Project 10 →Deployment of Swiggy application using github actions

18 min readFeb 29, 2024

Today we are going to deploy the Swiggy application using github actions as a ci-cd tool in place of jenkins or circle-ci below is the completion steps for this project

Completion Steps →

Step 1 → Setup Terraform and configure aws on your local machine

Step 2 → Building a simple Infrastructure from code using terraform

Step 3 → IAM Role for EC2

Step 4 →Setup github actions with ec2

Step 5 →setup sonarqube and dockerhub for github actions

Step 6→ Elastic kubernetes service or Eks cluster setup

Step 7 → build and push docker image

Step 8 →Monitering via Prmotheus and grafana

Step 9 → Destroy all the things

before do anything →

open your terminal and make a separate folder for swiggy→mkdir swiggy
cd swiggy
clone the github repo
git clone https://github.com/Aakibgithuber/deployment-using-github-actions.git

Step 1 → Setup Terraform and configure aws on your local machine

1. Setup Terraform

To install terraform copy and paste the below commands

sudo su
snap install terraform --classic

which terraform

2. Configure aws

create an IAM user
go to your aws account and type IAM

click on iam

3. click on user →create user

4. Give a name to your user and tick on provide user access to management console and then click on I want an IAM user option

5. choose a password for your user →click next

6. Attach the policies directly to your iam user → click next

note →I will provide the administrator accesss for now but we careful while attaching the policies on your workapce

review and create user

7. click on create user

8. download your password file if it is autogenerated otherwise it is your’s choice

9. Now click on your IAM user →security credentials

10. scroll down to access keys and create an access keys

11.choose aws cli from the options listed

12. click next and download you csv file for username and password

13. go to your terminal and type →aws configure

14. Now it is ask to your access key and secret key for this open your csv file and paste the access and secret key and remain everything default

15. Now you are ready to configure aws from your terminal

Step 2 → Building a simple Infrastructure from code using terraform

go to folder → cd Instance-terraform
there are three files present main.tf, script.sh , provider.tf
open the file →vim Main.tf

4. change this section → ami = # your ami id , key_name= #your key pair if any

Now run terraform commands →

main.tf includes userdata which links script.sh file on which execution install docker,trivy,and start the sonarqube container on port 9000

terraform init
terraform validate
terraform plan
terraform apply --auto-approve

terraform init,validate and plan output

terraform apply

Go to your aws console and checkout the ec2 instances

Here we see swiggy base server instance is created by terraform with the given configuration

Step 3 → IAM Role for EC2

Why we need IAM role for EC2 → It is used by your ec2 instance to create EKS cluster and manage s3 bucket by applying this IAM role it gives the authenticity to your ec2 to do changes in aws account

1. creating IAM role

on the search bar type IAM

2. click on Roles on the left side

3. click on create role and choose EC2 from the dropdown

4. click on next

5. choose administrator access on permission sections

6. click on next and give a name to your role

7. click on create role option and your IAM role is created

2. Attach IAM role with your EC2

go to EC2 section
click on actions → security → modify IAM role option

3. choose the role from dropdown and click on update IAM role

why we need IAM Role →

Imagine you have a robot (EC2 instance) that does tasks for you in a big factory (AWS environment). Now, this robot needs to access different rooms (AWS services like S3, DynamoDB, etc.) to perform its tasks.

Here’s where IAM (Identity and Access Management) comes in:

Robot Needs a Key to Enter Rooms: The IAM Role is like giving your robot a special key. This key allows the robot to enter specific rooms (access certain AWS services). Without this key, the robot can’t get in.
Different Keys for Different Robots: Each robot (EC2 instance) can have its own key (IAM Role) with specific permissions. So, one robot may have a key to enter the storage room (access S3), while another robot has a key to enter the database room (access DynamoDB).
No Need for Hardcoding Passwords: Using IAM Roles means you don’t have to hardcode passwords (access credentials) into the robot. It’s like not writing down passwords on the robot itself. The robot just uses its key when needed.
Easily Change Permissions: If you want to change what a robot can do, you just change the permissions on its key (IAM Role). No need to reprogram the robot or give it a new password; just update the permissions on its key.
Secure and Controlled Access: IAM Roles help keep things secure. You can control exactly what each robot is allowed to do. This way, if one robot is compromised or needs a different role, you can easily adjust its permissions without affecting others.

