Introduction to Cloud Migration

_Cloud migration is the process of moving applications, data, and workloads from an on-premise environment to the cloud. A well-planned migration ensures minimal disruption, maximized performance, and optimized costs.

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Common Cloud Migration Strategies (6 R's)

1. Rehosting ("Lift and Shift"):

   • Directly moving applications to the cloud without significant changes.
   • Best for legacy systems with minimal modification needs.

2. Replatforming ("Lift, Tinker, and Shift"):

   • Making minor optimizations to leverage cloud benefits without major architecture changes.
   • Example: Switching databases to a cloud-managed version.

3. Repurchasing:

   • Replacing the existing application with a cloud-native SaaS solution.
   • Example: Moving from a self-hosted CRM to Salesforce.

4. Refactoring/Re-architecting:

   • Redesigning applications to take full advantage of cloud-native features (e.g., serverless computing, microservices).
   • Best for modernizing applications for scalability and performance.

5. Retiring:

   • Decommissioning outdated or unnecessary systems instead of migrating them.

6. Retaining:

   • Keeping certain applications on-premise for compliance or technical reasons.

Cloud Migration Plan for an On-Premise Application

1. Assess Current Environment

• Inventory existing infrastructure, applications, and dependencies.
• Evaluate application performance, scalability, and resource requirements.
• Identify applications and data suitable for migration.

2. Define Migration Goals

• Key Objectives:
  • Improve scalability and performance.
  • Reduce infrastructure maintenance costs.
  • Increase availability and disaster recovery capabilities.
  • Enhance security and compliance.

3. Choose a Cloud Provider

• AWS, Azure, or Google Cloud Platform based on:
  • Budget.
  • Specific features (e.g., serverless, managed services).
  • Compliance requirements (e.g., GDPR, HIPAA).

4. Select a Migration Strategy

• For this plan, we'll use a Replatforming strategy:
  • Move the on-premise application to a cloud VM (e.g., AWS EC2).
  • Transition the database to a managed service (e.g., Amazon RDS).

5. Migration Plan Steps

Step 1: Pre-Migration Preparation

• Analyze application dependencies and identify services to move.
• Create a migration timeline to minimize downtime.
• Back up all application data to ensure data safety.

Step 2: Set Up the Cloud Environment

• Provision Resources:
  • Create a Virtual Private Cloud (VPC) with public and private subnets.
  • Launch EC2 instances for the application.
  • Configure a load balancer for high availability.
• Database Migration:
  • Set up Amazon RDS for the database.
  • Use AWS Database Migration Service (DMS) to migrate data from on-premise to RDS.

Step 3: Configure Networking and Security

• Set up security groups and firewalls to restrict access.
• Use IAM roles and policies to manage permissions.
• Configure a VPN or Direct Connect for secure communication between on-premise and cloud environments during migration.

Step 4: Data Migration

• Migrate static files to Amazon S3.
• Use AWS Snowball for large datasets or AWS DataSync for continuous file synchronization.

Step 5: Application Migration

• Package the application into containers (if applicable) for easy deployment.
• Use AWS Elastic Beanstalk or Kubernetes for deployment orchestration.
• Test the application in the cloud environment.

Step 6: Testing and Optimization

• Test application performance, latency, and functionality.
• Optimize instance types, storage, and autoscaling policies to reduce costs.

Step 7: Cutover and Go Live

• Schedule a maintenance window for the final cutover.
• Redirect DNS (using Amazon Route 53) to point traffic to the cloud-hosted application.

Step 8: Post-Migration Review

• Monitor the application using Amazon CloudWatch or another monitoring tool.
• Address any performance issues or bottlenecks.
• Optimize resources to ensure cost efficiency.

Example AWS Architecture for the Migrated Application

1. Compute:

   • EC2 instances in an Auto Scaling group.

2. Database:

   • Amazon RDS with Multi-AZ deployment for high availability.

3. Storage:

   • Amazon S3 for static content and backups.

4. Networking:

   • VPC with public and private subnets.
   • Elastic Load Balancer for distributing traffic.

5. Monitoring:

   • Amazon CloudWatch for metrics and alerts.

Terraform Configuration

1. Providers and Variables

provider "aws" {
  region = "us-east-1"  # Change as needed
}

variable "vpc_cidr" {
  default = "10.0.0.0/16"
}

variable "public_subnets" {
  default = ["10.0.1.0/24", "10.0.2.0/24"]
}

variable "private_subnets" {
  default = ["10.0.3.0/24", "10.0.4.0/24"]
}

variable "db_username" {
  default = "admin"  # Set your username
}

variable "db_password" {
  default = "yourpassword"  # Use secrets management for production
}

variable "instance_type" {
  default = "t3.micro"  # Modify as needed
}

2. Networking: VPC, Subnets, Internet Gateway, and Security Groups

resource "aws_vpc" "main" {
  cidr_block = var.vpc_cidr
}

resource "aws_subnet" "public" {
  count             = length(var.public_subnets)
  vpc_id            = aws_vpc.main.id
  cidr_block        = var.public_subnets[count.index]
  map_public_ip_on_launch = true
}

