From GitHub to Production: Streamlining Deployment with CI/CD , LB and AS

yuvi1228

Yuvraj Thapa Chhetri

Posted on October 19, 2024

From GitHub to Production: Streamlining Deployment with CI/CD , LB and AS

Introduction

Recently, I deployed an application to AWS Cloud using GitHub, utilizing an automated CI/CD pipeline on AWS. In this blog, I focused on using AWS Code Pipeline to ensure that whenever a developer pushes code to GitHub, it is automatically deployed to the server. I have outlined the step-by-step process to set this up, making it easier for teams to streamline their deployment workflows.

Here is architecture for deployment application using AWS Code Pipeline
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Why You Should Implement Application Deployment in Launch Templates ?
In today's digital landscape, businesses need to deploy applications quickly and seamlessly. Utilizing a CI/CD (Continuous Integration/Continuous Deployment) pipeline allows us to automate the process from development to production. Here are some key benefits:

  1. Speed and Efficiency: CI/CD accelerates the development and deployment process, enabling developers to release code faster.

  2. Quality Assurance: Automated testing helps identify bugs and issues early, improving the overall quality of the application.

  3. Scalability: With auto-scaling features, applications can adjust resources based on demand, optimizing resource utilization and controlling costs.

  4. Reliability: Load balancing efficiently distributes traffic, minimizing downtime and enhancing user experience.

  5. Cost-effectiveness: Automated processes and resource scaling lead to lower operational costs, as you only use resources as needed.

Now, Let's start with practical

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First, we have to create Launch Template

Go to launch template under Instances and click on create launch template

  • Launch Template Name: write your launch template name
  • Template version description: v1
  • In OS and Images tab: Click on quick start and select your OS according to your requirement
  • In instances type: Select Free tire [t2.micro] or you can select your requirement
  • Key pair: Create your key pair and keep it securely
  • Network setting: leave as execute
  • Firewall (Security Groups):Select create security group

---Security Group Name: write security group name
---Description: allow ssh and http (s)
---VPC: you can select your own VPC or leave as execute

  • Click on add security groups rule and add three security rules:

---Type: ssh / http /https
---Source type: Anywhere  

  • Expand Advance detail In IAM instance profile: Select new IAM Profile and create role

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  • After select create role:

----Select trusted entity: AWS Service
----Use Case: EC2 and then click on Next button
----Add permission tab: search codedeploy and select
AmazonEC2RoleforAWSCodeDeploy

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  • In role detail tab: write role name and description then click on create role.

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  • After create role come back advanced details under launch template and select your role

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  • Scroll down and search for User data and write some script:

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NOTE: Change the underline text according to your region

  • Now, Create launch template

After launch template select Auto scaling Groups

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Auto scaling configuration

---Name: write your ASG name
---Launch Template: Select your template

  • Version: Latest (1)
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  • Click on next

  • Under Network setting

---Select VPC: select default VPC or select your own VPC
---Availability Zones and subnets: Select minimum two subnets like 1a
and 1b

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  • Click Next
  • Under Load balancing tab:

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  • Select Attach a new load balancer

---Load balancer type: Network Load Balancer
---Load balancer name: write your LB name
---Load balancer scheme: Internet-facing

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  • Under Listeners and routing:

---Protocol: TCP
---Port: 80
---Default routing (forward to): create a target group
---New target group name: Give your TG name

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  • Under Group Size

---Desired capacity: 0
---Min desired capacity: 0
---Max desired capacity: 0

  • Select target tracking scaling policy

---Scaling policy name: Target tracking policy
---Metric type: Average CPU utilization
---Target Value: 50

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  • Then click on create button and you can see there is no instances and desired capacity.

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Now, go to CodeDeploy

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  • Select Application under deploy tab and create application

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  • Under Application Configuration:

---Application name: write your application name
---Compute platform: Select EC2/On-premises

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  • Now, after create application click on create deployment group

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  • Now, go back IAM dashboard and create role for deployment group

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  • In trusted entity type > select AWS service

  • In use case > select CodeDeploy

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  • Enter the role name

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  • Select View role

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  • then copy the ARN link of role

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  • Paste your ARN in service role tab under Deployment group

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  • Now Under Environment Configuration tab

  • Mark on Amazon EC2 Auto scaling Groups

  • Select your ASG

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  • In Deployment Setting

---Deployment Configuration : Select CodeDeployDefault.OneAtAtTime

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  • In Load Balancer Tab
  • Mark on Enable Load balancing
  • Select your target group of Application LB or Network LB
  • Now, Go to Pipelines under pipelines side nav bar

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  • In pipeline setting

---Pipeline name: write your name
---Pipeline type : Select v2
---Execution mode: select Queued (pipeline type V2 required)
---Service role: Select New service role

  • Role name automatically appear in your role name box

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  • Under source Tab

---Source Provider: GitHub (Version 2)]

  • Click on connect to GitHub

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  • Create Connection

---Connection name: Give your connection name

  • Then click on connect to GitHub button

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  • Click on Install new app

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  • Now, Login github

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  • Mark on Only select repositories

  • Select your repositories

  • Then click on install

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  • now, click on connect

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  • ensure your repository name and default Branch is correct

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  • Under Trigger Tab

  • Select No filter

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  • Skip Build Stage

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Now, Configuration Deploy

Deploy provider: AWS CodeDeploy
Region: Asia Pacific (Singapore)
Application name: select your Application name
Deployment group: select your Deployment group

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  • Click on deploy button

  • Then, your code will be automatically deploying
    .
    If there will error given as a picture below So, we have to configure auto scaling desired capacity.

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  • Search EC2 > select auto scaling group

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  • select your ASG and change desired capacity value given as a picture below

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  • again, go to CodePipeline and retry stage

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  • After deploy go to load balancer dashboard and copy DNS name and paste it any browser your application will be working.

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Your application is ready now

Finally , we successfully deploy application from github to cloud. Deploying applications through a CI/CD pipeline has become an essential practice in today’s competitive market. This approach not only enhances your development process but also provides better service to your end-users.

💖 💪 🙅 🚩
yuvi1228
Yuvraj Thapa Chhetri

Posted on October 19, 2024

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