Performance optimization in GCP - Mini Project: Build & Apply

Performance Optimization in Google Cloud Platform

📖 Scenario: You are managing a web application hosted on Google Cloud Platform (GCP). The application is experiencing slow response times during peak hours. To improve user experience, you want to optimize the performance by configuring autoscaling and load balancing.

🎯 Goal: Build a simple Google Cloud configuration that sets up an instance group with autoscaling enabled and a load balancer to distribute traffic evenly.

📋 What You'll Learn

Create a managed instance group with 3 instances

Set autoscaling to increase instances when CPU usage exceeds 60%

Configure a load balancer to distribute traffic to the instance group

💡 Why This Matters

🌍 Real World

Web applications often face varying traffic loads. Autoscaling and load balancing help maintain fast response times and availability during traffic spikes.

💼 Career

Cloud engineers and DevOps professionals use these configurations daily to optimize cloud infrastructure performance and cost.

1

Create a managed instance group

Create a managed instance group called web-instance-group with 3 instances using the template web-instance-template.

GCP

# Your code here to create a managed instance group with 3 instances

Need a hint?

Use the google_compute_instance_group_manager resource with target_size = 3.

2

Add autoscaling configuration

Add an autoscaler called web-autoscaler for the instance group web-instance-group that increases instances when CPU utilization exceeds 0.6 (60%).

GCP

resource "google_compute_instance_group_manager" "web_instance_group" {
  name               = "web-instance-group"
  base_instance_name  = "web-instance"
  instance_template   = "web-instance-template"
  target_size         = 3
  zone                = "us-central1-a"
}

# Your code here to add autoscaling for CPU utilization > 0.6

Need a hint?

Use the google_compute_autoscaler resource linked to the instance group with cpu_utilization.target = 0.6.

3

Configure a load balancer backend service

Create a backend service called web-backend-service that uses the instance group web-instance-group as its backend.

GCP

resource "google_compute_instance_group_manager" "web_instance_group" {
  ...
}

resource "google_compute_autoscaler" "web_autoscaler" {
  ...
}

# Your code here to create a backend service using the instance group

Need a hint?

Use google_compute_backend_service with the instance group as backend.

4

Create a HTTP load balancer frontend

Create a global forwarding rule called web-forwarding-rule that listens on port 80 and forwards traffic to the backend service web-backend-service.

GCP

resource "google_compute_instance_group_manager" "web_instance_group" {
  ...
}

resource "google_compute_autoscaler" "web_autoscaler" {
  ...
}

resource "google_compute_backend_service" "web_backend_service" {
  ...
}

# Your code here to create a global forwarding rule on port 80

Need a hint?

Use google_compute_global_forwarding_rule with port_range = "80" and target the backend service.