Now everything is done what we have to do is just throw some commands and build our infrastructure using terraform to run swiggy app

Step 4 →Setup github actions with ec2

go to your project repo of github →click on setting →Actions →Runners

select the runner image as i am using linux so chose linux

2. These commands gives by the github that are used to run on your linux server

3. go to your ec2 and connnect to it and run the following commands one by one

# Create a folder
mkdir actions-runner && cd actions-runner# Download the latest runner package

curl -o actions-runner-linux-x64-2.313.0.tar.gz -L https://github.com/actions/runner/releases/download/v2.313.0/actions-runner-linux-x64-2.313.0.tar.gz

# Optional: Validate the hash
echo "56910d6628b41f99d9a1c5fe9df54981ad5d8c9e42fc14899dcc177e222e71c4  actions-runner-linux-x64-2.313.0.tar.gz" | shasum -a 256 -c

# Extract the installer
tar xzf ./actions-runner-linux-x64-2.313.0.tar.gz

Configure
# Create the runner and start the configuration experience
./config.sh --url https://github.com/Aakibgithuber/Swiggy-app-deployment-using-github-actions- --token AYEA4XIU5ILR2XRXF6F2DFLF2GYZW# Last step, run it!
./run.sh

Step 5 →setup sonarqube and dockerhub for github actions

1. Sonarqube setup →

copy the public ip of your machine

go to your browser and type →<publicip>:9000

sonarqube window open

2. iniatially username and password is admin

3. update your password

4. welcome window of Sonarqube

setup projects in sonarqube for github actions

go to your sonarqube server
click on projects
in the name field type swiggy
click on set up

5. click on github actions

6. generate a token

7. copy token and go to your github repo →setting →secretand variable →actions →and create new repository secrets

8. paste the name and token generated above

9. create one more new secret repo and add the above info there

10. Now go back to your sonarqube and click on continue

11. Now go to your github and create a new file as below instuctions

12. Name the file as given above and enter the data as shown

13. create one more file according to above instructions

14. enter the above data in your file

15. commit changes and go to your ec2 and start a runner by command

./run.sh

16. Now go to Actions and see your build.yaml is automatically triggerd

17. checkout the sonarqube

2. setup dockerhub for github actions

go to your dockerhub account and create a token under myaccount →setting →Security

2. Now again go to your github account → setting →Secrets and variables →actions →create a new repo secret

3. create a one more secret of your username

Now you are connected with your dockerhub via github

Step 6→ Elastic kubernetes service or Eks cluster setup

Go to your ec2 and run the following command

aws configure

2. Provide the access key and secret key setup above

3. fetch the git hub repo of EKS terraform folder

git clone https://github.com/Aakibgithuber/deployment-using-github-actions.git

4. go to EKS terraform folder by

cd deployment-using-github-actions/Eks-terraform
ls

5. Now Setup your EKS cluster by the below terraform commands

terraform init
terraform validate
terraform plan
terraform apply

6. It takes 5 to 10 min to create a cluster

Step 7 → build and push docker image

Now go to your github workflows folder and edit the build.yaml file

add the following code

name: Build

on:
  push:
    branches:
      - master

jobs:
  build:
    name: Build
    runs-on: [self-hosted]
    steps:
      - uses: actions/checkout@v2
        with:
          fetch-depth: 0  # Shallow clones should be disabled for a better relevancy of analysis
      - uses: sonarsource/sonarqube-scan-action@master
        env:
          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
          SONAR_HOST_URL: ${{ secrets.SONAR_HOST_URL }}
      - name: NPM Install
        run: npm install
        
      - name: Docker build and push
        run: |
          # Run commands to build and push Docker images
          docker build -t swiggy-clone .
          docker tag swiggy-clone aakibkhan1212/swiggy-clone:latest
          docker login -u ${{ secrets.Dockerhub_username }} -p ${{ secrets.Dockerhub_token }}
          docker push aakibkhan1212/swiggy-clone:latest
        env:
          DOCKER_CLI_ACI: 1

Importent note → make sure to change the dockerhub repo name and tag of your image

2. Preview and commit the changes

3. Go to actions →build to see the changes

Docker image is created and pushed to your dockerhub

Step 7 →Deployment on kubernetes

Go to your repo and make changes on build.yml file and add the following code

deploy:
   needs: build
   runs-on: [self-hosted]
   steps:
      - name: docker pull image
        run: docker pull aakibkhan1212/swiggy-clone:latest
      - name: Image scan
        run: trivy image aakibkhan1212/swiggy-clone:latest > trivyimagedeploy.txt
      - name: Deploy to container
        run: docker run -d --name swiggy-clone -p 3000:3000 aakibkhan1212/swiggy-clone:latest

2. Above code runs the application locally

3. To run it on kubernetes cluster add the following code in your build.yml

- name: Update kubeconfig
        run: aws eks --region ap-south-1 update-kubeconfig --name EKS_CLOUD
      - name: Deploy to kubernetes
        run: kubectl apply -f deployment-service.yml2. commit the changes and this will deploy the image locally on the base server

