CloudPing.co
CloudPing records inter-region latency over TCP connections between all AWS regions in real-time, providing a continuously updated, reliable source of truth for AWS region-to-region latency metrics.
About
When building global AWS deployments, knowing which inter-region transactions will face the most latency is crucial for system design. While static examples and anecdotal guidance based on geographic location exist, CloudPing.co offers a dynamic, consistently updated latency monitoring service that tracks real-world performance between all AWS regions.
Architecture
CloudPing.co consists of several microservices working together:
Components
1. Frontend (cloudping-frontend-njs/)
A Next.js application that provides an interactive user interface for viewing latency data.
- Modern responsive design with Tailwind CSS
- Interactive latency matrix with filtering capabilities
- Visualization tools to help understand region relationships
- Supports viewing different time periods (daily, weekly, monthly, yearly)
- Ability to filter regions and view by percentiles (P50, P90, etc.)
2. API Service (cloudping-api/)
A serverless API built with AWS Chalice that provides endpoints for accessing latency data.
- RESTful endpoints for retrieving latency information
- Support for filtering by region, timeframe, and percentile
- Historical data access with API key authentication
- Provides region status information
3. Ping Functions (ping_from_region/)
Lambda functions deployed to each AWS region that measure TCP latency to all other regions.
- Runs every 6 hours in each active AWS region
- Measures TCP connection time to AWS service endpoints
- Records raw results in DynamoDB for historical tracking
- Stores detailed round-trip information for analysis
4. Scheduled Functions (scheduled_functions/)
Background tasks that process raw ping data to calculate statistics and summaries.
- Calculates daily, weekly, monthly, and annual averages
- Computes percentiles (P10, P25, P50, P75, P90, P98, P99)
- Stores aggregated data in DynamoDB tables
- Updates region status information
5. Ping Function Deployer (ping-function-deployer/)
Automated deployment service that ensures ping functions exist in all AWS regions.
- Automatically deploys ping functions to new regions
- Updates function code when changes are made
- Sets up appropriate CloudWatch Event Rules for scheduling
- Maintains consistent monitoring across the AWS global infrastructure
6. Account Region Manager (account-region-manager/)
Service that monitors and enables new AWS regions automatically.
- Checks for newly available AWS regions
- Automatically enables opt-in regions for the account
- Ensures CloudPing.co expands to cover new regions as they launch
- Maintains region status information
Database Structure
CloudPing.co uses Amazon DynamoDB for data storage:
PingTest - Raw data from all region-to-region pingscloudping_regions - Configuration data for all AWS regionscloudping_stored_avgs - Processed averages and percentiles used by the frontend
Local Development
Prerequisites
- Python 3.9+
- Node.js 18+
- AWS CLI configured with appropriate credentials
- Docker (optional, for container-based development)
Setting Up the Frontend
# Navigate to the frontend directory
cd cloudping-frontend-njs
# Install dependencies
npm install
# Run development server
npm run dev
The frontend will be available at http://localhost:3000
Setting Up the API
# Navigate to the API directory
cd cloudping-api
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Run local API server
chalice local
The API will be available at http://localhost:8000
Testing Ping Functions
# Navigate to the ping function directory
cd ping_from_region
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Run the function locally
python -c "from app import ping; ping({})"
Setting Up Scheduled Functions
# Navigate to the scheduled functions directory
cd scheduled_functions
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Run individual functions
python -c "from chalicelib.calculate_avgs import calculate; calculate({})"
Deployment
The Lambda functions are deployed with AWS Chalice:
# Example: Deploy ping functions
cd ping_from_region
chalice deploy --stage prod
The frontend is deployed as a Docker container in AWS Fargate:
# Build and deploy the frontend
cd cloudping-frontend-njs
docker build -t cloudping-frontend .
Future Enhancements
- Enhanced API access for raw data and custom queries
- Interactive graphs showing latency trends over time
- Support for GovCloud and China regions
- Additional cloud providers beyond AWS
Contributing
Contributions to CloudPing.co are welcome! If you'd like to help improve the project, please feel free to submit pull requests or open issues.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Contact
For questions or feedback, please contact [email protected].
