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What is gunicorn-statsd-prometheus-demo?

duffn/gunicorn-statsd-prometheus-demo — explained in plain English

Analysis updated 2026-07-18 · repo last pushed 2019-08-30

Audience · ops devopsComplexity · 3/5DormantSetup · moderate

In one sentence

A Docker Compose demo showing how to monitor a Gunicorn Python web server's performance metrics using statsd and Prometheus dashboards.

Mindmap

mindmap
  root((repo))
    What it does
      Collects server metrics
      Sends stats to Prometheus
      Shows metrics dashboard
      Full stack via Docker
    Tech stack
      Python
      Gunicorn
      Prometheus
      statsd
      Docker Compose
    Use cases
      Monitor web server load
      Debug slow performance
      Learn metrics pipeline
    Audience
      Developers
      Ops and sysadmins

Code map

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What do people build with it?

USE CASE 1

Spin up a Gunicorn app with Prometheus monitoring already wired together using Docker Compose.

USE CASE 2

Investigate why a web app is slow by checking request counts, latency, and memory metrics.

USE CASE 3

View real-time server metrics in the Prometheus graph interface.

USE CASE 4

Use the project as a template for wiring Gunicorn, statsd, and Prometheus in your own app.

What is it built with?

PythonGunicornPrometheusstatsdDocker Compose

How does it compare?

duffn/gunicorn-statsd-prometheus-demo0verflowme/alarm-clock0verflowme/seclists
LanguageCSS
Last pushed2019-08-302022-10-032020-05-03
MaintenanceDormantDormantDormant
Setup difficultymoderateeasyeasy
Complexity3/52/51/5
Audienceops devopsvibe coderops devops

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires Docker Compose, exact ports differ between Docker Machine and Docker on Mac setups.

So what is it?

This repository is a demonstration project that shows how to monitor a Python web application using Gunicorn (a web server) and track its performance metrics in Prometheus (a monitoring system). When you run the project using Docker Compose, it sets up a complete monitoring stack. The application collects statistics about how the web server is performing, things like how many requests it's handling, how long they take, and how much memory it's using, and sends this data to Prometheus. You can then view these metrics in a visual dashboard. After starting the project, you can visit two main interfaces. One shows you the Prometheus graph interface where you can explore and visualize the collected metrics over time. The other displays the raw statistics being gathered from Gunicorn in a metrics format. The specific ports and addresses are provided in the documentation, with different instructions depending on whether you're using Docker Machine or Docker on Mac. This type of setup is useful for developers or system administrators who want to understand how their web applications are performing in production. Instead of guessing why an application might be slow or using vague logs, you get concrete, real-time data about server behavior. A concrete example: if you notice your application is running slowly during certain hours, you could look at these metrics to see whether the problem is too many concurrent requests, memory usage, or something else entirely. The project essentially acts as a working template, rather than explaining how to wire these tools together in documentation, it shows you exactly how Gunicorn, statsd (a metrics collection protocol), and Prometheus fit together in practice.

Copy-paste prompts

Prompt 1
Help me run this Docker Compose stack and explain how to view the Prometheus metrics dashboard.
Prompt 2
Show me how Gunicorn's statsd metrics flow into Prometheus in this project.
Prompt 3
Explain how to use these metrics to diagnose why a web app is slow during peak hours.
Prompt 4
Walk me through adapting this Gunicorn-statsd-Prometheus setup for my own Python web app.

Frequently asked questions

What is gunicorn-statsd-prometheus-demo?

A Docker Compose demo showing how to monitor a Gunicorn Python web server's performance metrics using statsd and Prometheus dashboards.

Is gunicorn-statsd-prometheus-demo actively maintained?

Dormant — no commits in 2+ years (last push 2019-08-30).

How hard is gunicorn-statsd-prometheus-demo to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is gunicorn-statsd-prometheus-demo for?

Mainly ops devops.

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