Deployment is also completed check the runner on ec2

6. run the following command

kubectl get all

7. copy the load balancer ingress and paste it on browser

Your Swiggy app is Now deployed on the Kubernetes cluster

8. Complete code for build.yaml file

name: Build

on:
  push:
    branches:
      - master

jobs:
  build:
    name: Build
    runs-on: [self-hosted]
    steps:
      - uses: actions/checkout@v2
        with:
          fetch-depth: 0  # Shallow clones should be disabled for a better relevancy of analysis
      - uses: sonarsource/sonarqube-scan-action@master
        env:
          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
          SONAR_HOST_URL: ${{ secrets.SONAR_HOST_URL }}
      - name: NPM Install
        run: npm install
        
      - name: Docker build and push
        run: |
          # Run commands to build and push Docker images
          docker build -t swiggy-clone .
          docker tag swiggy-clone aakibkhan1212/swiggy-clone:latest
          docker login -u ${{ secrets.Dockerhub_username }} -p ${{ secrets.Dockerhub_token }}
          docker push aakibkhan1212/swiggy-clone:latest
        env:
          DOCKER_CLI_ACI: 1
  deploy:
   needs: build
   runs-on: [self-hosted]
   steps:
      - name: docker pull image
        run: docker pull aakibkhan1212/swiggy-clone:latest
      - name: Image scan
        run: trivy image aakibkhan1212/swiggy-clone:latest > trivyimagedeploy.txt
      - name: Deploy to container
        run: docker run -d --name swiggy-clone1 -p 3000:3000 aakibkhan1212/swiggy-clone:latest
      - name: Update kubeconfig
        run: aws eks --region ap-south-1 update-kubeconfig --name EKS_CLOUD
      - name: Deploy to kubernetes
        run: kubectl apply -f deployment-service.yml

Make changes in the above code according to your github repo and dockerhub account

Step7 →Monitering via Prmotheus and grafana

Prometheus is like a detective that constantly watches your software and gathers data about how it’s performing. It’s good at collecting metrics, like how fast your software is running or how many users are visiting your website.
Grafana, on the other hand, is like a dashboard designer. It takes all the data collected by Prometheus and turns it into easy-to-read charts and graphs. This helps you see how well your software is doing at a glance and spot any problems quickly.

In other words, Prometheus collects the information, and Grafana makes it look pretty and understandable so you can make decisions about your software. They’re often used together to monitor and manage applications and infrastructure.

1. Setup another server or EC2 for moniterning

go to ec2 console and launch an instance having a base image ofu buntu and with t2.medium specs because Minimum Requirements to Install Prometheus :

2 CPU cores.
4 GB of memory.
20 GB of free disk space.

2. Installing Prometheus:

First, create a dedicated Linux user for Prometheus and download Prometheus:

sudo useradd — system — no-create-home — shell /bin/false prometheus
wget https://github.com/prometheus/prometheus/releases/download/v2.47.1/prometheus-2.47.1.linux-amd64.tar.gz

2. Extract Prometheus files, move them, and create directories:

tar -xvf prometheus-2.47.1.linux-amd64.tar.gz
cd prometheus-2.47.1.linux-amd64/
sudo mkdir -p /data /etc/prometheus
sudo mv prometheus promtool /usr/local/bin/
sudo mv consoles/ console_libraries/ /etc/prometheus/
sudo mv prometheus.yml /etc/prometheus/prometheus.yml

3. Set ownership for directories:

useradd prometheus
sudo chown -R prometheus:prometheus /etc/prometheus/ /data/

4. Create a systemd unit configuration file for Prometheus:

sudo nano /etc/systemd/system/prometheus.service

Add the following code to the prometheus.service file:

[Unit]
Description=Prometheus
Wants=network-online.target
After=network-online.target

StartLimitIntervalSec=500
StartLimitBurst=5[Service]
User=prometheus
Group=prometheus
Type=simple
Restart=on-failure
RestartSec=5s
ExecStart=/usr/local/bin/prometheus \
  --config.file=/etc/prometheus/prometheus.yml \
  --storage.tsdb.path=/data \
  --web.console.templates=/etc/prometheus/consoles \
  --web.console.libraries=/etc/prometheus/console_libraries \
  --web.listen-address=0.0.0.0:9090 \
  --web.enable-lifecycle[Install]
WantedBy=multi-user.target

b. press →ctrl+o #for save and then ctrl+x #for exit from the file

Here’s a explanation of the key parts in this above file:

User and Group specify the Linux user and group under which Prometheus will run.
ExecStart is where you specify the Prometheus binary path, the location of the configuration file (prometheus.yml), the storage directory, and other settings.
web.listen-address configures Prometheus to listen on all network interfaces on port 9090.
web.enable-lifecycle allows for management of Prometheus through API calls.