resource "aws_subnet" "private" {
  count      = length(var.private_subnets)
  vpc_id     = aws_vpc.main.id
  cidr_block = var.private_subnets[count.index]
}

resource "aws_internet_gateway" "igw" {
  vpc_id = aws_vpc.main.id
}

resource "aws_route_table" "public_rt" {
  vpc_id = aws_vpc.main.id
}

resource "aws_route" "default_route" {
  route_table_id         = aws_route_table.public_rt.id
  destination_cidr_block = "0.0.0.0/0"
  gateway_id             = aws_internet_gateway.igw.id
}

resource "aws_security_group" "web_sg" {
  vpc_id = aws_vpc.main.id

  ingress {
    from_port   = 80
    to_port     = 80
    protocol    = "tcp"
    cidr_blocks = ["0.0.0.0/0"]
  }

  ingress {
    from_port   = 443
    to_port     = 443
    protocol    = "tcp"
    cidr_blocks = ["0.0.0.0/0"]
  }

  egress {
    from_port   = 0
    to_port     = 0
    protocol    = "-1"
    cidr_blocks = ["0.0.0.0/0"]
  }
}

resource "aws_security_group" "db_sg" {
  vpc_id = aws_vpc.main.id

  ingress {
    from_port   = 3306
    to_port     = 3306
    protocol    = "tcp"
    security_groups = [aws_security_group.web_sg.id]
  }

  egress {
    from_port   = 0
    to_port     = 0
    protocol    = "-1"
    cidr_blocks = ["0.0.0.0/0"]
  }
}

3. Compute: EC2 Instances with Auto Scaling

resource "aws_launch_configuration" "app" {
  name          = "app-launch-configuration"
  image_id      = "ami-0c02fb55956c7d316"  # Amazon Linux 2
  instance_type = var.instance_type
  security_groups = [aws_security_group.web_sg.id]

  lifecycle {
    create_before_destroy = true
  }
}

resource "aws_autoscaling_group" "app_asg" {
  desired_capacity     = 2
  max_size             = 3
  min_size             = 1
  launch_configuration = aws_launch_configuration.app.id
  vpc_zone_identifier  = aws_subnet.public[*].id

  tag {
    key                 = "Name"
    value               = "app-instance"
    propagate_at_launch = true
  }
}

4. Database: RDS Instance

resource "aws_db_subnet_group" "db" {
  name       = "db-subnet-group"
  subnet_ids = aws_subnet.private[*].id
}

resource "aws_db_instance" "app_db" {
  allocated_storage    = 20
  engine               = "mysql"
  instance_class       = "db.t3.micro"
  name                 = "appdb"
  username             = var.db_username
  password             = var.db_password
  vpc_security_group_ids = [aws_security_group.db_sg.id]
  db_subnet_group_name = aws_db_subnet_group.db.name
  multi_az             = true
  skip_final_snapshot  = true
}

5. Storage: S3 Bucket for Static Files

resource "aws_s3_bucket" "static" {
  bucket = "app-static-files-${random_id.bucket_id.hex}"
  acl    = "public-read"

  tags = {
    Name = "StaticFilesBucket"
  }
}

resource "random_id" "bucket_id" {
  byte_length = 8
}

6. Load Balancer

resource "aws_lb" "app_lb" {
  name               = "app-load-balancer"
  internal           = false
  load_balancer_type = "application"
  security_groups    = [aws_security_group.web_sg.id]
  subnets            = aws_subnet.public[*].id
}

resource "aws_lb_target_group" "app_tg" {
  name     = "app-target-group"
  port     = 80
  protocol = "HTTP"
  vpc_id   = aws_vpc.main.id
}

resource "aws_lb_listener" "http_listener" {
  load_balancer_arn = aws_lb.app_lb.arn
  port              = 80
  protocol          = "HTTP"
  default_action {
    type             = "forward"
    target_group_arn = aws_lb_target_group.app_tg.arn
  }
}

resource "aws_autoscaling_attachment" "asg_attachment" {
  autoscaling_group_name = aws_autoscaling_group.app_asg.name
  target_group_arn       = aws_lb_target_group.app_tg.arn
}

How to Deploy This Configuration

1. Install Terraform on your local machine.
2. Save the configuration in a .tf file (e.g., main.tf).
3. Initialize Terraform:

   terraform init

1. Validate the configuration:

   terraform validate

1. Plan the deployment:

   terraform plan

1. Deploy the resources:

   terraform apply

Summary

Migrating an on-premise application to the cloud requires careful planning, execution, and testing. By following a structured migration strategy like the one outlined above, organizations can achieve improved scalability, reliability, and cost savings while minimizing downtime and risks.

Happy Learning !!!