May 8, 2025

Best Google Cloud Platform Project Ideas for Beginners [With Source Code]

Are you a complete beginner ready to explore Google Cloud Platform? Learning to work on practical GCP projects is the best way to start your journey into cloud computing and modern infrastructure management.

Here is a list of beginner-friendly GCP projects that will help you gain hands-on experience, develop essential cloud skills, and boost your professional profile.

10 Beginner-Friendly Google Cloud Platform Project Ideas – Overview

Here’s an overview of the 10 best Google Cloud Platform Project Ideas for beginners:

S.No.	Project Title	Complexity	Estimated Time	Source Code
1	Deploy a Static Website Using GCP Storage	Easy	2–3 hours	Get Started
2	Set Up a Virtual Machine on Compute Engine	Easy	3 hours	Get Started
3	Use GCP Cloud Shell for Basic Automation	Easy	2 hours	Get Started
4	Cloud Functions for Image Resizing	Easy	4 hours	Get Started
5	Build a Simple Contact Form with Firebase	Easy	4 hours	Get Started
6	Deploy a Dockerized App to Cloud Run	Medium	5 hours	Get Started
7	Sentiment Analysis Using AutoML	Medium	6 hours	Get Started
8	Build a Real-Time Chat App with Firebase	Medium	6 hours	Get Started
9	Data Pipeline with Pub/Sub + Dataflow	Hard	8 hours	Get Started
10	Deploy ML Model on AI Platform	Hard	7 hours	Get Started

Top 10 Google Cloud Platform Project Ideas for Beginners

Here are the top 10 Google Cloud Platform project ideas for beginners.

1. Deploy a Static Website Using GCP Storage

This is one of the Google Cloud Platform mini projects that involves hosting a static HTML/CSS website on Google Cloud Storage as a cost-effective and scalable solution.

You will learn the fundamentals of GCP bucket management, permissions, and static web deployment.

Duration: 2–3 hours

Project Complexity: Easy

Key Concepts Covered:

Cloud Storage Buckets
Website Hosting
IAM Permissions

Implementation Steps:

Create a GCP project and enable billing.
Set up a Cloud Storage bucket and make it public.
Upload HTML/CSS files to the bucket.
Configure the bucket for static website hosting.
Access the site via the public URL.

Required Pre-requisites:

Basic HTML/CSS knowledge
GCP account setup
Familiarity with the cloud dashboard

Resources Required:

GCP Free Tier
Static HTML/CSS files
Internet browser

Real-World Application:

Hosting portfolio websites
Deploying documentation or landing pages

Get Started

2. Set Up a Virtual Machine on Compute Engine

This is one of the Google Cloud Platform project ideas for beginner projects that guides you through creating and managing a virtual machine (VM) instance using Google Compute Engine.

You will gain hands-on experience with virtualized infrastructure, SSH access, and basic VM administration in GCP.

Duration: 3 hours

Project Complexity: Easy

Key Concepts Covered:

Compute Engine
VM Configuration
SSH Access

Implementation Steps:

Create a new GCP project and enable Compute Engine API.
Launch a VM instance with predefined specs.
Set up firewall rules and SSH access.
Connect to the VM via Cloud Console or SSH.
Install and run basic software (e.g., a web server).

Required Pre-requisites:

GCP account setup
Basic Linux/terminal knowledge
Understanding of cloud basics

Resources Required:

GCP Free Tier
Web browser
Terminal (optional)

Real-World Application:

Hosting lightweight web applications
Testing server environments and configurations

Get Started

3. Use GCP Cloud Shell for Basic Automation

This project introduces you to automating simple tasks using GCP Cloud Shell and command-line tools.

You will learn how to manage cloud resources, write shell scripts, and use CLI tools efficiently in Google Cloud.

Duration: 2 hours

Project Complexity: Easy

Key Concepts Covered:

Cloud Shell Environment
Bash Scripting
gcloud CLI

Implementation Steps:

Launch Cloud Shell from the GCP Console.
Explore the pre-installed tools and environment.
Write a bash script to automate resource creation (e.g., buckets, folders).
Run and debug the script inside Cloud Shell.
Use version control with Git integration (optional).

