Application modernization is the process of updating your legacy applications—infrastructure, architecture, code, or data layer—to work with modern technologies and AI-driven tools. Modernizing your portfolio of applications typically involves quick fixes alongside deeper redesigns and can be done in phases.
Key takeaways
- Modernizing your legacy applications is a flexible process—you can use the 7 Rs framework to decide what to update, what to leave alone, and what to retire.
- The Rs in the 7 Rs framework—retain, retire, rehost, replatform, refactor, rearchitect, and rebuild—can be mixed and matched to fit your technology and business needs.
- You don’t have to modernize everything simultaneously—upgrading one piece of technology at a time is less risky than trying to replace an entire system at once.
- A legacy database is often overlooked in application modernization but it can cause bottlenecks if not modernized with the rest of the system.
- AI is changing how fast modernization can happen; new tools can now rewrite legacy code and generate tests on their own, which dramatically shortens modernization timelines.
- Modernization isn’t just about technology, it also takes leadership, measurable goals, and a roadmap that keeps everything on track.
Table of contents
- What is application modernization?
- Why should you modernize legacy apps?
- How do you assess legacy applications?
- What are the 7 Rs of modernization?
- Application modernization is a comprehensive strategy
- Which application modernization strategies work best?
- Why databases must be included in application modernization plans
- How is AI changing application modernization?
- Which tools and services do you need for modernization?
- How do you build an application modernization roadmap?
- Your modernization ROI checklist
- What are your next steps for application modernization?
- Related resources
What is application modernization?
Application modernization is the process of updating existing legacy applications to work with modern technology, infrastructure, and current business requirements. It doesn’t necessarily mean replacing an entire system. Instead, application modernization typically includes upgrading the platform, architecture, code, or data layer—often in stages. Common fixes include moving an application to the cloud as-is, breaking one large application into smaller independent services, or getting rid of applications that aren't worth maintaining.
The reason application modernization has become urgent for so many organizations is that the legacy systems running their businesses were designed for a different era—they still function, but they can’t keep up with what modern businesses need. For most organizations, application modernization isn't just an IT project—it's a foundational part of broader digital transformation.
Use case: Where app modernization problems often begin
Kai is the VP of Engineering at a $40 billion regional bank with a strong retail base and a growing wealth management division. The bank's platform was deployed in 2003 and it still works. Customers are making transactions and there are no obvious system issues.
But just because the bank’s applications work today doesn’t mean they’ll support what the bank has planned for the near future—like new mobile features, automated fraud detection, and a more connected customer experience.
Most of the pressure to modernize revolves around the data layer. A platform built in 2003with a rigid, relational structure records transactions well but struggles with the unstructured, high-volume data that AI workloads like fraud detection depend on. That mismatch is often what pushes teams to modernize in the first place—and it’s where a flexible document model like MongoDB tends to fit, since it’s designed to handle diverse data types and scale as demand grows.
Why should you modernize legacy apps?
Application modernization is one of the fastest-growing categories of enterprise technology spending—the global modernization services market is expected to grow from $19.82 billion in 2024 to $39.62 billion by 2029, according to MarketsandMarkets.
Many businesses begin to modernize existing apps when the cost of keeping them exceeds the cost of changing them. That cost shows up in more than dollars—it's found in security risks, slow performance, and customer dissatisfaction.
Below are common reasons why you might want to modernize:
Competition is moving faster than you are: Newer companies in your industry don’t carry as many legacy issues as you do, which means they can launch new features more quickly—and your customers are starting to notice you’re not keeping up.
Maintenance costs are eating your budget: Industry research suggests that organizations spend 60% to 80% of their IT budget just keeping old systems alive. McKinsey research has shown modernization can reduce IT infrastructure costs by 50%. Modernizing isn’t free, but doing nothing comes with a cost, too; protecting your existing investments often means modernizing them.
