Serverless Crypto Price Data Pipeline with AWS and Terraform

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In today’s fast-evolving cryptocurrency landscape, access to timely and structured price data is essential for traders, analysts, and developers building financial applications. This article explores a fully automated, serverless cloud pipeline that fetches hourly cryptocurrency prices — including Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and XRP — from the CoinGecko API, stores them in Amazon S3, and manages infrastructure through Terraform and GitHub Actions.

Designed for scalability, reliability, and ease of deployment, this solution eliminates the need for manual intervention while ensuring consistent data collection. Whether you're building historical datasets, powering analytics dashboards, or training machine learning models, this architecture offers a solid foundation.

👉 Discover how to automate crypto data collection securely and efficiently.

Core Features of the Pipeline

The pipeline delivers several powerful capabilities out of the box:

These components work together seamlessly to create a robust, low-maintenance system ideal for developers focused on data-driven applications.

How the Architecture Works

The system follows a clean, event-driven design:

CoinGecko API → AWS Lambda (triggered hourly by EventBridge) → JSON data stored in S3

Here’s a breakdown of each component:

1. Data Source: CoinGecko API

The pipeline pulls real-time cryptocurrency prices from the public CoinGecko API, which provides reliable, up-to-date market data without requiring authentication for basic endpoints.

2. Execution Layer: AWS Lambda + EventBridge

An AWS Lambda function runs every hour, initiated by an Amazon EventBridge rule. This serverless approach ensures cost efficiency (you only pay when the function runs) and automatic scaling.

3. Storage: Amazon S3

Each execution generates a JSON file named with a UTC timestamp (e.g., crypto-prices/2025-04-05T10:00:00Z.json) and uploads it to a designated S3 bucket. This structure enables easy querying, backup, and integration with downstream tools like AWS Athena or data lakes.

4. Infrastructure Management: Terraform

All AWS resources — including the Lambda function, S3 bucket, IAM roles, and EventBridge schedule — are defined in main.tf using Terraform. This allows full version control, reproducibility across environments, and safe rollbacks if needed.

5. Deployment Automation: GitHub Actions

Every push to the main branch triggers a GitHub Actions workflow (defined in .github/workflows/main.yml) that automatically applies Terraform changes and deploys the latest Lambda code — enabling true CI/CD with zero manual steps.

👉 Learn how automation can streamline your crypto data workflows.

Getting Started: Setup Guide

To deploy this pipeline, follow these steps:

Prerequisites

Before beginning, ensure you have:

Step-by-Step Deployment

  1. Clone the Repository

    git clone https://github.com/emaseku/E-Crypto-Prices.git
cd E-Crypto-Prices

  2. Configure Terraform Variables

    Create a terraform.tfvars file to specify your AWS region and preferred bucket name:

    aws_region = "us-east-1"
s3_bucket_name = "your-unique-bucket-name-crypto-prices"

  3. Initialize and Apply Terraform

    Initialize the backend and apply the configuration:

    terraform init
terraform apply

    Confirm the plan to provision all necessary AWS resources.

  4. Enable GitHub Actions (Optional but Recommended)

    Push your code to a GitHub repository. The included workflow will automatically detect changes and deploy updates on every commit to the main branch.

Project Structure Overview

Understanding the file layout helps with customization and maintenance:

You can extend handle.py to include additional coins, convert prices into other fiat currencies, or add logging and error alerts.

Use Cases and Data Applications

Once deployed, the collected data opens doors to various applications:

Because each record includes a precise timestamp and standardized format, integrating this data into larger systems becomes straightforward.

Frequently Asked Questions (FAQ)

Q: Can I add more cryptocurrencies beyond BTC, ETH, LTC, and XRP?
A: Yes! The handle.py script can be modified to include any coin supported by the CoinGecko API. Simply update the list of coin IDs in the request URL.

Q: Is there a cost associated with running this pipeline?
A: While most services have free tiers (e.g., 1M Lambda requests/month, 5GB S3 storage), long-term usage may incur minimal charges based on AWS pricing. Always monitor usage in the AWS console.

Q: How is data organized in the S3 bucket?
A: Files are stored under the crypto-prices/ prefix with filenames matching ISO 8601 timestamps (e.g., crypto-prices/2025-04-05T12:00:00Z.json), making them easy to sort and query.

Q: What happens if the API call fails?
A: Currently, failures result in missing entries. For production use, consider adding retry logic or CloudWatch alarms to notify of execution errors.

Q: Can I change the frequency from hourly to every 15 minutes?
A: Yes — adjust the EventBridge schedule expression in main.tf from rate(1 hour) to rate(15 minutes).

Q: Is sensitive data involved in this pipeline?
A: No personal or private data is processed. The CoinGecko API returns public market data, and no credentials are stored in the codebase when using proper IAM roles.

Final Thoughts

This serverless crypto price ingestion pipeline demonstrates how modern DevOps practices — combining cloud computing, infrastructure automation, and CI/CD — can simplify data engineering tasks. By leveraging AWS Lambda, S3, Terraform, and GitHub Actions, developers gain a maintainable, scalable way to collect valuable cryptocurrency insights without managing servers.

Whether you're exploring blockchain analytics or building next-generation fintech tools, automating data collection is the first step toward smarter decision-making.

👉 Start building your own crypto data solutions today.