5 Phases of Legacy System Migration + Common Strategies

Legacy systems still power critical operations in finance, healthcare, and government. But they’re getting harder to maintain, slower to adapt, and riskier to secure. In fact, 88% of organizations say legacy tech is holding them back. 

‍

Legacy system migration helps turn those systems into a foundation for future development. It makes older platforms easier to integrate, easier to maintain, and better equipped to support new tools and use cases.

‍

In this article, we’ll cover: 

• The 5 phases of legacy migration
• Proven strategies to reduce migration risk and cost
• How low-code platforms like Superblocks accelerate modernization

Let’s start with what legacy system migration involves.

What is legacy system migration?

Legacy system migration is the process of updating or moving an outdated software system to a modern environment.

‍

Legacy migrations involve various approaches, including:

• Rehosting the system “as is” on new infrastructure
• Refactoring its code for the cloud
• Completely replacing it with a new application

Common examples of legacy systems

A legacy system refers to any application, database, or infrastructure that no longer supports current business needs. 

‍

Common examples of these systems are:

• COBOL-based mainframe apps.
• On-Premises ERP Systems, like SAP R/3 or early Oracle E-Business Suite, deployed in company data centers.
• Legacy CRM software, for example, Siebel CRM, which was widely used before cloud CRMs. 
• Specialized software from vendors that is now outdated or no longer supported. 

Why organizations hesitate to migrate legacy systems

It’s common for organizations to hesitate when it comes to legacy migration. Key reasons include:

• Comfort with the status quo: Change introduces uncertainty, which feels riskier than maintaining what's familiar.
• High initial costs and effort: Migration requires a budget for new tools, training, and possible downtime. Executives hesitate to commit without a clear return on investment (ROI).
• System dependencies: Legacy platforms often integrate with multiple other tools. Teams worry that removing one part could compromise the integrity of others.
• Skill shortages: Older systems rely on skills like COBOL and mainframe support. Those specialists are retiring, and few replacements exist.

For a deeper look at why IT transformation efforts stall and how to unblock them, read this breakdown of IT transformation strategy.

The risks of sticking with legacy systems

The longer a company waits, the more fragile and expensive legacy systems become. This is because legacy systems have:

• High maintenance burden: They cost more to run each year, need rare skills, and custom fixes to stay functional.
• Integration gaps: They often don’t support modern APIs or data formats. Teams must move data manually or build workarounds.
• Scalability limits: They slow down under pressure and are expensive to scale.
• Security flaws: Most systems don’t get regular updates or security patches.
• Talent shortages: Legacy tech depends on retiring experts. Losing one key person can leave teams unable to maintain or change the system.
• Opportunity cost: They may not support real-time data, mobile apps, or AI. Workarounds waste time and stall progress.

How do I know if my legacy system should be replaced or modernized?

One crucial question is whether to completely replace a legacy system with a new system or SaaS product or to modernize it in place through updates, refactoring, or replatforming.

‍

The right choice depends on several factors:

• Business fit: If the system blocks key goals or no longer fits how the business operates, it should be replaced. If it still does the job but needs updates, modernization makes more sense.‍
• Technical condition: Replace systems that are unstable, insecure, or unsupported. Modernize systems with a solid foundation that need better performance or integrations.‍
• Cost comparison: Compare the ongoing maintenance against migration costs to see which option is cheaper. In many cases, legacy systems often cost more to keep than to modernize.‍
• Compliance needs: If the system can’t meet current regulations or audit requirements, replacement may be the only safe option.‍
• Talent availability: If no one on your team can maintain or extend the system, replacement is usually the safer bet.

5 phases of a legacy system migration

Migrating a legacy system is easier to manage and less risky when broken into distinct phases. 

‍

The five main phases are:

Phase 1: Assessment & audit 

Start by mapping the system’s architecture, data, and external connections. Interview the teams who use it every day. What slows them down? What’s broken or missing?

‍

Some issues are obvious, like outdated tech or unsupported formats. Others surface only when you trace workflows or review compliance requirements. This process reveals the system’s scope, weaknesses, and what any modernization must address.

Phase 2: Planning & architecture

Next, create a detailed migration plan and target architecture.

‍

Key planning steps include:

• Choose a migration strategy: Use the assessment to decide whether each component should be rehosted, refactored, replatformed, or replaced.
• Define the target architecture: If moving to the cloud, choose your provider (AWS, Azure, GCP) and confirm compatibility with systems and data.
• Develop a project plan: Set timelines, allocate resources, and align the budget with business and technical goals.
• Identify risks and backups: List possible failure points, like slow data transfers or broken dependencies. Create fallback plans.
• Prepare the landing zone: Build the new infrastructure first. Confirm it meets security, capacity, and compliance requirements.

Read more: How to design a future-ready enterprise application architecture.

Phase 3: Migration execution 

With the plan in place, begin migration in controlled steps. 

