Course Description

The Architecting with Google Compute Engine (AGCE) course is designed to provide individuals with the knowledge and skills necessary to design scalable and highly available solutions using Google Compute Engine (GCE), a core infrastructure service on the Google Cloud Platform (GCP). This course focuses on architectural principles, best practices, and hands-on experience to enable participants to build robust and efficient solutions on GCE.

Prerequisites

To enroll in the AGCE course, participants should have a strong understanding of cloud computing concepts and familiarity with GCP fundamentals. Prior experience with designing and deploying applications on GCP or other cloud platforms is recommended. Participants should also have a basic understanding of networking, storage, and compute concepts.

Methodology

The AGCE course follows a blended learning approach, combining theoretical instruction, demonstrations, discussions, and hands-on labs. Participants will engage in instructor-led sessions where architectural principles and best practices for GCE are explained. They will also have access to GCE resources and tools to gain practical experience in designing and implementing solutions. The course encourages active participation, discussions, and collaborative problem-solving to reinforce learning.

Course Outline

Introduction to Google Compute Engine (GCE)

Overview of GCE and its key features

Understanding GCE’s infrastructure and regional availability

Exploring GCE’s networking and storage options

Designing Compute Resources in GCE

Choosing appropriate machine types and sizes for workloads

Utilizing preemptible VMs for cost optimization

Designing for high availability and auto scaling

Networking and Load Balancing in GCE

Configuring VPC networks, subnets, and firewall rules

Implementing internal and external load balancing

Designing network architectures for scalability and fault tolerance

Storage and Data Management in GCE

Utilizing persistent disks and local SSDs for storage

Designing for data redundancy and backup strategies

Utilizing Cloud Storage and Cloud Filestore for file storage

Securing and Managing GCE Resources

Implementing identity and access management (IAM) for resource security

Managing and securing SSH access to GCE instances

Automating resource management with instance templates and managed instance groups

Optimizing Performance and Cost in GCE

Monitoring and optimizing resource utilization

Implementing caching and content delivery strategies

Utilizing managed instance groups for autoscaling and cost optimization

Outcome

By the end of the AGCE course, participants will have:

• Developed a comprehensive understanding of architectural principles and best practices for designing solutions on GCE
• Acquired practical knowledge in designing and implementing compute resources, networking, storage, and security in GCE
• Gained expertise in optimizing performance and cost efficiency in GCE environments
• Learned techniques for managing and automating GCE resources effectively
• Gained hands-on experience through practical labs and exercises
• Prepared to design scalable and highly available solutions using GCE on the GCP platform

Labs

The AGCE course includes hands-on labs that provide participants with practical experience in designing and implementing solutions using GCE. Some examples of lab exercises include:

• Creating and configuring GCE instances with appropriate machine types and sizes
• Configuring VPC networks, subnets, and firewall rules
• Implementing internal and external load balancing for GCE instances
• Configuring persistent disks and local SSDs for storage
• Implementing identity and access management (IAM) for resource security
• Monitoring and optimizing resource utilization in GCE

These labs enable participants to apply the concepts learned in the course and gain hands-on experience in designing and implementing solutions using GCE, allowing them to develop practical skills as architects in the GCP environment.