Prometheus Python

Prometheus Python

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Prometheus Python: A Brief Overview

Prometheus is a popular open-source monitoring and alerting system that collects metrics, stores them in a time-series database, and generates alerts based on those metrics. The tool is named after the Titan in Greek mythology who defied Zeus by stealing fire from the gods.

The Prometheus Python client provides an interface for collecting and sending data to a Prometheus server, allowing you to monitor your applications and systems. This article will cover the basics of using Prometheus with Python.

Installing Prometheus and the Prometheus Python Client

To get started with Prometheus and the Prometheus Python client, follow these steps:

Creating a Prometheus Metric

To send metrics from your Python application to Prometheus, you need to create a metric. Here's an example of how you can do this:

import prometheus_client
class MyMetrics(prometheus_client.Metric):
def init(self):
super().init('my_metrics')
Create some sample metrics
self.request_count = prometheus_client.GaugeMetricFamily(
'request_count', 'The number of requests handled by the application'
)
self.request_latency = prometheus_client.HistogramMetricFamily(
'request_latency', 'The latency of the request in milliseconds'
)
def update(self):
Update the metrics
self.request_count.set(100)
self.request_latency.observe(500)
my_metrics = MyMetrics()

Pushing Metrics to Prometheus

To push your metrics to Prometheus, use the push_to_gateway method:

my_metrics.push_to_gateway('http://localhost:9090')

Consuming Prometheus Data in Python

To consume Prometheus data in Python, you can use the prometheus_client library. Here's an example of how you can do this:

import prometheus_client
Create a Prometheus client
client = prometheus_client.PrometheusClient('http://localhost:9090')
Fetch some metrics from Prometheus
metrics = client.get_metric_family('my_metrics_request_count')
Print the metric value
print(metrics[0].value)

Benefits of Using Prometheus with Python

Using Prometheus with Python offers several benefits, including:

Conclusion

In this article, we explored the basics of using Prometheus with Python. We covered installing Prometheus and the Prometheus Python client, creating a metric, pushing metrics to Prometheus, consuming Prometheus data in Python, and the benefits of using Prometheus with Python. By following these steps, you can start monitoring your applications and systems with Prometheus.

Happy monitoring!

What is the python script to monitor log files?

Here's a Python script that monitors log files for new logs and provides a real-time update:

log_monitor.py

import os
import time
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
class LogMonitorHandler(FileSystemEventHandler):
def on_modified(self, event):
if not self.is_log_file(event.src_path):
return
print(f"New log detected: {event.src_path}")
def is_log_file(self, path):
return os.path.splitext(path)[1] in ['.log', '.txt'] and 'logs' in path
if name == "main":
path = "."
event_handler = LogMonitorHandler()
observer = Observer()
observer.schedule(event_handler, path)
observer.start()
try:
while True:
time.sleep(1)
except KeyboardInterrupt:
observer.stop()
observer.join()

How it works:

Installation:

To install and use this script:

    pip install watchdog

    python log_monitor.py

Remember to customize the script according to your specific log file structure and location.