A Python microservice template using Flask, providing RESTful API endpoints for building scalable backend services.
This repository contains a production-ready Flask microservice that connects to a Couchbase database. It is designed to demonstrate how to set up a web server with health check endpoints, graceful shutdown capabilities, and logging using Loguru. The application also integrates with Prometheus for monitoring and Grafana for visualization.
You can install the required packages using the following command:
pip install -r requirements.txt
Clone the repository:
git clone https://github.com/yourusername/your-repo-name.git
cd your-repo-name
Install the required dependencies:
pip install -r requirements.txt
Set up your Couchbase server and create a bucket. Update the configuration in the .env file or set environment variables as described in the Configuration section.
The application configuration is managed through environment variables. You can set the following variables:
FLASK_HOST: The host for the Flask application (default: 0.0.0.0).FLASK_PORT: The port for the Flask application (default: 8080).FLASK_DEBUG: Enable or disable debug mode (default: False).REQUEST_TIMEOUT: Timeout for requests in seconds (default: 30).KEEP_ALIVE_TIMEOUT: Keep-alive timeout in seconds (default: 5).GRACEFUL_SHUTDOWN_TIMEOUT: Timeout for graceful shutdown in seconds (default: 5).FLASK_SECRET_KEY: Secret key for session management (default: your-secret-key-here).COUCHBASE_HOST: Couchbase server host (default: couchbase://localhost).COUCHBASE_USER: Couchbase username (default: Administrator).COUCHBASE_PASSWORD: Couchbase password (default: password).COUCHBASE_BUCKET: Couchbase bucket name (default: travel-sample).To run the application, execute the following command:
python main.py
The application will start and listen for incoming requests on the specified host and port.
GET /: Returns a simple greeting message.GET /health-check: Returns a health check status.POST /shutdown: Initiates a graceful shutdown of the server.The application exports metrics that can be scraped by Prometheus. To set up Prometheus:
Configure your prometheus.yml to scrape metrics from the Flask application:
global:
scrape_interval: 10s
scrape_configs:
- job_name: flask-app
static_configs:
- targets:
- localhost:8080
metrics_path: /metrics
Start Prometheus and point it to your configuration file.
Use Grafana to visualize the metrics collected by Prometheus. You can create dashboards to monitor the health and performance of your microservice.
The application uses Loguru for logging. Logs are output to the console and also saved to a file (logs/app.log). The log level can be configured through the LOG_LEVEL environment variable.
Contributions are welcome! Please feel free to submit a pull request or open an issue for any suggestions or improvements.
This project is licensed under the MIT License. See the LICENSE file for more details.