Software Development Cost: A Guide to Legacy Systems, Rewrites, and Microservices

As a high agency person, you know every decision shapes your product and your bottom line, especially when balancing growth with sustainable software development cost. Effective cost management can free up resources for innovation and ensure you stick to your software development budget. In this guide, you’ll explore three proven strategies that help you allocate funds wisely and keep your project on track.

Choosing the right path depends on your goals, team size, and how much you can invest upfront. We’ll look at maintaining legacy systems, executing a complete rewrite, and implementing a microservices architecture. Each option has trade-offs in terms of cost, time, and future scalability.

Maintaining legacy systems often means finding creative workarounds to reduce overhead and avoid steep migration costs. You can extend existing modules, update critical dependencies, and streamline performance without starting from scratch. This approach keeps your immediate software development cost predictable and embraces mature code while you plan for future shifts.

A complete rewrite lets you build a modern codebase designed for today’s demands and emerging technologies. It carries a higher upfront investment in time and resources but can pay off if you need long-term scalability, maintainability, and faster deployment cycles. With proper planning, this option aligns with long-term cost management goals and helps prevent costly refactors later.

Adopting a microservices architecture breaks your application into independent, scalable components that teams can own and deploy separately. This setup requires coordination, a solid API strategy, and robust DevOps practices, but it delivers flexibility for your teams and more granular control over your software development budget. Over time, you’ll see opportunities to spin up, update, or retire services without a monolithic rewrite and fine-tune your ongoing cost management.

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Legacy Systems: Managing Software Development Cost Through Maintenance

Definition and Characteristics of Legacy Systems

Legacy systems are long-standing software applications that continue to support essential business processes. Typically developed using now less-popular technologies and frameworks, they remain at the heart of operations due to proven reliability and deep integration with organizational workflows. Over time, legacy systems may accumulate technical debt and become harder to evolve or maintain as original team members leave and documentation grows stale.

Key characteristics include:

• Established codebase: Developed with older programming languages or frameworks.
• Proven reliability: Long-term stable operation, often underpinning mission-critical functions.
• Deep business integration: Closely tied to unique workflows and internal processes.
• Limited documentation: Institutional knowledge may erode as teams turn over.
• Accumulated technical debt: Past design decisions and quick fixes increase maintenance complexity.
• Monolithic architecture: Systems are often large and interconnected, making modular updates challenging.

The biggest trap in maintaining legacy is the lack of understanding of the technology and the availability of talent.

Jacek Głodek

Founder @ Iterators

Pros and Cons of Maintaining Legacy Systems

Pros

1. Lower Initial Cost: Maintaining an existing system generally requires less upfront investment than a complete rewrite or microservices transformation.
2. Business Continuity: Minimizes disruption to ongoing operations and user workflows.
3. Proven Functionality: Leverages existing system stability and functionality that has been refined over time.
4. Preserved Knowledge: Maintains institutional knowledge embedded in the existing system.
5. Faster Implementation: Enhancements and fixes can be deployed more quickly than building new systems from scratch.
6. Risk Mitigation: Avoids the significant risks associated with large-scale rewrites.

Cons

1. Limited Scalability: Legacy systems often struggle to handle growing user loads or data volumes.
2. Integration Challenges: Difficulty integrating with modern technologies, APIs, and third-party services.
3. Talent Scarcity: Finding developers skilled in legacy frameworks becomes increasingly difficult and expensive.
4. Growing Maintenance Burden: Technical debt accumulates over time, making maintenance progressively more complex and time-consuming.
5. Security Vulnerabilities: Older systems may have security weaknesses that are difficult to address.
6. Competitive Disadvantage: May limit the ability to implement innovative features or respond quickly to market changes.

Cost Implications of Legacy Systems

Short-Term (0–12 months)

• Minimal up-front spending: Maintenance is typically the least expensive option in the short term.
• Stable operational costs: Infrastructure and processes are already in place.
• Targeted enhancements: Budget can go to incremental improvements.
• Familiarity: Lower training costs, since teams know the system.

Medium-Term (1–3 years)

• Rising maintenance costs: As complexity increases, maintaining quality and reliability becomes harder and more expensive.
• Talent costs: Specialized skills command higher salaries.
• Integration overhead: New business needs often require custom adapters or middleware.
• Technical debt “interest”: Even small changes can become disproportionately costly.
• Partial modernization: Investments in specific components may be necessary to maintain usability.

Long-Term (3+ years)

• Escalating support costs: Legacy maintenance can dominate IT spending, sometimes exceeding what a rewrite would cost.
• Opportunity costs: Limits on feature development or market responsiveness can impact growth.
• Security remediation: Patchwork fixes may not fully address vulnerabilities.
• Increased outage risk: Systems may become more fragile with age.
• Eventual replacement: In most cases, ongoing costs eventually force a transition to a new system.