Your systems can’t handle modern workloads: Your older applications were likely built to handle a smaller amount of users, transactions, and data than modern businesses generate. Slowdowns or crashes might be showing up when traffic spikes or data volumes grow.
Security is getting harder to manage: Bad actors love legacy applications because they’re easier to hack—many can’t support modern security tools and no longer offer patches.
You can’t hire (or keep) the engineers you need: Many engineers don’t want to work with old technology, so they’ll move on—taking all their valuable knowledge with them. And finding their replacement can be difficult.
You can’t add new capabilities: All the modern tools—AI agents, machine learning, real-time data, and automation—are nearly impossible to add to legacy applications because they weren’t designed to support them.
Most organizations don't face one of these pressures—they face several at once. That's usually what tips the modernization decision from "someday" to "now."
TECH TIP: What is technical debt?
You may have heard the phrase “technical debt,” but what does it mean? Technical debt is the accumulated impact of not modernizing your code, architecture, or infrastructure. Each shortcut you took to keep your outdated system running saved time in the moment, but likely complicated future upgrades. Over time, those workarounds make every additional change slower, riskier, and more expensive.
Use case: What’s motivating Kai to modernize?
For Kai, the modernization pressures are showing up in several places at once:
A core vendor recently announced end-of-life support for one of the bank's underlying platforms.
Two regional fintechs are launching mobile features the bank’s customers are already asking about.
Internal engineers are grumbling about maintaining a system more than 20 years old.
The bank's last security audit flagged the legacy system as a growing risk because the framework underneath it can no longer be patched.
Like many companies in her position, Kai has to figure out where to start.
How do you assess legacy applications?
Before you decide what to modernize and how, you need to understand the cost of keeping your existing applications running. The three steps below can help you take stock of your current technology and put you on a path to modernization.
Step 1: Take inventory
To ensure you’ve got the full picture, it’s important to take stock of what you have. Write down every application your organization uses along with the systems it depends on. Interview engineers and system administrators—they’ll help you locate older applications, uncover forgotten integrations, and account for undocumented dependencies.
Step 2: Audit your technical debt
A technical debt audit examines the health of the application’s code, the age of its underlying frameworks, its ability to stay secure from modern threats, and its performance under current workloads. You probably won't do this assessment personally—your engineering team will. But you'll need to understand their findings enough to direct the next step.
Step 3: Decide what’s worth modernizing
Once you’ve completed your inventory and technical debt audit, the next step is deciding which applications are worth updating, which ones can wait, and which ones should be retired. To do this, ask yourself two questions about each application: how valuable is it to your business and how hard is it to modernize?
Once you’ve answered both questions for each application, you’ll get a clearer sense of what to do next.
If the application is:
Valuable and easy to update, proceed with modernization.
Valuable but hard to update, explore what’s needed and make a plan to modernize.
Not very valuable, ask your team if these applications are still needed. If they're easy to update, modernize them when you have time. If they're hard to update, you may choose to retire them instead.
DEEP DIVE: What’s included in a modernization inventory?
A modernization inventory includes more than just applications. It consists of source code, runtime dependencies, integration touchpoints (APIs, file transfers, message queues), database schemas, scheduled jobs, infrastructure configurations, monitoring tools, and the people in your organization who know how everything works.
Use case: What Kai finds when she takes a closer look
Kai’s inventory uncovers 47 applications across the bank’s business units: 20 have no current owner because the people who maintained them have moved on, 12 are running on frameworks that no longer receive security patches, 8 overlap with other systems, and 5 haven't been used in over a year but the bank is still paying infrastructure fees. Now that Kai has clarity, she can start deciding what to modernize first and what to retire by following the 7 Rs of modernization.
What are the 7 Rs of application modernization?
The 7 Rs is a popular modernization framework that companies use to evaluate their application portfolio. Each modernization decision—from a small fix to a complete rebuild—can be aligned with one of these seven actions:
Retain: Make an explicit decision to leave some apps as-is because they still work, or because the cost of modernizing won’t justify the cost.
