The Challenge
Mainframe to AWS migration is the ultimate “Lift and Shift” vs. “Refactor” debate—and 45% of these projects fail outright. AWS offers specific tools (AWS Mainframe Modernization service) that support both patterns, but the architectural implications are vastly different. Before committing, we recommend a Cloud Readiness Assessment to validate your workloads are suitable for AWS infrastructure.
Technical Deep Dive
1. The “Replatform” Pattern (Emulation)
This involves running your existing COBOL/PL1 code on x86 instances (EC2) using a runtime emulator (like Micro Focus or Blu Age). For language-specific guidance, see our COBOL Migration Services deep dive.
- Pros: Fastest path to cloud; preserves business logic exactly.
- Cons: You still have COBOL code; you don’t get full cloud-native benefits (serverless, microservices).
- AWS Service: AWS Mainframe Modernization (Replatform with Micro Focus).
2. The “Refactor” Pattern (Automated Conversion)
Converting legacy code to Java/Spring Boot to run on containers (EKS) or Lambda.
- Pros: Eliminates technical debt; opens talent pool; enables true agility.
- Cons: Higher initial risk; requires rigorous testing.
- AWS Service: AWS Mainframe Modernization (Refactor with Blu Age).
3. Data Strategy: VSAM to DynamoDB
Mapping flat-file VSAM structures to a NoSQL store like DynamoDB can unlock massive performance gains for read-heavy workloads.
Pattern: Use Change Data Capture (CDC) tools (like AWS DMS or Qlik Replicate) to sync mainframe data to AWS in real-time during the transition period. This allows you to build new “Read Models” on AWS while the “Write Model” stays on the mainframe until cutover.
Migration Architecture: Before & After
flowchart LR
subgraph "Legacy State"
MF["IBM z/OS Mainframe"]
COBOL["COBOL/PL1 Apps"]
CICS["CICS Transactions"]
DB2["DB2 Database"]
VSAM["VSAM Files"]
JCL["JCL Batch Jobs"]
COBOL --> CICS
CICS --> DB2
COBOL --> VSAM
JCL --> COBOL
end
subgraph "AWS Target State"
direction TB
subgraph "Compute"
EC2["EC2 + Micro Focus"]
EKS["EKS Containers"]
Lambda["Lambda Functions"]
end
subgraph "Data"
RDS["RDS PostgreSQL"]
DDB["DynamoDB"]
S3["S3 Data Lake"]
end
subgraph "Integration"
API["API Gateway"]
SF["Step Functions"]
MQ["Amazon MQ"]
end
EC2 --> RDS
EKS --> DDB
Lambda --> S3
API --> EKS
SF --> Lambda
end
MF -.->|"CDC Sync"| RDS
MF -.->|"Replatform"| EC2
MF -.->|"Refactor"| EKS
Key architectural decisions:
- Replatform path: COBOL runs on EC2 with Micro Focus emulator → fastest, keeps technical debt
- Refactor path: Convert to Java/containers on EKS → slower, eliminates debt
- Data sync: CDC keeps both systems in sync during 6-18 month parallel run
Blu Age vs Micro Focus: Which Conversion Tool?
| Factor | Blu Age (AWS Native) | Micro Focus (Enterprise Server) |
|---|---|---|
| Approach | Automated COBOL→Java conversion | COBOL emulation on x86 |
| Output | Native Java/Spring Boot | COBOL running on Linux/Windows |
| AWS Integration | Deep (built into AWS MM service) | Good (runs on EC2) |
| Best For | Long-term modernization, talent | Fast exit, preserve logic exactly |
| Risk Level | Higher (code transformation) | Lower (same code, new runtime) |
| Ongoing Costs | Lower (no emulator license) | Higher ($500K-$2M/year licensing) |
| Timeline | 2-4 years | 6-18 months |
Our take: Use Micro Focus if you need to exit the data center in <18 months (hardware refresh deadline). Use Blu Age if you have 2+ years and want to eliminate COBOL entirely.
Compliance Considerations for Regulated Industries
For banking, insurance, and government mainframe migrations:
| Requirement | Mainframe Approach | AWS Equivalent |
|---|---|---|
| SOX Audit Trail | SMF records, RACF logs | CloudTrail + Config Rules |
| PCI-DSS Data Security | RACF encryption, tape vaults | KMS encryption, S3 Glacier |
| HIPAA PHI Protection | DB2 row-level security | RDS IAM policies, VPC isolation |
| Disaster Recovery | GDPS, tape replication | Multi-AZ, Cross-Region replication |
| Change Management | Manual CAB approvals | AWS Service Catalog + approval workflows |
Critical: Your compliance team must sign off on the AWS control mappings BEFORE migration begins. Retrofitting compliance is 3x more expensive.
AWS Migration Acceleration Program (MAP) Credits
AWS MAP provides funding credits for qualifying mainframe migrations:
| Deal Size | Typical Credits | Requirements |
|---|---|---|
| $1M-$5M migration | $100K-$300K | Partner must be MAP-certified |
| $5M-$15M migration | $300K-$750K | Workload assessment required |
| $15M+ migration | $750K-$1.5M+ | Executive sponsorship, multi-year commit |
How to qualify:
- Engage an AWS Partner with MAP certification (TCS, DXC, Infosys all qualify)
- Complete AWS Migration Readiness Assessment (MRA)
- Commit to 3-year Reserved Instances or Savings Plans
- Document workload inventory and migration plan
Pro tip: MAP credits can offset parallel run costs—negotiate this upfront.
