Github Traffic Insights as Prometheus metrics.

Overview

github-traffic

Github Traffic collects your repository's traffic data and exposes it as Prometheus metrics.

Grafana dashboard Grafana dashboard that displays the metrics generated by Github Traffic.

Quickstart

Requirements:

  • Docker >= 20.10.3

To run github-traffic locally you've to create a .env file like this one:

$ cat .env
# Required
GITHUB_TOKEN=your-github-token-goes-here
ORG_NAME=the-name-of-your-organization-goes-here
# Optional
REPO_TYPE=public-or-private # Default: public
REPO_NAME_CONTAINS=string-to-match-repositories-with # Default: ""
CRONTAB_SCHEDULE=crontab-schedule-to-get-data-from-github # Default: "0 * * * *"

Run the image:

$ docker run --env-file .env -it -p 8001:8001 ghcr.io/grafana/github-traffic
level=INFO msg="Github traffic is running!" 
level=INFO msg="Gather insights" repo="k6" views=163 unique_views=90 clones=406 unique_clones=109 stars=13805
level=INFO msg="Gather insights" repo="postman-to-k6" views=3 unique_views=2 clones=1 unique_clones=1 stars=238
level=INFO msg="Gather insights" repo="jmeter-to-k6" views=1 unique_views=1 clones=2 unique_clones=2 stars=44
...
Go to http://localhost:8001/metrics

Profit!

Now you can collect those metrics as you would do with any other service. To visualize them, we provide an example/template Grafana dashboard: https://grafana.com/grafana/dashboards/15000

You might also like...
DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction
DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction

DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction This is the implementation of DeepSTD in

Code for paper Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting
Code for paper Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting

Decoupled Spatial-Temporal Graph Neural Networks Code for our paper: Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.

A PaddlePaddle implementation of STGCN with a few modifications in the model architecture in order to forecast traffic jam.
A PaddlePaddle implementation of STGCN with a few modifications in the model architecture in order to forecast traffic jam.

About This repository contains the code of a PaddlePaddle implementation of STGCN based on the paper Spatio-Temporal Graph Convolutional Networks: A D

Flow is a computational framework for deep RL and control experiments for traffic microsimulation.
Flow is a computational framework for deep RL and control experiments for traffic microsimulation.

Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap

DI-smartcross - Decision Intelligence Platform for Traffic Crossing Signal Control
DI-smartcross - Decision Intelligence Platform for Traffic Crossing Signal Control

DI-smartcross DI-smartcross - Decision Intelligence Platform for Traffic Crossin

Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

Note: the current releases of this toolbox are a beta release, to test working with Haskell's, Python's, and R's code repositories. Metrics provides i

Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.
Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.

Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this

Details about the wide minima density hypothesis and metrics to compute width of a minima

wide-minima-density-hypothesis Details about the wide minima density hypothesis and metrics to compute width of a minima This repo presents the wide m

Comments
  • Added top referrers and top paths to metrics

    Added top referrers and top paths to metrics

    I extended the code to also collect the github traffic top paths and referrers.

    For instance, for my open source project protoCURL, the web UI shows this: image

    With the changes in the commit, Icreated these panels in Prometheus: github-traffic-top-sites

    I would like to integrate these changes, as I think that other users could also benefit from that.

    The changes essentially just call these two python methods:

    What do you think?

    opened by GollyTicker 3
Releases(v0.0.3)
Owner
Grafana Labs
Grafana Labs is behind leading open source projects Grafana and Loki, and the creator of the first open & composable observability platform.
Grafana Labs
Provide baselines and evaluation metrics of the task: traffic flow prediction

Note: This repo is adpoted from https://github.com/UNIMIBInside/Smart-Mobility-Prediction. Due to technical reasons, I did not fork their code. Introd

Zhangzhi Peng 11 Nov 2, 2022
Pytorch Lightning 1.2k Jan 6, 2023
Prometheus Exporter for data scraped from datenplattform.darmstadt.de

darmstadt-opendata-exporter Scrapes data from https://datenplattform.darmstadt.de and presents it in the Prometheus Exposition format. Pull requests w

Martin Weinelt 2 Apr 12, 2022
Prometheus exporter for Cisco Unified Computing System (UCS) Manager

prometheus-ucs-exporter Overview Use metrics from the UCS API to export relevant metrics to Prometheus This repository is a fork of Drew Stinnett's or

Marshall Wace 6 Nov 7, 2022
git git《Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking》(CVPR 2021) GitHub:git2] 《Masksembles for Uncertainty Estimation》(CVPR 2021) GitHub:git3]

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking Ning Wang, Wengang Zhou, Jie Wang, and Houqiang Li Accepted by CVPR

NingWang 236 Dec 22, 2022
Repository for Traffic Accident Benchmark for Causality Recognition (ECCV 2020)

Causality In Traffic Accident (Under Construction) Repository for Traffic Accident Benchmark for Causality Recognition (ECCV 2020) Overview Data Prepa

Tackgeun 21 Nov 20, 2022
GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting

GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting

null 564 Jan 2, 2023
Project code for weakly supervised 3D object detectors using wide-baseline multi-view traffic camera data: WIBAM.

WIBAM (Work in progress) Weakly Supervised Training of Monocular 3D Object Detectors Using Wide Baseline Multi-view Traffic Camera Data 3D object dete

Matthew Howe 10 Aug 24, 2022
Trajectory Extraction of road users via Traffic Camera

Traffic Monitoring Citation The associated paper for this project will be published here as soon as possible. When using this software, please cite th

Julian Strosahl 14 Dec 17, 2022
Yolo Traffic Light Detection With Python

Yolo-Traffic-Light-Detection This project is based on detecting the Traffic light. Pretained data is used. This application entertained both real time

Ananta Raj Pant 2 Aug 8, 2022