Retire: Shut down some applications for good because they duplicate other systems or are no longer being used.
Rehost: Move the application to the cloud as-is with minimal changes. Often called “lift and shift,” rehosting is fast when you need to get off aging hardware quickly. When shifted, the application still works the same way it always did, it's just running on cloud infrastructure—which means all of its original problems (i.e., scaling limits, technical debt) come with it too.
Replatform: Move the application to the cloud, but swap out specific components for modern, cloud-native versions. For example, you might replace a self-managed database with a managed cloud service while keeping other components unchanged—the application still works the same way from the user’s perspective, but modernizing it reduces your maintenance burden.
Refactor: Clean up messy or outdated code with refactoring—it makes the application easier to maintain and reduces risk, but doesn’t add new functionality.
Rearchitect: Redesign the application’s structure in a major way, such as splitting one large application into smaller, independent pieces (sometimes called microservices), or by changing how the application stores and works with data. Rearchitecting takes time and carries risk because it touches so many parts of the original architecture, but it’s often the only way to add capabilities like real-time data, AI integration, or scaling on demand.
Rebuild: Build a new application from scratch, keeping only the rules and processes from the old system that are still useful. Rebuilding is the most expensive option, but it might be necessary if your legacy application is too outdated to save or the business has changed so much that the original system no longer works.
Application modernization is a comprehensive strategy, not just one decision
Most organizations use incremental modernization, applying several of the 7 Rs in manageable increments based on what they need instead of trying to overhaul everything at once.
For incremental modernization to work, you must have two things in place: alignment between your modernization goals and business goals, and proper governance of decisions (i.e., KPIs, accountability structures, and clear success criteria). The next step is making sure each decision moves the business forward—often toward the cloud.
The application modernization framework comes to life when you see it applied to a real portfolio—let’s see how Kai uses the 7 Rs at the bank.
Use case: How Kai uses the 7 Rs of application modernization
Kai sorts her 47 applications by value and effort, aligning each app to one of the 7 Rs. Her first round of decisions uses four: retire, rehost, rearchitect, and rebuild.
Kai retires the bank’s legacy reporting tool and replaces it with a modern business intelligence (BI) platform.
She rehosts the customer notification system in the cloud—a quick win that preserves it without rebuilding it.
The core banking platform gets rearchitected because the original architecture can no longer support mobile features or the unified customer view that the planning team wants.
The fraud detection application is rebuilt from scratch because it’s so outdated that it can’t receive security patches, which poses a serious risk for the bank.
Kai doesn’t make these modernization upgrades one after another; she runs them in parallel with different teams owning different applications.
Which application modernization strategies work best?
Three app modernization strategies that show up most often in modernization plans include cloud migration, monolith to microservices, and cloud adoption and hybrid cloud. None of these approaches is a single R from the framework above—they're patterns that combine multiple Rs depending on the situation.
Cloud migration is the most common starting point for application modernization
For most organizations, cloud migrations take years, not weeks—and that’s by design. To accelerate cloud adoptions, you might start with cloud rehosting because you need to stop using old hardware immediately, and delay cloud rearchitecting until you can assess your current applications more thoroughly.
Containerization is often used for staged migrations. Containers wrap an application together with everything it needs to run, so you can run it on your existing infrastructure today and in the cloud next month. That portability lets you decide when to migrate instead of being forced into a preplanned timeline.
When you migrate applications to the cloud, your spending migrates there, too. Large upfront infrastructure purchases are replaced by monthly operation costs, which typically saves money over time. However, on-premises legacy applications may experience performance issues during cloud implementation, so cost savings shouldn’t be the only thing driving your decision to move to the cloud.
Microservices are the most common way to break up a monolith
Many legacy applications are monoliths—single, all-in-one applications where every feature lives inside the same codebase. As businesses grow, monoliths become hard to change because everything inside is connected to everything else. Updating one part of the application might break another unrelated part.
