Platform.
- Lab: Cloud Storage and Cloud SQL
Module 5: Containers in the Cloud
- Define the concept of a container and identify uses for containers.
- Identify the purpose of and use cases for Google Kubernetes Engine and Kubernetes.
- Lab: Kubernetes Engine
Module 6: Applications in the Cloud
- Understand the purpose of and use cases for Google App Engine.
- Contrast the App Engine Standard environment with the App Engine Flexible environment.
- Understand the purpose of and use cases for Google Cloud Endpoints.
- Lab: App Engine
Module 7: Developing, Deploying, and Monitoring in the Cloud
- Understand options for software developers to host their source code.
- Understand the purpose of template-based creation and management of resources.
- Understand the purpose of integrated monitoring, alerting, and debugging.
- Lab: Deployment Manager and Stackdriver
Module 8: Big Data and Machine Learning in the Cloud
- Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms.
- Lab: BigQuery
In Architecting with Google Cloud Platform: Infrastructure, you will learn
Module 1: Introduction to Google Cloud Platform
- Google Cloud Platform (GCP) Infrastructure
- Using GCP
- Lab: Console and Cloud Shell
- Demo: Projects
- Lab: Infrastructure Preview
Module 2: Virtual Networks
- Virtual Private Cloud (VPC), Projects, Networks, Sub networks, IP addresses, Routes, Firewall rules
- Sub networks for resource management instead of physical network topology
- Lab: Virtual Networking
- Lab: Bastion Host
Module 3: Virtual Machines
- Compute Engine
- Lab: Creating Virtual Machines
- Compute options (vCPU and Memory)
- Common Compute Engine actions
- Lab: Working with Virtual Machines
Module 4: Cloud IAM
- Organizations, Roles, Members, Service accounts, Cloud IAM best practices
- Lab: Cloud IAM
Module 5: Data Storage Services
- Cloud Storage
- Lab: Cloud Storage
- Cloud SQL
- Lab: Cloud SQL
- Cloud Spanner, Cloud Datastore
- Lab: Cloud Datastore
- Cloud Bigtable
Module 6: Resource Management
- Cloud Resource Manager, Quotas, Labels, Names, Billing
- Demo: Billing Administration
- Lab: Examining Billing Data with BigQuery
Module 7: Resource Monitoring
- Stackdriver, Monitoring
- Lab: Resource Monitoring (Stackdriver)
- Logging, Error Reporting, Tracing, Debugging
- Lab: Error Reporting and Debugging (Stackdriver)
Module 8: Interconnecting Networks
- Cloud Virtual Private Network (VPN)
- Lab: Virtual Private Networks (VPN)
- Cloud Router, Cloud Interconnect, External Peering, Cloud DNS
Module 9: Load Balancing
- Managed Instance Groups, HTTPS load balancing, Cross-region and content-based load balancing, SSL proxy/TCP proxy load balancing, Network load balancing
- Lab: VM Automation and Load Balancing
Module 10: Autoscaling
- Autoscaling, Policies, Configuration
- Lab: Autoscaling
Module 11: Infrastructure Automation with Google Cloud Platform APIs
- Infrastructure automation, Images, Metadata, Scripts, Google Cloud API
- Lab: Google Cloud Platform API Infrastructure Automation
Module 12: Infrastructure Automation with Deployment Manager
- Deployment Manager, Configuration, Cloud Launcher
- Lab: Deployment Manager
Module 13: Managed Services
- Cloud Dataproc, Cloud Dataflow, BigQuery, Cloud Datalab
Module 14: Application Infrastructure Services
- Cloud Pub/Sub, API Management, Cloud Functions, Cloud Source Repositories, Specialty APIs
Module 15: Application Development Services
Module 16: Containers
- Containers, Kubernetes Engine, Container Registry
- Lab: Kubernetes Load Balancing
- Kubernetes Engine, App Engine, or Containers on Compute Engine