Github Traffic Insights as Prometheus metrics.

Related tags

Deep Learningrepositorystarsgithub-traffic
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

null 5 Sep 26, 2022
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.

S22 43 Jan 4, 2023
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

Tianjian Li 1 Jan 11, 2022
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

null 867 Jan 2, 2023
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

OpenDILab 213 Jan 2, 2023
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

Ben Hamner 1.6k Dec 26, 2022
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

Keplr 495 Dec 10, 2022
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

Twitter Research 239 Jan 2, 2023
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

Nikhil Iyer 9 Dec 27, 2022
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
GitHub Repository
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2

3.2k Dec 30, 2022
Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.

Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.

Aviv Gabbay 41 Nov 29, 2022
Density-aware Single Image De-raining using a Multi-stream Dense Network (CVPR 2018)

DID-MDN Density-aware Single Image De-raining using a Multi-stream Dense Network He Zhang, Vishal M. Patel [Paper Link] (CVPR'18) We present a novel d

He Zhang 224 Dec 12, 2022
Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR

Codebase for "INVASE: Instance-wise Variable Selection" Authors: Jinsung Yoon, James Jordon, Mihaela van der Schaar Paper: Jinsung Yoon, James Jordon,

Jinsung Yoon 50 Nov 11, 2022
Framework for joint representation learning, evaluation through multimodal registration and comparison with image translation based approaches

CoMIR: Contrastive Multimodal Image Representation for Registration Framework 🖼 Registration of images in different modalities with Deep Learning 🤖

Methods for Image Data Analysis - MIDA 55 Dec 09, 2022
PenguinSpeciesPredictionML - Basic model to predict Penguin species based on beak size and sex.

Penguin Species Prediction (ML) 🐧 👨🏽‍💻 What? 💻 This project is a basic model using sklearn methods to predict Penguin species based on beak size

Tucker Paron 0 Jan 08, 2022
Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)

Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)

Packt 1.5k Jan 03, 2023
Video-based open-world segmentation

UVO_Challenge Team Alpes_runner Solutions This is an official repo for our UVO Challenge solutions for Image/Video-based open-world segmentation. Our

Yuming Du 84 Dec 22, 2022
Extreme Dynamic Classifier Chains - XGBoost for Multi-label Classification

Extreme Dynamic Classifier Chains Classifier chains is a key technique in multi-label classification, sinceit allows to consider label dependencies ef

6 Oct 08, 2022
《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》(EMNLP 2020)

The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers

53 Dec 16, 2022
Plato: A New Framework for Federated Learning Research

a new software framework to facilitate scalable federated learning research.

System <a href=[email protected] Lab"> 192 Jan 05, 2023
Software associated to AAAI paper "Planning with Biological Neurons and Synapses"

jBrain Software associated with the AAAI 2022 paper Francesco D'Amore, Daniel Mitropolsky, Pierluigi Crescenzi, Emanuele Natale, Christos H. Papadimit

Pierluigi Crescenzi 1 Apr 10, 2022
CenterNet:Objects as Points目标检测模型在Pytorch当中的实现

CenterNet:Objects as Points目标检测模型在Pytorch当中的实现

Bubbliiiing 267 Dec 29, 2022
Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.

NOTE: This is still being developed! Setup notes This document uses Jeff Sackmann's tennis data. You can obtain it as follows: git clone https://githu

Martin Ingram 1 Jan 20, 2022
🌾 PASTIS 🌾 Panoptic Agricultural Satellite TIme Series

🌾 PASTIS 🌾 Panoptic Agricultural Satellite TIme Series (optical and radar) The PASTIS Dataset Dataset presentation PASTIS is a benchmark dataset for

86 Jan 04, 2023
Unofficial implementation (replicates paper results!) of MINER: Multiscale Implicit Neural Representations in pytorch-lightning

MINER_pl Unofficial implementation of MINER: Multiscale Implicit Neural Representations in pytorch-lightning. 📖 Ref readings Laplacian pyramid explan

AI葵 51 Nov 28, 2022
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations

Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr

Sriram Ravula 26 Dec 10, 2022
Official Implementation of CVPR 2022 paper: "Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning"

(CVPR 2022) Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning ArXiv This repo contains Official Implementat

Yujun Shi 24 Nov 01, 2022
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm

Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neu

Filip Molcik 38 Dec 17, 2022
Pytorch implementation of Hinton's Dynamic Routing Between Capsules

pytorch-capsule A Pytorch implementation of Hinton's "Dynamic Routing Between Capsules". https://arxiv.org/pdf/1710.09829.pdf Thanks to @naturomics fo

Tim Omernick 625 Oct 27, 2022