Real-World Examples and Case Studies

Case Study: E-commerce Platform Modernization

Challenge: A major e-commerce company needed to modernize its platform to handle increased traffic and provide a better user experience. The existing monolithic architecture was hindering scalability and rapid deployment of new features.

Approach: The company transitioned to a microservices-based architecture, allowing for independent development and deployment of services. This shift enabled the team to scale specific components as needed and improved fault isolation. Hygraph

Outcome: Post-migration, the company experienced improved scalability, faster deployment cycles, and enhanced system resilience, leading to better customer satisfaction and increased revenue.

Case Study: U.S. Army’s Digital Infrastructure Overhaul 

Challenge: The U.S. Army was burdened with nearly 1,000 outdated internal systems, leading to inefficiencies, high maintenance costs, and challenges in meeting modern operational demands. New York Post

Approach: Initiated in November 2024, the Army embarked on a comprehensive digital transformation. Key strategies included: New York Post

Consolidating and streamlining internal systems, reducing their number from approximately 980 to under 300. New York Post

Implementing AI-driven automation to expedite routine tasks, such as updating job descriptions for 300,000 civilian employees, reducing the process from four months to one week. New York Post

Overhauling expensive, paper-based processes, notably the military records retrieval system, which previously cost $43 million annually. New York Post +1 Coherent Solutions +1

Outcome: The modernization efforts are projected to save at least $89 million starting October 1, 2025. Additionally, the Army achieved a 50% reduction in cloud-related costs for certain logistics programs and enhanced overall operational efficiency. New York Post

Case Study: ING Bank’s COBOL to Java Migration

Challenge: ING Bank, one of Europe’s top 10 banks, faced challenges with its legacy systems built on COBOL, including CICS/DB2 and JCL batch processes. These systems were becoming increasingly difficult to maintain and integrate with modern technologies. softwaremining.com

Approach: ING Bank undertook a significant modernization effort by migrating 1.5 million lines of COBOL code to Java. This transformation aimed to improve scalability, security, and operational efficiency. softwaremining.com

Outcome: The successful migration enhanced the bank’s ability to adapt to changing market demands and reduced reliance on outdated technologies.

Warning Signs and When to Consider Alternatives

Red Flags That Your Legacy Approach Is Unsustainable

1. Significantly rising costs: When year-on-year maintenance increases outpace value delivered.
2. Talent shortages: Difficulty recruiting or retaining people who know the system.
3. Frequent incidents: Growing instability, even with increased effort.
4. Security or compliance pressure: New requirements that can’t be met without architectural changes.
5. Vendor abandonment: Critical technologies no longer supported.
6. Business limitations: The system blocks growth, innovation, or key strategic moves.

Decision Framework for Moving Beyond Legacy Maintenance

Consider alternatives to the legacy approach when:

• ROI Analysis Shows Diminishing Returns: The cost of maintenance exceeds the value delivered.
• Technical Debt Becomes Overwhelming: Simple changes require extensive workarounds and testing.
• Competitive Pressure Demands Innovation: Market forces require capabilities the legacy system cannot support.
• Growth Projections Exceed System Capacity: Anticipated scaling needs surpass what the current architecture can handle.
• Security or Compliance Mandates: External requirements necessitate architectural changes.

The single most expensive mistake? Ignoring your business context. No two modernization journeys are the same, but every decision starts at the intersection of roadmap, budget, and burn rate.

Jacek Głodek

Founder @ Iterators

Transition Strategies

When you decide that maintaining legacy is no longer the best option, you can:

• Use the strangler pattern: Replace components incrementally while running old and new in parallel.
• Parallel implementation: Synchronize data and features between systems until migration is complete.
• Phase-based migration: Move in planned steps, based on business priority.
• Service abstraction: Create interfaces that work with both old and new components.
• Start with data: Migrate and clean data before replatforming functionality.

Maintaining legacy systems can be a pragmatic, cost-effective path for many organizations, especially in the early stages or when resources are limited. However, as technical debt, maintenance effort, and opportunity costs accumulate, it’s essential to regularly reassess whether this approach still aligns with your goals and market context.

Strategic planning, ongoing monitoring, and readiness to shift when warning signs appear are key to getting the most value from your legacy investments—while staying prepared for necessary evolution.

Full Rewrite: Resetting Your Software Development Cost Baseline

What Is a Full Rewrite in Software Modernization?

When you hear the phrase “full rewrite,” think demolition and rebuilding, not home renovation. A true rewrite in software modernization is not a refactor, nor a series of quick patches—it’s a complete teardown and reconstruction of your product’s digital foundation. All the old code, business rules, technical assumptions, and hacks are left behind. You’re building a brand-new system, often with a modern stack and new architectural paradigm.