The opposite of a monolith is a microservices architecture, where the same application is built as a collection of small, independent services that work together. Each microservice—like customer accounts or payment processing—has its own deployment pipeline and can be updated without touching the other services.
The most common way to modernize a monolith is with microservices via the strangler pattern:
The monolith remains untouched while new microservices are built alongside it.
As each new service comes online, it takes over a piece of the monolith’s work.
Eventually, all work moves to the microservices and the monolith is retired.
From that point on, the microservices work together to deliver the same application—just in smaller, more flexible pieces.
The name “strangler” comes from the strangler fig tree, which grows around its host until the host is gone.
Hybrid cloud is the most practical choice for most enterprise application modernization projects
Most large companies don’t move everything to the cloud—they use a hybrid approach, which offers a mix of public cloud services with on-premises infrastructure.
Hybrid clouds are typically used for three main reasons:
Regulations: Some industries require certain data to stay on private infrastructure. Healthcare providers, for example, often have to keep patient records in private systems to comply with HIPAA. Banks may need to keep customer financial data in specific countries to meet local laws.
Performance: Some applications need to be physically close to the people or systems using them. For example, production-line software in a factory may need to run on local hardware so it can respond instantly to equipment changes; any delay from a distant public cloud could disrupt operations.
Cost: Some workloads are simply cheaper to run on hardware you already own. A company that's already invested in its own data center may find that batch processing jobs—like nightly financial reports—cost less to run on existing infrastructure than in the public cloud.
Why databases must be included in application modernization plans
Most modernization frameworks, including the 7 Rs, focus on the application: where it runs, how the code is structured, and how teams release new versions—not on the legacy database. But ignoring a 20-year-old database can stall even the best modernization plan because the database simply wasn’t built for what your modernized applications will need.
Complete modernization requires modernizing the data layer, too. Tools like MongoDB's Relational Migrator help teams move from rigid relational schemas to more flexible document-based models that align to how the business works today.
Use case: How Kai discovers the bank’s database bottleneck
When Kai's team starts planning the core banking rearchitect, they assume the biggest job is the application code, but they soon find out the database is its own monolith—a 2,400-table relational database with 800 stored procedures that contain critical business logic. Without rearchitecting the database along with the applications, Kai’s team can't deliver any of the capabilities the bank is counting on.
Kai isn't alone in this discovery. Intellect Design, a global financial technology company, ran into the same problem—key business logic locked inside hundreds of SQL stored procedures, with batch processing delays that limited what the platform could do. After modernizing both the data layer and the application together with MongoDB, Intellect Design reduced its onboarding workflow times by 85%—proof that the database is an integral part of a complete modernization.
How is AI changing application modernization?
Until recently, the modernization process meant months or years of manual work—engineers had to read legacy code, rewrite it line by line, and test to make sure everything worked. AI has changed that.
Four areas where AI is making the biggest difference:
Code transformation: AI agents can read aging codebases (including older languages like COBOL) and produce modern equivalents at speeds that weren't possible two years ago.
Test generation: AI can analyze how a legacy application behaves and generate the tests needed to confirm the modernized version can do the same work.
Business logic extraction: Legacy applications have years of business rules buried in their code—things like how interest rates are calculated or how transactions are flagged for review. AI can read through the old code, find those rules, and pull them out as separate, reusable pieces, so the rules survive, but the rest of the application gets rebuilt.
Building feedback loops: Modernized applications can collect data on how they're performing in real time—including whether AI decisions are right or wrong. That data feeds back into the AI, helping it improve over time. Most legacy applications can't do this; modernized ones are built for it.
MongoDB's Application Modernization Platform (AMP) blends AI capabilities with proven methodology and engineering expertise. For enterprises with significant legacy applications, AMP can compress modernization timelines by two to three times.
For example, Bendigo and Adelaide Bank used AI tooling to reduce application test case execution from 80 hours to 5 minutes. Most organizations get the best results by piloting AI features incrementally—starting with a single application or workflow, learning from the results, and scaling up from there.