‍

This phase usually includes:

• Data migration: Extract and convert data from the legacy system into formats suitable for the new system. You may need to transform data schemas, clean up inconsistencies, and then load data into the new environment.
• Application or code migration: If you are porting over app code, this is where you deploy the legacy application. In a rehost, you move the app and data as-is to the new infrastructure. The process may be as straightforward as copying virtual machine images to the cloud. In a refactor, developers rewrite portions of code, then redeploy the app.
• Integration and cutover: Connect the new system to tools, APIs, and services. Then switch live users over. Some teams cut over all at once. Others run both systems in parallel.

Phase 4: Testing & validation

Run tests to confirm the migration worked and nothing broke along the way.

‍

Key types of testing include:

• Functional testing: Verify the system works as expected and features perform correctly.
• Data validation: Compare the new and old systems to ensure every record transferred accurately.
• Performance testing: Measure whether the new system meets or exceeds the performance of the old one.
• User Acceptance Testing (UAT): Have real users test real scenarios to verify usability and process support.

Phase 5: Optimization & ongoing integration 

Even after going live, closely monitor the system for a while to ensure you haven’t introduced new problems.

‍

Key tasks in this phase are:

• Tuning and optimization: Refine performance based on test results and user feedback.
• Training and Change management: Train users and IT staff on the new system. Good documentation and training sessions will ease the transition.
• Monitoring and support setup: Implement monitoring tools to keep an eye on the new system’s health. Also, adjust support processes if operations are shifting from legacy admins to a cloud or DevOps team.
• Continuous integration: Explore additional opportunities to integrate the new system with other modern tools. Perhaps now you can use an API gateway or analytics platform with the data.
• Post-migration audit: After some weeks or months, conduct a post-mortem and audit. Verify that all data was transferred correctly, that no security or compliance holes were introduced, and that the system is meeting KPIs.
• Retire legacy components: After confirming the new system is stable, shut down the old one. Archive all required documents for compliance, then decommission servers and cancel support contracts to minimize overhead.
  

Common legacy system migration challenges

Even well-planned migrations hit snags. Most problems fall into a few predictable categories:

• Data mapping and inconsistencies: Legacy data is often messy. Formats may be outdated, fields inconsistent, and records duplicated. Mapping that data to a new system takes time.
• Downtime and user disruption: Poorly timed cutovers can break workflows. If users lose access or encounter bugs, confidence in the new system drops quickly.
• Vendor lock-in risks: Some legacy tools use proprietary formats or licensing terms that restrict how and when data can be moved. These constraints often require legal and technical work to resolve.
• Internal resistance and training: Some teams prefer the old system because they are familiar with it. Others fear losing control. 
• Integration with modern tools: After migration, your teams may need to build custom APIs, middleware, or adapters to connect the new system to your existing stack.

Which migration strategy is right for your enterprise?

The right strategy depends on what your legacy system does, how well it still performs, and how much change your team can absorb.

‍

Here are the most common options:

• Rehosting (lift and shift): Move the system to a new environment without changing the code. This is fast and low-risk, but it doesn’t fix underlying technical debt. Works best for stable apps that just need new infrastructure.
• Replatforming: Move to a new platform with minor tweaks, like swapping an on-prem database for a managed cloud version. This adds performance and scalability without a full rebuild.
• Refactoring: Rewrite parts of the code to improve structure or performance. This takes more time but creates a system that’s easier to maintain and extend.
• Replacing with SaaS: Retire the old system and switch to a modern cloud product. This often makes sense for commodity use cases like CRM or HR, but you’ll need to adjust workflows to fit the new tool.
• Wrapping with APIs (strangler pattern): Expose parts of the legacy system through APIs, then gradually replace them with modern services. This lets you modernize in stages without a full cutover.

How Superblocks supports legacy migration

Superblocks is an AI-native enterprise app platform for building internal software fast and securely. It adds immediate value without requiring a full rip-and-replace.

‍

Teams use it to modernize legacy environments in the following ways:

• Building new UIs on top of legacy databases: Use Clark AI to generate internal apps on top of legacy databases. It can suggest queries, build interfaces, and connect data sources while respecting your design systems and permissioning structures. This makes it easy to replace outdated forms or admin tools with clean web apps.
• Exposing legacy data and functions via REST APIs: Build and deploy API endpoints that interface with legacy systems. This effectively “wraps” the legacy system in a modern API layer, so newer apps and services can consume that data without dealing with the legacy stack.
• Automate workflows tied to legacy and cloud simultaneously: Build automations to run jobs that pull from both old and new systems. This is particularly useful during transition periods when both systems need to remain in sync.
• Add governance and observability without added infrastructure: Enforce RBAC, SSO, and audit logging across all apps built on Superblocks. You can track usage and control access without adding new infrastructure.
• Deploy on-prem for data control: Use Superblocks’ on-prem agent to keep sensitive data inside your network. This supports compliance needs while extending legacy data to cloud interfaces.
• Use code when needed: You aren’t limited by the platform’s out-of-the-box connectors. If a legacy system requires a custom script or query, you can embed it using JavaScript, Python, and SQL.

The smart way to move legacy systems to the cloud

Migrating legacy systems to the cloud is a common modernization goal. The cloud offers scalability, on-demand resources, and managed services. But not every legacy workload is cloud-ready. 