But why would any sane founder, CTO, or product owner take on such a daunting challenge? The reality is, legacy systems eventually become a drag on every part of the business—productivity, hiring, time to market, even compliance. When your tech is slowing you down more than it’s helping you compete, the rewrite question becomes impossible to ignore.

The True Cost Profile of a Full Rewrite

Let’s be blunt: a full rewrite will put your burn rate through the roof—at least at first. It’s a high-risk, high-reward move that looks very different from incremental upgrades or optimization.

Cost Curves and the J-Curve Reality

• Short term: Expect a period where investment is high but visible product progress is minimal. No new features for users, just a rising pile of code and invoices.
• Medium term: Eventually, you’ll catch up with the legacy system (feature parity). The costs remain high, but now you’re starting to see the light at the end of the tunnel.
• Long term: If the team survives the pain and the runway lasts, you’ll (finally) see a payoff: rapid delivery of new features, lower maintenance cost, and a team that can finally work with modern tools.

Budget Breakdown & Resource Patterns

Every rewrite is different, but most follow this rough pattern:

• Planning & Analysis: 10–15% (mapping out requirements, understanding business rules)
• Core Development: 40–50% (building essential features, integrating new architecture)
• QA & Testing: 15–20% (catching edge cases, security, user acceptance)
• Infrastructure & Deployment: 10–15% (setting up environments, automation)
• Project Management & Contingency: 10–20% (keeping everything on track, handling surprises)
• Resource needs evolution: You’ll need more senior architects at the start, more developers mid-project, and a spike in QA/DevOps as you approach launch.

Burn Rate and Runway Management During a Rewrite

The biggest shock for most executives? How quickly a rewrite eats through your budget. For months, you’re burning capital without shipping new features to users or clients. This isn’t just a founder’s problem—C-level leaders, product owners, and engineering directors all face the same pressure when the board or investors ask, “Why aren’t we seeing results yet?”

How Does a Rewrite Impact Runway?

• Burn rate spikes: Your team expands (more engineers, QA, architects, DevOps), and you start paying for parallel infrastructure, testing environments, and external audits.
• Zero revenue-impacting features: During the bulk of the rewrite, most changes are invisible to customers.
• Runway shortens: Even well-funded companies can find themselves dangerously close to running out of cash before the new system is ready.
• Pressure from stakeholders: The longer the drought, the harder it is to keep everyone aligned.

Cost Management Tactics for Survival

• Phased funding: Break the rewrite into milestones tied to specific deliverables. Use go/no-go gates to avoid throwing good money after bad.
• Milestone reporting: Keep board and investors updated with transparent, data-driven progress reports.
• Parallel ops: Maintain business continuity by keeping critical legacy systems operational until the new system is stable.
• Timeboxing: Use fixed-length sprints with regular demos, so you catch overruns early.

When Is a Rewrite the Only Sensible Choice?

A rewrite is the nuclear option—and it’s only justified when every other option is worse for the business. But how do you know you’re at that point? Here’s how experienced execs, CTOs, and product leaders make the call:

Strategic Decision Criteria and Red Flags

• The core tech stack is obsolete or unsupported.
• Regulatory or security requirements can’t be met without fundamental changes.
• Technical debt makes adding or maintaining features prohibitively expensive.
• Time-to-market has slowed so much you’re losing competitive edge or market share.
• Talent is impossible to hire for your legacy technology.

Checklist for Decision Makers:

• The cost of keeping the old system running now exceeds 40% of your development budget.
• Delivering a new feature takes 3x longer than the market standard.
• The architecture is so broken that even minor improvements cause regressions.
• The business can withstand 6–12 months with no major releases or visible improvements.
• Funding and stakeholder patience are secured for the entire project duration.

Real-World Triggers

• Regulatory change means “adapt or die.”
• A competitor leapfrogs your product because you can’t move fast enough.
• The last expert on your legacy system is about to leave (or just did).

Pro tip: If you’re debating a rewrite simply because “everyone hates the old code,” think again. The only justifiable reason is when the legacy actively blocks business survival or growth.

Planning for the Hidden Risks in Full Rewrites

A full rewrite isn’t just a technical marathon—it’s an organizational minefield. The cost and complexity multiply when you hit surprises nobody planned for. Executives and tech leaders who’ve lived through it know: the biggest risks are rarely about code—they’re about knowledge loss, integration blockers, and team stability.

The Most Dangerous Risks

• Loss of Organizational Knowledge: The deeper your legacy system, the more business logic is hidden in “tribal knowledge” and undocumented code. If you start a rewrite without mapping out real-world processes and exceptions, you’ll miss critical features or edge cases—and users will notice.
• Integration Nightmares: Legacy systems rarely exist in isolation. Untangling all their dependencies (APIs, third-party services, back-office tools) is slow, messy, and often underestimated.
• Losing Key People: When the last developer or analyst who understands the old system leaves mid-project, your rewrite risk spikes.
• Blind Spots & Black Boxes: Most teams think they know their system better than they do. Surprises come when “corner cases” surface that nobody remembered.