How to Choose a Mainframe to AWS Migration Partner
If you have massive data volumes (50TB+): TCS. Their MasterCraft suite is proven for handling petabyte-scale data migrations for Global 2000 firms.
If you want a “Lift & Shift” (Replatform) first: Heirloom Computing. Their PaaS solution allows you to run existing COBOL code on AWS Elastic Beanstalk with minimal changes.
If you need risk-averse, steady hands: DXC Technology or Infosys. They have deep heritage in mainframe operations and won’t break your core banking system.
If you want to refactor to microservices: SoftServe. They specialize in cloud-native development and can help break the monolith into AWS Lambda/Fargate services.
If you need business process modernization: Cognizant. They focus on optimizing the business workflows, not just the code.
Red flags:
- Partners who ignore “Data Egress Costs” in their TCO model
- No experience with “Hybrid State” latency management (Mainframe ↔ AWS calls)
- Suggesting a “Big Bang” cutover for a system with >1M daily transactions
- Lack of specific expertise with AWS Mainframe Modernization service
- No references from banking/insurance mainframe migrations
How We Select Partners
Modernization Intel evaluates mainframe migration partners based on objective criteria, not pay-to-play rankings:
| Criteria | Weight | What We Look For |
|---|---|---|
| AWS Competency | 25% | AWS Migration Competency badge, Mainframe Modernization specialization |
| Mainframe Heritage | 25% | Years of COBOL/JCL/CICS experience, retired IBM talent on staff |
| Verified Case Studies | 20% | Named clients, published outcomes, referenceable projects |
| Pricing Transparency | 15% | Published rate cards, fixed-price options, no hidden fees |
| Tool Partnerships | 15% | Blu Age, Micro Focus, or Heirloom certifications |
Our commercial model: We receive a referral fee from partners when you engage them through our shortlist. This doesn’t affect our rankings—partners cannot pay for placement. We only recommend firms we’d hire ourselves. See our Modernization Strategy page for how we approach vendor-neutral guidance.
When to Hire Mainframe to AWS Migration Services
1. Hardware Refresh Cycle ($5M+ CapEx)
Your IBM z14/z15 lease is expiring. Upgrading to z16 will cost $10M+ in capital expenditure. The CFO wants to move to OpEx (Pay-as-you-go).
Trigger: Lease renewal notice arrives; CFO mandates “No new data centers.”
2. COBOL Talent Crisis
Your average mainframe developer is 58 years old. You have zero junior developers learning JCL or CICS. The risk of knowledge loss is existential.
Trigger: Key architect retires; inability to fix a critical bug because “nobody knows how that module works.”
3. Agility & Time-to-Market
Competitors deploy features daily. Your mainframe release cycle is quarterly. You cannot integrate with modern mobile apps or 3rd party APIs easily.
Trigger: Business loses a major deal because the product couldn’t support a modern API integration in time.
4. Cost of MIPS (Software Licensing)
IBM MLC (Monthly License Charges) and ISV software (BMC, CA/Broadcom) costs are increasing annually. You are paying millions just to keep the lights on.
Trigger: Software licensing costs exceed 50% of the total IT budget.
5. Data Analytics Needs
Your data is locked in VSAM files. You want to run Machine Learning or Real-time Analytics, but you can’t get the data out fast enough without impacting transaction performance.
Trigger: Data Science team complains they can’t access core customer data; need for real-time fraud detection.
Hidden Costs Most Partners Won’t Tell You
Beyond the TCO Calculator above, watch for these costs that don’t appear in vendor proposals:
| Hidden Cost | Impact | Mitigation |
|---|---|---|
| Parallel Run | Pay for Mainframe AND AWS for 6-12 months | Negotiate AWS credits (MAP program) |
| Data Egress Fees | $0.09/GB out of AWS adds up fast | Use Direct Connect, minimize hybrid sync |
| Emulator Licensing | Micro Focus/Heirloom fees are ongoing | Factor into 5-year TCO, not just migration |
| Skills Gap | AWS architects cost $180K+; your COBOL team needs retraining | Budget 10% for training & knowledge transfer |
| Testing | Mainframe precision (18-digit decimals) requires exhaustive regression | Automate early; budget 30-40% of project cost |
Tip: If you’re also evaluating Azure, see our Mainframe to Azure comparison to understand the trade-offs.
Post-Migration: What Happens After Go-Live
Months 1-3: Hypercare
- Performance Tuning: Tune IOPS on EBS volumes and RDS instances. Mainframe I/O is incredibly fast; AWS needs right-sizing.
- Cost Monitoring: Watch out for unexpected Data Transfer costs. Set up AWS Cost Explorer alerts immediately.
Months 4-6: Incremental Modernization
- Strangler Fig: Start breaking the monolithic Java/COBOL code on AWS into microservices.
- API Enablement: Expose core business logic via API Gateway to internal developers.
- Cloud-Native Adoption: Replace batch jobs with event-driven Lambda functions where appropriate.