Open source monitoring and visualization UI for the TICK stack

Monitor ESXi, Synology, Docker, PiHole and Raspberry Pi and Windows using Grafana, InfluxDB and Telegraf

Docker Image with Telegraf (StatsD), InfluxDB and Grafana

Framework allows to perform load testing with Apache Jmeter, view application/server metrics in real-time with Grafana, analyze errors cause with detailed traces for failed requests, compare different test runs in scripted dashboard and perform frontend performance testing with sitespeed.io+webpagetest

Collect golang runtime metrics, pushing to InfluxDB or pulling with Telegraf

Monitoring Pi-Hole statistics with Grafana

Inline Menus for Telegraf made simple

A functional and useful dashboard for pfSense that utilizes influxdb, grafana and telegraf

List of Grafana Dashboards 📺

InfluxDB PHP SDK - UDP/IP or HTTP adapters for read and write data

Telegram Bot framework for Crystal

Installing and configuring Telegraf via Ansible for RedHat/Debian/Ubuntu/Windows/Suse.

Telegraf, InfluxDB, Grafana Docker Monitoring

Python client for sending metrics to Telegraf

Docker - ELK - Tick Stack - Grafana - Kafka

Kubernetes and Docker Compose files to run ISP checks on a Raspberry Pi. 📊

Collect RaspberryPi CPU and GPU temperature with telegraf

Syntax highlighter bot for telegram.

Home Server Setup

🤖 Powerful Nest module for easy and fast creation Telegram bots

Sample project to explore monitoring Vault and Consul with telegraf/influxdb/grafana

Some shell scripts for controlling and checking the Fritz!Box/Fritz!Repeater

Telegraf local sessions middleware with multiple supported storage types (Memory/FileSync/FileAsync/...) using lowdb

A script to collect various Raspberry Pi statistics, which are sent via Telegraf to InfluxDB.

Composite docker application with "8" containers (2x Node-RED, 2x MQTT broker, Telegraf, InfluxDb, Grafana, Nginx) for deployment on Raspberry Pi through Balena.

Chronograf Dashboards for use with data produced by Telegraf input plugins.

Make instant view easily and fast, from any article on the internet in the best messenger ever Telegram

Ecommerce project is being developed using Spring Boot Microservices and Spring Cloud (Backend) and React (Frontend). Splitting the Ecommerce functionality into various individual microservices so that they can be distributed, scale really well and make use of resources efficiently.

Telegram bot example using Telegraf with easy configuration steps. Node v8+.