‍

Here’s how to make the move with less risk and more long-term value:

• Start with a cloud readiness assessment: Review technical dependencies, security constraints, and data sensitivity. If a system needs local latency or uses unsupported hardware, it may not be a good fit, yet.
• Choose cloud-native or hybrid deployment: Go all-in on cloud when possible. If not, start with a hybrid setup that connects cloud services to on-prem systems.
• Use iPaaS and low-code tools to bridge gaps: Platforms like Superblocks and MuleSoft connect legacy systems to cloud apps. Use them to handle integrations without custom development.
• Prepare the environment before migrating: Set up access controls, backups, monitoring, and compliance policies before migration. This helps you avoid issues post-deployment.

4 tips for a smooth legacy to cloud migration

Once you pick a strategy, follow these best practices:

1. Focus on high-impact use cases first: Start with migrations that show measurable ROI. Quick wins help justify the broader effort and build stakeholder support.
2. Run pilot migrations before scaling: Test your process with a smaller system or dataset. Validate integrations, performance, and rollback steps before committing to production.
3. Get stakeholders aligned early: Bring IT, security, compliance, and business leaders into the plan.
4. Set up monitoring from day one: Track performance, usage, and failures in real time. Good observability helps catch issues early and supports a clean handoff from project to operations.

Which tools support legacy software migration?

No single tool solves legacy migration. Most teams use a mix based on what they’re migrating and how fast they need to move.

‍

Teams use:

• iPaaS tools (e.g., MuleSoft, Boomi): Tools like MuleSoft and Boomi help sync data between systems, translate formats, and expose legacy functions as APIs. Ideal for connecting on-prem and cloud during hybrid phases.
• Low-code platforms (e.g., Superblocks): Low-code tools let you build internal apps fast, often on top of legacy databases. They help replace old UIs, automate workflows, and gradually shift logic away from legacy systems.
• ETL and data pipeline tools: Informatica, Talend, or Azure Data Factory are built to move and transform large datasets. Use them when your migration involves bulk data transfers, reformatting, or loading into cloud warehouses.
• API gateways and service meshes: Tools like Kong, Apigee, or AWS API Gateway let you expose legacy functions as modern, secure APIs. They’re especially useful when using the strangler pattern to phase out legacy modules.

Modernize legacy systems with Superblocks

Superblocks helps legacy modernization by providing a platform to quickly build new software layers on top of legacy systems without replacing the backend or adding new infrastructure. It’s a practical way to extend functionality and reduce migration risk without slowing down delivery.

‍

This is possible thanks to our extensive set of features:

• Flexible development model: Use Clark AI to generate apps from plain English, fine-tune them in the visual editor or tweak with code when needed — all within a unified workflow.
• Standardized UI components: Build consistent interfaces using reusable elements that align with your design system.
• Full-code extensibility: Leverage JavaScript, Python, SQL, and React to handle complex finance logic and integrations. Connect to Git and deploy through your existing CI/CD pipeline.
• Integration with your existing systems: Connect to databases, SaaS apps, and other third-party platforms using our pre-built connectors.
• Centralized governance: Enforce RBAC, authentication, and audit logs from a single control plane.‍
• Full portability: Export your app as raw React code and run it independently.‍
• Fits into existing SDLCs & DevOps pipelines: Supports automated testing, CI/CD integration, version control (Git), and staged deployments so you can manage changes.‍
• Incredibly simple observability: Receive metrics, traces, and logs from all your internal tools directly in Datadog, New Relic, Splunk, or any other observability platform.‍
• Real-time streaming support: Stream data to front-end components and connect to any streaming platform, such as Kafka, Confluent, or Kinesis, to build real-time user interfaces.

If you’d like to see how these features can support your migration roadmap, explore our Quickstart Guide, or better yet, try it for free.

Frequently Asked Questions 

What is the best legacy system migration strategy?

The best strategy is one that balances risk, cost, and business value. It should mitigate your legacy system’s pain points with an acceptable level of effort and risk. Generally, you’ll choose among strategies like rehosting, replatforming, refactoring, or complete replacement. 

How can I migrate legacy systems to the cloud?

Start with a readiness assessment. Then, choose a strategy, such as rehosting or replatforming, and implement it in stages. Use tools that sync data, expose APIs, and support hybrid environments.

How long does a typical migration project take?

Small, simple migrations like a single server application to the cloud might be done in a few weeks or a couple of months. Large-scale migrations, for example, migrating off a legacy data warehouse to the cloud, can take 6 months to over a year.

What tools are best for legacy to cloud migration?

Some of the tools used for legacy to cloud migration include iPaaS tools (MuleSoft, Boomi), low-code platforms (Superblocks), ETL tools, and API gateways. The best tool will depend on what aspect of migration you need help with.

Can I build new UIs on top of legacy databases with Superblocks?

Yes. Superblocks connects directly to legacy databases. You can connect Superblocks to your existing legacy database via provided or custom integrations, then build UIs or automations that work with that data.

What’s the difference between refactoring vs. replatforming a legacy app?

Refactoring rewrites parts of the code for better structure or performance. Replatforming moves the app to a new environment with minimal to moderate code changes, such as updating middleware or switching databases, without a full rewrite.