Architecting with Google Compute Engine Training

Description:

This training provides a detailed exploration of architecting compute solutions using Google Compute Engine (GCE) and related services.

Participants will learn VM lifecycle management, network design, IAM integration, and load balancing configurations.

Hands-on labs cover deploying scalable VMs, securing workloads, and monitoring performance with GCP-native tools.

By the end, learners will be able to design production-ready GCE solutions and align with GCP architect certification requirements.

Duration: 5 Days

Course Code: BDT 523

Learning Objectives:

After this training, participants will be able to:

1. Deploy and manage Compute Engine workloads
2. Architect scalable VPCs
3. Apply IAM and monitoring best practices
4. Design interconnect and load balancing solutions

1. Cloud architects
2. Systems engineers
3. Developers working with GCE

1. Knowledge of cloud computing
2. Linux/Windows administration skills
3. Networking basics

Course Outline:

Module 1: Introduction to GCP

• GCP ecosystem and services
• Global infrastructure (regions, zones, edge)
• IaaS vs PaaS vs SaaS
• Using GCP Console, Cloud SDK, APIs

Module 2: Virtual Networks

• VPCs, subnets, routes, firewall rules
• IP addressing (internal/external)
• VPN, Peering, Interconnect, Cloud Router, Cloud DNS
• Common network design and hybrid connectivity

Module 3: Compute Services

• Compute Engine basics
• VM lifecycle and machine types
• Disk options, images, snapshots
• Instance groups (managed/unmanaged)
• Load balancing basics

Module 4: Identity and Access Management (IAM)

• IAM hierarchy (org, folders, projects)
• Roles and policies (basic, predefined, custom)
• Members and service accounts
• IAM best practices and audit logging

Module 5: Storage and Database Services

• Cloud Storage (classes, lifecycle, signed URLs)
• Cloud SQL basics
• Cloud Spanner
• Datastore / Firestore
• Bigtable, Memorystore (intro)

Module 6: Resource Management

• Projects and resource hierarchy
• Quotas and limits
• Billing accounts, budgets, alerts
• Labels and naming conventions

Module 7: Monitoring and Logging

• Cloud Monitoring: metrics, dashboards, alerts
• Cloud Logging: log explorer, sinks
• Error reporting, tracing, debugging
• Best practices for observability

Module 8: Load Balancing and Autoscaling

• HTTP(S), Network, SSL Proxy load balancing
• Cross-region and content-based load balancing
• Managed instance groups
• Autoscaling policies and configuration

Module 9: Infrastructure Automation

• Infrastructure automation concepts
• Images, metadata, startup scripts
• Using Cloud API and gcloud CLI
• Deployment Manager basics (templates, launcher)
• Intro to Terraform (optional)

Module 10: Managed and Analytics Services

• Dataproc, Dataflow, BigQuery
• Other key managed services in GCP

Module 11: Application & Development Services

• Cloud Pub/Sub
• Cloud Functions (serverless)
• API Management and Gateway
• Cloud Source Repositories
• Specialty APIs

Module 12: Containers and Modern App Platforms

• Containers overview
• Google Kubernetes Engine (GKE)
• Container Registry
• Cloud Run (optional, for serverless containers)

Training material provided: Yes (Digital format)