Architecting with Google Compute Engine (GCE)

This class is intended for the following participants:

• Cloud solution architects, DevOps engineers.
  
• People who use the Google Cloud to create new solutions or to integrate existing systems, application environments and infrastructure with the
• Google Cloud .

This course teaches participants the following skills:

• The full range of Google Cloud technologies in their plans.
  
• Methods to develop and implement solutions.
  
• Distinguishing between product features and similar or related technologies.
  
• Recognize a wide variety of solution domains, use cases, and applications
  
• Develop essential skills for managing and administering solutions
  
• Develop knowledge of solution patterns: methods, technologies, and designs used to implement security, scalability, high availability, and other desired qualities.
   
  

Module 1: Introduction to the Google Cloud

• Google Cloud Platform Infrastructure (GC)
• Use of GC
• Lab: Console and Cloud Shell
• Demo: Projects
• Lab: Preview of the infrastructure

Module 2: Virtual Networks

• Virtual Private Cloud (VPC), Projects, Networking, Subnets, IP Addresses, Routing, Firewall Rules
• Subnets for resource management instead of physical network topology
• Lab: Virtual networks
• Lab: Host of the bastion

Module 3: Virtual Machines

• Calculation engine
• Lab: Creating virtual machines
• Calculation options (vCPU and memory)
• Images
• Common actions of the calculation engine
• Lab: Working with virtual machines
• Essential Cloud Infrastructure: Core Services

Module 4: Cloud IAM

• Organizations, Roles, Members, Service Accounts, Cloud IAM Best Practices
• Lab: Cloud AMI

Module 5: Data Storage Services

• Cloud storage
• Lab: Cloud storage
• SQL Cloud
• Lab: SQL cloud
• Cloud Key, Cloud Datastore
• Lab: Cloud data storage
• Bigtable Cloud

Module 6: Resource Management

• Cloud Resource Manager, Fees, Tags, Names, Billing
• Demo: Billing Administration
• Lab: Examining billing data with BigQuery

Module 7: Resource Monitoring

• Stackdriver, Monitoring
• Lab: Resource monitoring (Stackdriver)
• Logging, error reporting, tracking, debugging
• Lab: Reporting and debugging bugs (Stackdriver)
• Elastic Cloud Infrastructure: Scaling and Automation

Module 8: Interconnection networks

• Cloud Virtual Private Network (VPN)
• Lab: Virtual private networks (VPNs)
• Cloud Router, Cloud Interconnect, External Peering, Cloud DNS

Module 9: Load Balancing

• Managed Instance Groups, HTTPS Load Balancing, Region and Content Based Load Balancing, SSL/TCP Proxy Load Balancing, Network Load Balancing
• Lab: VM automation and load balancing

Module 10: Self-Scale

• Autoscale, Policies, Configuration
• Lab: Self-scaling

Module 11: Automating the Infrastructure with Google Cloud APIs

• Infrastructure Automation, Images, Metadata, Scripting, Google Cloud API
• Lab: Automating the Google Cloud API infrastructure

Module 12: Infrastructure Automation with Deployment Manager

• Deployment Manager, Configuration, Cloud Launcher
• Lab: Implementation manager

Module 13: Managed Services

• Cloud Dataproc, Cloud Dataflow, BigQuery, Cloud Datalab
• Elastic Cloud Infrastructure: Containers and Services

Module 14: Application Infrastructure Services

• Cloud Pub/Sub, API Management, Cloud Source Features, Cloud Source Repositories, Specialized APIs

Module 15: Application Development Services

• Application Engine

Module 16: Containers

• Containers, Engine Kubernetes, Container Registration
• Lab: Kubernetes load balancing
• Kubernetes engine, application or container engine in Compute Engine?

To get the most out of this course, participants should have

• Fundamentals of the Google Cloud or equivalent experience
  
• Basic knowledge of command line tools and Linux operating system environments