Which tools and services do you need for modernization?
Choosing application modernization tools and application modernization services usually involves two parallel decisions: which tools to use and which services to activate.
Tools that matter most in modernization
Observability and monitoring: Track how applications perform so you can spot problems early and verify modernized versions work better than what they replaced.
CI/CD pipelines (continuous integration and continuous delivery): Automate the testing and deployment of code changes, so teams can ship updates daily or weekly instead of quarterly.
Test automation: Run tests automatically when code changes, with AI-powered options that can generate tests by studying how the legacy application currently behaves.
Migration accelerators: Analyze legacy code, map dependencies, and convert old code into modern equivalents, sometimes compressing months of manual work into days.
Services that matter most in modernization
Consulting partners: Bring in outside modernization expertise, typically starting with an assessment and continuing through implementation.
Platform vendors with integrated services: Offer the modernization platform along with engineers to help you use it (MongoDB AMP).
Hybrid approaches: Combine outside platforms and consultants with internal engineering, letting you control which parts of the work get handled in-house and which get handed off.
Change management and training: Prepare engineers, leaders, and end users for new tools and workflows because modernization can fail when people don't know how to use what's been built.
Managed or self-managed services?
On top of choosing tools and services, most organizations also have to choose between managed services or self-managed services. Managed services are faster to set up and easier to maintain, but you have less control and may become too dependent on the vendor. Self-managed options give you more control, but then you have to handle everything—patching, scaling, security, and disaster recovery.
Large businesses with multiple business units often set up a Center of Excellence—a small, cross-functional team—to set standards and manage their approach.
How do you build an application modernization roadmap?
A modernization roadmap is a sequenced strategy that defines what gets modernized, in what order, and how you'll measure success.
Most successful roadmaps share four key actions:
Staged milestones: Plan a 12 to 36 month rollout, broken into quarterly deliverables.
KPIs and success metrics: Track delivery speed, cost, performance, and developer satisfaction.
A pilot project: Start with a small project that can deliver early wins.
An iterative release cadence: Ship every quarter rather than promising a perfect outcome three years from now.
Your modernization ROI checklist
Use case: Where Kai's plan stands now
Six months into her 18-month roadmap, Kai's notification system has shipped, the strangler pattern on core banking is underway, and the fraud detection rebuild is active. Like Lombard Odier, which cut regression testing from three days to three hours with MongoDB, Kai is starting to see modernization’s compounding returns.
What are your next steps for application modernization?
Whether you're early in your application modernization journey or already in motion, the path forward is simpler than it looks.
Take stock of what you have: Even an informal walk through of your applications, dependencies, and the engineers who maintain them, is enough to begin.
Pick a small pilot: Choose one application that's important enough to matter but small enough to finish quickly, so you can prove your approach works before scaling up.
Don’t skip your data layer: Modernization efforts can stall when the database is treated as an afterthought rather than part of the plan.
Build an evaluation checklist before talking to vendors: Create a list of must-haves first, so vendor pitches don't end up shaping your requirements.
A successful application modernization strategy takes time, alignment across teams, and constant reassessment. But the principles are straightforward: take stock of what you have, prioritize what matters, modernize in steps, and keep every decision tied to business value. Most organizations find it easier to begin once they see the path is built one decision at a time.
Explore MongoDB's application modernization solutions →
Related resources
Modernize Legacy Apps with AMP — Discover how MongoDB's Application Modernization Platform transforms outdated apps into flexible, AI-ready systems.
MongoDB Relational Migrator — Learn how to move from rigid relational schemas to flexible document-based models without disrupting your business.
What Is a Document Database? — Explore how document databases work and why they align better with how modern businesses operate.
MongoDB Atlas— Discover the cloud database platform that powers modern, AI-ready applications.
How Intellect Design Accelerated Legacy Modernization by 200% — See how a global financial technology company modernized its wealth management platform with MongoDB and gen AI.