Prometheus + ML Intermediate

Prometheus is the leading open-source monitoring system. While it does not include ML natively, you can extend it with ML capabilities for anomaly detection, forecasting, and intelligent alerting using complementary tools and custom exporters.

Adding ML to Prometheus

ApproachToolHow It Works
ForecastingPrometheus + ProphetExternal service reads Prometheus data, runs Prophet, writes predictions back
Anomaly DetectionCustom exporterPython service computes anomaly scores and exposes as Prometheus metrics
Built-in FunctionsPromQLUse predict_linear() and holt_winters() for basic predictions
ML PlatformGrafana MLGrafana Cloud's ML-powered anomaly detection and forecasting

PromQL Forecasting Functions

PromQL
# Predict disk usage 24 hours ahead using linear regression
predict_linear(node_filesystem_avail_bytes{mountpoint="/"}[7d], 86400)

# Holt-Winters smoothing for seasonal patterns
holt_winters(ifHCInOctets{device="eth0"}[1w], 0.3, 0.7)

# Alert if interface utilization is predicted to exceed 90% in 4 hours
predict_linear(
  ifHCInOctets_rate5m{job="network"}[6h], 14400
) > 0.9 * ifHighSpeed * 125000

Custom Anomaly Detection Exporter

Python
from prometheus_client import start_http_server, Gauge
from sklearn.ensemble import IsolationForest
import requests

anomaly_score = Gauge('network_anomaly_score',
                      'Anomaly score for network interface',
                      ['device', 'interface'])

def compute_anomalies():
    # Query Prometheus for recent metrics
    response = requests.get('http://prometheus:9090/api/v1/query',
        params={'query': 'rate(ifHCInOctets[5m])'})
    # Run Isolation Forest and update gauge metrics
    # ... (training and scoring logic)
    anomaly_score.labels(device='router1', interface='eth0').set(score)

start_http_server(8000)  # Prometheus scrapes this endpoint
Grafana ML: If you use Grafana Cloud, its built-in ML features provide anomaly detection and forecasting without building custom exporters. It integrates directly with Prometheus data sources.

Next Step

Learn how to design intelligent alerting systems with dynamic baselines and composite alerts.

Next: Alerting →
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