Required Pre-requisites:

Basic shell scripting knowledge
GCP account
Familiarity with terminal commands

Resources Required:

GCP Cloud Shell
Bash script file
Cloud Console access

Real-World Application:

Automating repetitive cloud tasks
Managing cloud infrastructure through scripts

Get Started

4. Cloud Functions for Image Resizing

This is one of the Google Cloud Platform projects that involves creating a serverless function to automatically resize images uploaded to a Cloud Storage bucket.

You will learn about event-driven architecture, serverless deployments, and cloud-native automation using GCP.

Duration: 4 hours

Project Complexity: Easy

Key Concepts Covered:

Cloud Functions
Event-driven Triggers
Image Processing

Implementation Steps:

Create a Cloud Storage bucket and upload sample images.
Write a Cloud Function to process and resize images using a library like Sharp.
Set up triggers to invoke the function when uploading files.
Deploy the function using gcloud CLI or console.
Verify that the images have been resized in the output bucket or directory.

Required Pre-requisites:

GCP account
Basic Node.js or Python knowledge
Understanding of Cloud Functions

Resources Required:

GCP Free Tier
Cloud Storage
Code editor (Cloud Shell or local)

Real-World Application:

Automating image optimization workflows
Preprocessing media for web or mobile apps

Get Started

5. Build a Simple Contact Form with Firebase

This project guides you in building a contact form that captures and stores user input in Firebase Firestore.

You will learn how to integrate Firebase services for real-time data storage and front-end interaction in GCP.

Duration: 4 hours

Project Complexity: Easy

Key Concepts Covered:

Firebase Firestore
Real-time Data Handling
Firebase Hosting

Implementation Steps:

Create a Firebase project and set up Firestore.
Build a simple HTML contact form with input fields.
Connect the form to Firestore using the Firebase SDK.
Add validation and form submission logic.
Host the form using Firebase Hosting.

Required Pre-requisites:

Basic HTML/CSS/JS knowledge
Firebase account
Understanding of client-side scripting

Resources Required:

Firebase Console
HTML/CSS/JS files
Firebase SDK

Real-World Application:

Collecting user feedback or inquiries
Building dynamic forms for websites or apps

Get Started

6. Deploy a Dockerized App to Cloud Run

This project involves containerizing a simple web application using Docker and deploying it to GCP’s fully managed Cloud Run service.

You will learn how to use Docker with GCP, build container images, and manage scalable, serverless deployments.

Duration: 5 hours

Project Complexity: Medium

Key Concepts Covered:

Docker Containerization
Cloud Run Deployment
CI/CD Integration

Implementation Steps:

Create a simple app using Node.js, Python, or another language.
Write a Dockerfile and build the image locally or using Cloud Build.
Push the image to Google Container Registry or Artifact Registry.
Deploy the image to Cloud Run via CLI or console.
Test and access the app using the auto-generated URL.

Required Pre-requisites:

Basic Docker knowledge
GCP account with billing enabled
Familiarity with a programming language

Resources Required:

Docker
Cloud SDK (gcloud)
Source code for the app

Real-World Application:

Deploying scalable microservices
Hosting containerized APIs or web apps

Get Started

7. Sentiment Analysis Using AutoML

This project focuses on training a custom sentiment analysis model using Google Cloud AutoML Natural Language.

You will learn how to prepare datasets, train models, and analyze textual sentiment with GCP’s no-code ML tools.

Duration: 6 hours

Project Complexity: Medium

Key Concepts Covered:

AutoML Natural Language
Dataset Preparation
Model Evaluation

Implementation Steps:

Create a dataset of text samples labeled by sentiment (positive, neutral, negative).
Upload and import the dataset to AutoML Natural Language.
Train the model using GCP’s UI-based training process.
Evaluate the model using the built-in metrics.
Use the model to predict sentiment from new text.

Required Pre-requisites:

GCP account with billing
Understanding of text classification
Familiarity with CSV formatting

Resources Required:

AutoML Natural Language
Labeled dataset
GCP Console

Real-World Application:

Analyzing customer reviews or feedback
Automating social media sentiment monitoring

Get Started

8. Build a Real-Time Chat App with Firebase

This project teaches you how to develop a real-time chat application using Firebase Realtime Database and Authentication.

