Architecting with Google Compute Engine

(3 days)

This three-day instructor-led class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.

Objectives

This course teaches participants the following skills:

• Consider the entire range of Google Cloud Platform technologies in their plans
• Learn methods to develop, implement, and deploy solutions
• Distinguish between features of similar or related products and 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 that are used to implement security, scalability, high availability, and other desired qualities

Audience

This class is intended for experienced developers who are responsible for managing big data transformations including:

• Cloud Solutions Architects, Systems Operations professionals, DevOps Engineers, IT managers
• Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform

Prerequisites

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

• Completed Google Cloud Platform Fundamentals or have equivalent experience
• Basic proficiency with command-line tools and Linux operating system environments
• Systems Operations experience including deploying and managing applications, either on-premises or in a public cloud environment

Course Outline

Module 1: Introduction to Google Cloud Platform

• Role of the Cloud Architect
• Learn about Solution Domains as an approach to design
• Lab: Console and Cloudshell
• Lab: Projects
• Lab: Infrastructure Preview

Module 2: Virtual Networks

• Cloud Virtual Networks (CVN), Projects, Networks, Subnetworks, IP addresses, Routes, Firewall rules
• Subnetworks for resource management instead of physical network topology
• Lab: Virtual Networking
• Lab: Bastion Host

Module 3: Virtual Machines

• GCE, tags, VM options, vCPUs, disk options, images, and special features of persistent disks for VMs
• Lab: Creating Virtual Machines
• Lab: Working with Virtual Machines

Module 4: Cloud IAM

• Members, roles, organizations, account administration, service accounts
• Lab: Cloud IAM

Module 5: Data Storage Services

• Cloud Storage, Datastore, Bigtable, Cloud SQL
• Lab: Cloud Storage
• Lab: Cloud SQL
• Lab: Cloud Datastore

Module 6: Resource Management

• Billing, Quotas, Labels, Names, Cloud Resource Manager
• Lab: Billing Administration
• Lab: Examining Billing Data and BigQuery

Module 7: Resource Monitoring

• Stackdriver, Monitoring, Logging, Error Reporting, Tracing, Debugging
• Lab: Resource Monitoring (Stackdriver)
• Lab: Error Reporting and Debugging (Stackdriver)

Module 8: Interconnecting Networks

• VPNs, Cloud Router, Cloud Interconnect, Direct Peering, Cloud DNS
• Lab: Virtual Private Networks (VPN)
• Lab: Dynamic VPN with Cloud Routers

Module 9: Load Balancing

• Network Load Balancing, HTTP(S) Load Balancing, SSL Load Balancing and Internal Load Balancing, Managed Instance Groups
• Lab: VM Automation and Load Balancing

Module 10: Autoscaling

• Autoscaler
• Lab: Autoscaling

Module 11: Infrastructure Automation with Cloud API

• Infrastructure automation, custom images, startup and shutdown scripts and metadata
• Lab: Cloud API Infrastructure Automation

Module 12: Infrastructure Automation with Deployment Manager

• Deployment Manager templates
• Lab: Deployment Manager

Module 13: Managed Services

• Dataproc, Dataflow, BigQuery, Datalab

Module 14: Application Development Infrastructure

• Cloud Pub/Sub, Cloud Endpoints and Apigee, Cloud Functions

Module 15: Application Development Services

• Google App Engine (GAE), Dev Tools, Cloud Source Repos.
• Lab: App Engine Development

Module 16: Containers

• Containers, Google Container Engine (GKE), and Container Registry.
• Lab: Kubernetes Load Balancing

** Notice: Cancellations will be charged an administrative fee through Eventbrite.