AWS Mainframe Migration: The Basics and a Quick Tutorial

Understanding the AWS Mainframe Modernization Solution

Amazon Web Services (AWS) provides an integrated solution for migrating mainframe workloads to the cloud. IT includes tools and services to assess, replatform, and refactor mainframe applications, along with a managed runtime environment and developer tooling.

Key components of AWS Mainframe Modernization include:

Assessment tools: AWS provides capabilities to assess the existing mainframe environment, helping organizations plan their modernization projects in terms of scope, feasibility, and strategy.
Refactoring with AWS Blu Age: Applications can be refactored to convert legacy codebases into modern, multi-tier Java-based applications. This process preserves functional behavior while generating API-enabled backends and web-based frontends, accelerating modernization through automation.
Replatforming with Micro Focus Enterprise Suite: Replatforming enables organizations to migrate applications with minimal code changes. This pattern preserves existing programming languages and structures while moving the system to cloud-managed services and adopting modern DevOps practices.
AWS Blu Insights integration: Available through the AWS Management Console, Blu Insights offers codebase analysis and transformation tools with simplified access via single sign-on.
Rocket Developer IDE: A web-based integrated development environment is available on-demand, supporting features like smart editing, debugging, and instant compilation for efficient development workflows.
Rocket managed runtime environment: AWS provides a self-healing, auto-scaling runtime environment that continuously monitors workloads to ensure reliability and performance.

AWS Mainframe Modernization Pricing

AWS Mainframe Modernization cannot be used “off the shelf”; it is usually purchased via AWS Professional Services or integration partners. The following pricing can give you an idea of the Amazon resource costs involved in running the solution. You can choose between on-demand pricing for short-term needs or discounted committed plans for long-running workloads.

Blu Age Runtime and Tools

For the Blu Age runtime, on-demand pricing is $0.31 per AWS CPU core per hour. This rate also applies per 2 AWS virtual CPUs for serverless compute environments. Instance pricing ranges from $0.31/hour (M2.m6i.large) up to $9.92/hour (M2.m6i.16xlarge), applicable across several instance families including m6i, c6i, and r5.

Blu Age analysis, developer, and build tools incur no additional cost, though standard AWS infrastructure charges apply.

Blu Age Transformation Center, which automates refactoring, is priced at $0.103 per line of code (LOC) after a free tier of 120,000 LOC. Charges apply only to newly converted or modified lines within a project.

Rocket Runtime and Tools

The Rocket runtime (Enterprise Server) is priced at $5.55 per AWS CPU core per hour. Instances range from $5.55/hour (M2.m6i.large) up to $88.80/hour (M2.m6i.8xlarge).

Rocket Developer (Enterprise Developer) costs $2.14 per AWS CPU core per hour. Instance pricing ranges from $2.14/hour (large) to $34.24/hour (8xlarge), with some variations depending on stream instance types.

Rocket analyzer and build tools are provided at no additional charge, with standard AWS infrastructure costs applied.

Charges for Other AWS Services and Resources

Infrastructure components: Resources running on EC2, S3, RDS, and other services may generate additional costs depending on the service configuration.
Storage: Storing application data in services like Amazon FSx, EFS, Aurora, or RDS is billed separately.
Application testing: Charged at $0.06 per minute for test execution time and $0.99 per GB for data comparison.
Data replication: Costs $60/GB for IBM z/OS and $30/GB for IBM i systems.
File transfer: Billed at $1.30/GB for data transferred from IBM z/OS to Amazon S3.
Code conversion (mLogica): Conversion from assembler to COBOL is priced at $2.75 per line of code.

Related content: Read our guide to mainframe modernization tools

Tutorial: AWS Mainframe Migration with Managed Runtime and AWS Blu Age

This tutorial walks through deploying a demo application using the AWS Mainframe Modernization managed runtime environment for AWS Blu Age. You’ll upload the demo app, define its configuration, and deploy and test it in the runtime. These instructions are adapted from the AWS documentation.

Step 1: Upload the Demo Application

Start by uploading the PlanetsDemo-v4.zip file to an S3 bucket in the same AWS region where you’ll deploy the application. For example:

aws s3 cp PlanetsDemo-v4.zip s3://planets-demo/v1/

Ensure the bucket has a folder structure, such as v1/, to organize the archive.

Step 2: Create the Application Definition

Create a JSON file that defines the source location and runtime settings. Save this as a text file locally, such as planets-app-definition.json.

{
  "template-version": "2.0",
  "source-locations": [{
    "source-id": "s3-source",
    "source-type": "s3",
    "properties": {
      "s3-bucket": "planets-demo",
      "s3-key-prefix": "v1"
    }
  }],
  "definition": {
    "listeners": [{
      "port": 8196,
      "type": "http"
    }],
    "ba-application": {
      "app-location": "${s3-source}/PlanetsDemo-v4.zip"
    }
  }
}

Step 3: Create the Runtime Environment

In the AWS Mainframe Modernization console:

Navigate to Environments and click Create environment.
Enter a name and select AWS Blu Age as the engine.
Choose Standalone runtime environment.
Under Security and network:
- Allow public access.
- Choose the default VPC and two subnets that support public IPs.
- Ensure the security group permits traffic on port 8196 from your browser IP.

Step 4: Create the Application

Go to Applications and choose Create application.
Provide a name and select AWS Blu Age as the engine.
On the configuration page, paste your JSON definition from Step 2.
Review and create the application.

If creation fails, double-check your S3 bucket name and path for case sensitivity.

Step 5: Deploy the Application

Wait for both the environment and application to show an Available status.
Select the environment, then click Deploy application.
Choose the application and version, then confirm the deployment.

Step 6: Start the Application

Navigate to your application’s Deployments tab.
Wait for the deployment to succeed.
Select Actions > Start application.

Step 7: Access the Application

Once running:

Copy the DNS hostname from the application info.
Open a browser and navigate to:

http://{hostname}:8196/PlanetsDemo-web-1.0.0/

Replace {hostname} with your actual DNS value.

If inaccessible, check your security group’s inbound rule or troubleshoot based on AWS guidelines.

Step 8: Test the Application

On the JICS screen, enter PINQ and press Enter.
Type a planet name, such as Earth, and press Enter again.
The application should return relevant details for the planet.

This confirms successful deployment and functionality within the managed runtime environment.Related content: Read our guide to mainframe migration