5. Enable and start Prometheus:

sudo systemctl enable prometheus
sudo systemctl start prometheus

sudo systemctl status prometheus

Now go to your security group of your ec2 to enable port 9090 in which prometheus will run

go to → http://public_ip:9090 to see the webpage of prometheus

3. Installing Node Exporter:

Node exporter is like a “reporter” tool for Prometheus, which helps collect and provide information about a computer (node) so Prometheus can monitor it. It gathers data about things like CPU usage, memory, disk space, and network activity on that computer.

A Node Port Exporter is a specific kind of Node Exporter that is used to collect information about network ports on a computer. It tells Prometheus which network ports are open and what kind of data is going in and out of those ports. This information is useful for monitoring network-related activities and can help you ensure that your applications and services are running smoothly and securely.

Run the following commands for installation

Create a system user for Node Exporter and download Node Exporter:

sudo useradd — system — no-create-home — shell /bin/false node_exporter

wget https://github.com/prometheus/node_exporter/releases/download/v1.6.1/node_exporter-1.6.1.linux-amd64.tar.gz

2. Extract Node Exporter files, move the binary, and clean up:

tar -xvf node_exporter-1.6.1.linux-amd64.tar.gz
sudo mv node_exporter-1.6.1.linux-amd64/node_exporter /usr/local/bin/
rm -rf node_exporter*

3. Create a systemd unit configuration file for Node Exporter:

sudo nano /etc/systemd/system/node_exporter.service

add the following code to the node_exporter.service file:

provide more detailed information about what might be going wrong. For example:

[Unit]
Description=Node Exporter
After=network.target

[Service]
User=node_exporter
Group=node_exporter
Type=simple
ExecStart=/usr/local/bin/node_exporter[Install]
WantedBy=default.target

4. Enable and start Node Exporter:

sudo useradd -m -s /bin/bash node_exporter

sudo chown node_exporter:node_exporter /usr/local/bin/node_exporter

sudo systemctl daemon-reload
sudo systemctl start node_exporter
sudo systemctl enable node_exporter
sudo systemctl status node_exporter

node exporter service is now running

You can access Node Exporter metrics in Prometheus.

publicip:9100

5. Configure Prometheus Plugin Integration:

go to your EC2 and run →

cd /etc/prometheus

2. you have to edit the prometheus.yml file to moniter anything

scrape_configs:
  - job_name: 'node_exporter'
    static_configs:
      - targets: ['localhost:9100']
  - job_name: 'jenkins'
    metrics_path: '/prometheus'
    static_configs:
      - targets: ['<your-jenkins-ip>:<your-jenkins-port>']

add the above code with proper indentation like this →

press esc+:wq to save and exit

a. Check the validity of the configuration file →

promtool check config /etc/prometheus/prometheus.yml

o/p →success

b. Reload the Prometheus configuration without restarting →

curl -X POST http://localhost:9090/-/reload

go to your prometheus tab again and click on status and select targets you will there is three targets present as we enter in yaml file for moniterning

prometheus targets dashboard

5. Setup Grafana

Install Dependencies:

sudo apt-get update
sudo apt-get install -y apt-transport-https software-properties-common

Add the GPG Key for Grafana:

wget -q -O —  https://packages.grafana.com/gpg.key | sudo apt-key add -

Add the repository for Grafana stable releases:

echo “deb https://packages.grafana.com/oss/deb stable main” | sudo tee — a /etc/apt/sources.list.d/grafana.list

Update the package list , install and start Grafana:

sudo apt-get update
sudo apt-get -y install grafana

sudo systemctl enable grafana-server

sudo systemctl start grafana-server

sudo systemctl status grafana-server

Now go to your ec2 security group and open port no. 3000 in which grafana runs

Go and browse http://public_ip:3000 to access your grafana web interface

username = admin, password =admin

6. Add Prometheus Data Source:

To visualize metrics, you need to add a data source.

Follow these steps:

Click on the gear icon (⚙️) in the left sidebar to open the “Configuration” menu.
Select “Data Sources.”
Click on the “Add data source” button.

Choose “Prometheus” as the data source type.
In the “HTTP” section:
Set the “URL” to http://localhost:9090 (assuming Prometheus is running on the same server).
Click the “Save & Test” button to ensure the data source is working.

7. Import a Dashboard

Importing a dashboard in Grafana is like using a ready-made template to quickly create a set of charts and graphs for monitoring your data, without having to build them from scratch.