You will learn about live data syncing, user authentication, and front-end integration in Google Cloud’s Firebase platform.

Duration: 6 hours

Project Complexity: Medium

Key Concepts Covered:

Realtime Database
Firebase Auth
Live UI Updates

Implementation Steps:

Set up a Firebase project with Realtime Database and Authentication.
Build a basic chat UI with HTML/CSS/JS.
Enable user sign-up/sign-in with Firebase Auth.
Connect the chat UI to the database for sending/receiving messages.
Implement message ordering and live sync.

Required Pre-requisites:

Front-end development basics
Firebase project setup
Basic JavaScript skills

Resources Required:

Firebase Console
Realtime Database
Web development tools

Real-World Application:

Creating lightweight messaging platforms
Integrating real-time communication in apps

Get Started

9. Data Pipeline with Pub/Sub + Dataflow

This project involves building a real-time data ingestion and processing pipeline using Cloud Pub/Sub and Dataflow.

You will learn how to stream data, apply transformations, and build scalable ETL workflows using Google Cloud tools.

Duration: 8 hours

Project Complexity: Hard

Key Concepts Covered:

Cloud Pub/Sub
Apache Beam (Dataflow)
Real-time Data Processing

Implementation Steps:

Set up a Pub/Sub topic and publish sample data.
Create a Dataflow pipeline using Apache Beam (Python/Java).
Connect the pipeline to read from Pub/Sub and write to BigQuery or Cloud Storage.
Deploy and monitor the pipeline via GCP Console.
Validate data flow and transformations.

Required Pre-requisites:

Intermediate Python or Java knowledge
GCP services familiarity
Basic understanding of data pipelines

Resources Required:

Cloud Pub/Sub
Dataflow/Apache Beam SDK
BigQuery or Cloud Storage

Real-World Application:

Processing streaming data (e.g., IoT, logs)
Building ETL workflows for real-time analytics

Get Started

10. Deploy ML Model on AI Platform

This project focuses on deploying a pre-trained machine learning model to Google Cloud AI Platform for scalable serving.

You will learn model packaging, deployment, and managing prediction endpoints in GCP.

Duration: 7 hours

Project Complexity: Hard

Key Concepts Covered:

AI Platform Serving
Model Deployment
Prediction API

Implementation Steps:

Prepare and export a trained ML model (e.g., TensorFlow SavedModel).
Upload the model to Google Cloud Storage.
Create a model and version on the AI Platform via CLI or Console.
Deploy the model and set up prediction endpoints.
Test predictions using the REST API or client SDK.

Required Pre-requisites:

Familiarity with ML models and TensorFlow
GCP account with AI Platform enabled
Basic REST API usage

Resources Required:

Trained ML model files
GCP Storage
AI Platform console and SDK

Real-World Application:

Deploying ML-powered APIs
Scaling AI inference in production systems

Get Started

Final Words

Beginner-friendly GCP projects can enhance your cloud computing skills, improve your problem-solving abilities, and provide practical experience with real-world cloud scenarios.

Therefore, starting with these easy GCP projects is a smart move to kickstart your journey into mastering Google Cloud Platform!

Frequently Asked Questions

1. What are some easy Google Cloud Platform project ideas for beginners?

Easy GCP project ideas include deploying static websites, setting up virtual machines, using Cloud Shell for automation, creating contact forms with Firebase, and resizing images with Cloud Functions.

2. Why are GCP project ideas important for beginners?

GCP project ideas help beginners gain practical experience, build confidence, and understand cloud services through hands-on learning.

3. What skills can beginners learn from GCP project ideas?

Beginners can learn cloud resource management, basic scripting, serverless functions, database integration, and deploying applications on GCP.

4. Which GCP Project is recommended for someone with no prior programming experience?

Deploying a static website using GCP Storage is ideal for beginners with no programming background.

5. How long does it typically take to complete a beginner-level GCP project?

A beginner-level GCP project usually takes between 2 to 5 hours to complete.

Thirumoorthy

Thirumoorthy serves as a teacher and coach. He obtained a 99 percentile on the CAT. He cleared numerous IT jobs and public sector job interviews, but he still decided to pursue a career in education. He desires to elevate the underprivileged sections of society through education