Part 4: Deploy Grafana Dashboard to AWS EC2

In this part we will learn how to be devops haha ✌️, deploying grafana local to server with AWS EC2

Photo by David Iskander on Unsplash

Before we go, i hope you have a aws account, and have a credit for creating instances.

Create New Instance

https://console.aws.amazon.com/ec2/v2/home?region=us-east-1

Select Ubuntu Server 16.04 LTS

In configure security add HTTP, HTTPS and Custom TCP

Create new key.pem

• Chmod 400 grafana-server.pem
• Create file name login.sh

ssh -i “pemname.pem” ubuntu@domainname
example : 
ssh -i "grafana-server.pem" ubuntu@ec2-3-23-161-56.compute-1.amazonaws.com

• Change permission login.sh file

sudo chmod 755 login.sh

• Login AWS EC2 with

./login.sh

Setting Nodejs and Docker

• Install nodejs and npm

sudo apt update
sudo apt install nodejs
sudo apt install npm

• Install nginx

sudo apt install nginx

• And check ip address

• Install Docker

sudo apt-get update
sudo apt-get install \
apt-transport-https \
ca-certificates \
curl \
gnupg-agent \
software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository \
"deb [arch=amd64] https://download.docker.com/linux/ubuntu \
$(lsb_release -cs) \
stable"
sudo apt update
sudo apt-get install docker-ce docker-ce-cli containerd.io
sudo docker --version

• Install docker-compose

sudo curl -L “https://github.com/docker/compose/releases/download/1.25.4/docker-compose-$(uname -s)-$(uname -m)” -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
docker-compose --version

• Clone your project

git clone https://github.com/rafiudd/bigquery-api-nodejs
cd bigquery-api-nodejs
npm install

• Setting credentials path

export GOOGLE_APPLICATION_CREDENTIALS="[PATH]"
example : 
export GOOGLE_APPLICATION_CREDENTIALS="/home/bigquery-api-nodejs/key.json"

• Last bro 😍, but not least run docker compose

sudo docker-compose up -d

• And check the ip with port 3000

yeayyy ,grafana is successfully running in server️ ✌️

• Login with default username and password

username: admin
password: admin

• Edit your inbound and compare with nodejs port

• Now run your code, create table and get data from bigquery

node index.js

Yeyyy finally we finish it

Check live dashboard at

http://3.83.163.86:3000/
email: rayhanrafiudd@gmail.com
password: admincantik

rafiudd/bigquery-api-nodejs

Amazon Web Services (AWS) - Layanan Komputasi Cloud

Part 3: Data Visualization with Grafana

Part 2: Create API Bigquery to Postgresql with Nodejs

Part 1: Introduction to Data Visualization