Python Flask Microservice: Monitoring with Prometheus and Grafana

About Monitoring with Prometheus and Grafana

Both Prometheus and Grafana are compatible with microservice applications, integrating Prometheus with Flask is straightforward to provide performance and monitoring metrics.

Here I will update the docker-compose to add Prometheus and Grafana as services, then add Prometheus metrics in both order and user application code by importing PrometheusMetrics from the prometheus_flask_exporter module, which is used to expose Prometheus metrics for the Flask application. then initialize Prometheus metrics with metrics = PrometheusMetrics(app). Use @metrics.counter('get_orders_count', 'Count of calls to the get_orders endpoint') to define a Prometheus counter metric that increments each time the get_orders endpoint is called.

Import os to enable environment variable for Logstash host, logstash_host = os.getenv('LOGSTASH_HOST', 'localhost') to fetche the Logstash host from environment variables, defaulting to localhost.

# Folder structure
/06-with-monitoringstack
├── api_gateway
│   ├── api_gateway.py
│   └── Dockerfile
├── docker-compose.yml
├── logstash.conf
├── order_service
│   ├── Dockerfile
│   ├── order_service.py
├── prometheus.yaml
└── user_service
    ├── Dockerfile
    └── user_service.py

# add Prometheus and Grafana in docker-compose.yaml
version: '3'
services:
  prometheus:
    image: prom/prometheus
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
    ports:
      - "9090:9090"
  grafana:
    image: grafana/grafana
    ports:
      - "3000:3000"

# create prometheus.yml for Prometheus configration
# vim prometheus.yml
global:
  scrape_interval: 15s

scrape_configs:
  - job_name: 'flask'
    static_configs:
      - targets: ['user-service:5001', 'order-service:5002']

# add Monitoring logic into python code 

# order_service.py
import logging
import requests
from flask import Flask, jsonify
from pygelf import GelfUdpHandler
from prometheus_flask_exporter import PrometheusMetrics
import os

app = Flask(__name__)
metrics = PrometheusMetrics(app)

@app.route('/orders')
def get_orders():
    orders = [
        {'id': 1, 'item': 'Laptop', 'price': 1200},
        {'id': 2, 'item': 'Phone', 'price': 800}
    ]
    app.logger.info("Fetched order data")
    return jsonify(orders)

def register_service():
    payload = {
        "ID": "order-service",
        "Name": "order-service",
        "Address": "order-service",
        "Port": 5002
    }
    response = requests.put('http://consul:8500/v1/agent/service/register', json=payload)
    if response.status_code == 200:
        app.logger.info("Order service registered successfully")
    else:
        app.logger.error("Failed to register order service")

if __name__ == '__main__':
    # Configure logging
    logstash_host = os.getenv('LOGSTASH_HOST', 'localhost')
    handler = GelfUdpHandler(host=logstash_host, port=12201)
    app.logger.addHandler(handler)
    app.logger.setLevel(logging.INFO)
    
    register_service()
    app.run(host='0.0.0.0', port=5002)


# user_service.py
import logging
import requests
from flask import Flask, jsonify
from pygelf import GelfUdpHandler
from prometheus_flask_exporter import PrometheusMetrics
import os

app = Flask(__name__)
metrics = PrometheusMetrics(app)

@app.route('/users')
def get_users():
    users = [
        {'id': 1, 'name': 'Alice'},
        {'id': 2, 'name': 'Bob'}
    ]
    app.logger.info("Fetched user data")
    return jsonify(users)

def register_service():
    payload = {
        "ID": "user-service",
        "Name": "user-service",
        "Address": "user-service",
        "Port": 5001
    }
    response = requests.put('http://consul:8500/v1/agent/service/register', json=payload)
    if response.status_code == 200:
        app.logger.info("User service registered successfully")
    else:
        app.logger.error("Failed to register user service")

if __name__ == '__main__':
    # Configure logging
    logstash_host = os.getenv('LOGSTASH_HOST', 'localhost')
    handler = GelfUdpHandler(host=logstash_host, port=12201)
    app.logger.addHandler(handler)
    app.logger.setLevel(logging.INFO)
    
    register_service()
    app.run(host='0.0.0.0', port=5001)

Now Run docker-compose to bring all containers up and running. Should see all services with Prometheus and Grafana.

docker-compose up --build

Creating 06-with-monitoringstack_api-gateway_1   ... done
Creating 06-with-monitoringstack_order-service_1 ... done
Creating 06-with-monitoringstack_user-service_1  ... done
Creating 06-with-monitoringstack_kibana_1        ... done
Creating 06-with-monitoringstack_grafana_1       ... done
Creating 06-with-monitoringstack_logstash_1      ... done
Creating 06-with-monitoringstack_prometheus_1    ... done
Creating 06-with-monitoringstack_elasticsearch_1 ... done
Creating 06-with-monitoringstack_consul_1        ... done

Verify Prometheus and Grafana

Access Grafana via http://localhost:3000, log in with admin/admin.

Add Prometheus as a Data Source in Grafana by setting the URL to http://localhost:9090 and save.

Create Dashboards in Grafana to use the Prometheus data source to visualize metrics from user-service and order-service.

Conclusion

Now we can enable monitoring with Prometheus and Grafana.

In the next post, I will see how to depoly our Python Flask microservice into Kubernetes.