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
Betafold - AlphaFold with tunings

BetaFold We (hegelab.org) craeted this standalone AlphaFold (AlphaFold-Multimer,

2 Aug 11, 2022
Garbage Detection system which will detect objects based on whether it is plastic waste or plastics or just garbage.

Garbage Detection using Yolov5 on Jetson Nano 2gb Developer Kit. Garbage detection system which will detect objects based on whether it is plastic was

Rishikesh A. Bondade 2 May 13, 2022
🌳 A Python-inspired implementation of the Optimum-Path Forest classifier.

OPFython: A Python-Inspired Optimum-Path Forest Classifier Welcome to OPFython. Note that this implementation relies purely on the standard LibOPF. Th

Gustavo Rosa 30 Jan 04, 2023
Display, filter and search log messages in your terminal

Textualog Display, filter and search logging messages in the terminal. This project is powered by rich and textual. Some of the ideas and code in this

Rik Huygen 24 Dec 10, 2022
Make a surveillance camera from your raspberry pi!

rpi-surveillance Make a surveillance camera from your Raspberry Pi 4! The surveillance is built as following: the camera records 10 seconds video and

Vladyslav 62 Feb 03, 2022
Tool which allow you to detect and translate text.

Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr

Damian Panek 176 Nov 28, 2022
The official repo of the CVPR 2021 paper Group Collaborative Learning for Co-Salient Object Detection .

GCoNet The official repo of the CVPR 2021 paper Group Collaborative Learning for Co-Salient Object Detection . Trained model Download final_gconet.pth

Qi Fan 46 Nov 17, 2022
naked is a Python tool which allows you to strip a model and only keep what matters for making predictions.

naked is a Python tool which allows you to strip a model and only keep what matters for making predictions. The result is a pure Python function with no third-party dependencies that you can simply c

Max Halford 24 Dec 20, 2022
Wind Speed Prediction using LSTMs in PyTorch

Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu

Onur Kaplan 151 Dec 14, 2022
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation Demo video: CVPR 2021 Oral: Single Channel Manipulation: Localized or attribu

Zongze Wu 267 Dec 30, 2022
Official implementation of "Watermarking Images in Self-Supervised Latent-Spaces"

🔍 Watermarking Images in Self-Supervised Latent-Spaces PyTorch implementation and pretrained models for the paper. For details, see Watermarking Imag

Meta Research 32 Dec 13, 2022
Transformer model implemented with Pytorch

transformer-pytorch Transformer model implemented with Pytorch Attention is all you need-[Paper] Architecture Self-Attention self_attention.py class

Mingu Kang 12 Sep 03, 2022
High accurate tool for automatic faces detection with landmarks

faces_detanator High accurate tool for automatic faces detection with landmarks. The library is based on public detectors with high accuracy (TinaFace

Ihar 7 May 10, 2022
Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)

AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed

Sakib Mahmud 1 Nov 15, 2021
PyTorch DepthNet Training on Still Box dataset

DepthNet training on Still Box Project page This code can replicate the results of our paper that was published in UAVg-17. If you use this repo in yo

Clément Pinard 115 Nov 21, 2022
A package related to building quasi-fibration symmetries

qf A package related to building quasi-fibration symmetries. If you'd like to learn more about how it works, see the brief explanation and References

Paolo Boldi 1 Dec 01, 2021
StocksMA is a package to facilitate access to financial and economic data of Moroccan stocks.

Creating easier access to the Moroccan stock market data What is StocksMA ? StocksMA is a package to facilitate access to financial and economic data

Salah Eddine LABIAD 28 Jan 04, 2023
Bayesian Optimization Library for Medical Image Segmentation.

bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im

Şafak Bilici 7 Feb 10, 2022
PyArmadillo: an alternative approach to linear algebra in Python

PyArmadillo is a linear algebra library for the Python language, with an emphasis on ease of use.

Terry Zhuo 58 Oct 11, 2022
This repository is all about spending some time the with the original problem posed by Minsky and Papert

This repository is all about spending some time the with the original problem posed by Minsky and Papert. Working through this problem is a great way to begin learning computer vision.

Jaissruti Nanthakumar 1 Jan 23, 2022