Risk Mitigation Strategies

• Document everything: Black box/white box analysis; map what the system actually does, not just what’s in the spec.
• Keep legacy experts engaged: Incentivize them to help, not just check out.
• Prioritize integrations: Start with the most business-critical and riskiest dependencies.
• Regular risk reviews: Schedule checkpoints to reassess assumptions, team morale, and project health.
• Knowledge transfer: Shadowing, pair programming, detailed handover sessions.

Phased Delivery and Minimum Viable Rewrite (MVR)

The “big bang” rewrite—turning off the old and switching on the new overnight—is legendary for causing outages, failed launches, and sometimes company-ending disasters. The smarter move? Phased delivery and Minimum Viable Rewrite.

Why Big Bang Fails, and Phased Wins

• Safer Transitions: Rolling out the new system feature-by-feature or module-by-module lets you validate each part and catch issues early.
• User Trust: Users see steady improvements, not a sudden cliff of bugs and missing features.
• Business Continuity: If something breaks, you can roll back or switch to legacy until the fix is ready.
• Learning Loops: Every successful migration builds team competence and confidence for the next phase.

How to Do Minimum Viable Rewrite

• Start with core workflows: Migrate the highest-value, most-stable pieces first.
• Parallel running: Run legacy and new system side-by-side. Use feature flags or canary releases to limit exposure.
• Gradual migration: Move users and data incrementally—not all at once.
• Continuous feedback: Build in user feedback loops and A/B testing to validate business impact at each stage.
• Celebrate milestones: Recognize progress—nothing kills morale like an endless slog.

Cost Management Tactics for Rewrite Success

Cost control in a full rewrite is less about squeezing pennies and more about designing a process that keeps your spend aligned with progress and value. If you treat a rewrite like a blank check, costs will balloon and timelines will slip until you’re left with two half-broken systems and a demoralized team. Seasoned executives know: process discipline and structured feedback are what separate success from burn-out.

First, budgeting for uncertainty is critical. You need to plan for overruns—history says even well-run rewrites blow past initial estimates. Smart organizations build in a 20–30% contingency buffer up front. Just as important, the budgets for the new build and the ongoing maintenance of legacy systems should be clearly separated. This avoids the death spiral where funds for “keeping the lights on” get sucked into rewrite fire drills, risking business continuity.

Time-boxing development and creating clear checkpoints is non-negotiable. Set fixed-length sprints, insist on demos at every milestone, and use go/no-go decisions to keep the project honest. If something’s off track, act fast—don’t let small delays accumulate until the runway disappears. Milestone-based funding, tied to real, testable outcomes, keeps both teams and investors aligned on what “progress” really means.

Resist “gold plating”—the urge to add just one more feature or optimization. The right approach is to aim for minimum viable parity: get the essentials live, then improve. Anything else is a recipe for never shipping.

Real-world cost management isn’t about one magic trick. It’s a portfolio of habits: constant stakeholder updates, transparent communication, feedback loops that expose issues early, and an organizational culture that celebrates incremental wins rather than swinging for a mythical home run.

Real-World Case Studies: Full Rewrite Outcomes

Real-world examples make the theory tangible—and show that rewrites, while difficult, can drive enormous value if done for the right reasons and with the right discipline.

Take ING Bank, one of Europe’s largest financial institutions. Facing mounting technical debt and growing integration challenges from decades-old COBOL mainframes, ING didn’t reach for the panic button. Instead, they undertook a highly structured, phased rewrite—migrating 1.5 million lines of legacy COBOL code to Java. The key wasn’t just technical skill, but the way they managed risk and knowledge transfer: they ran old and new in parallel, staged migrations by business priority, and built feedback loops between IT and business users. The result? Reduced maintenance costs, improved scalability, and the ability to finally deliver new digital features customers wanted.

Similarly, look at the experience of Shopify (often discussed in modernization circles, even if not a “total rewrite”): Instead of a single “big bang,” they invested in modularizing and rebuilding their monolithic core over time, launching new capabilities piece by piece. This approach let them maintain stability and deliver value while transforming their technology stack, avoiding the risk of business disruption.

Finally, composite industry examples abound—think of mid-sized SaaS firms who, faced with lost market share and skyrocketing legacy maintenance, funded parallel teams for the rewrite and legacy support. The ones who succeeded set aggressive, phased milestones, prioritized institutional knowledge transfer, and resisted the urge to chase every new technology fad mid-project. The failures? Most lacked planning discipline, ran out of budget, or lost key talent at critical points.

The lesson: A rewrite is survivable, and even transformative, if you treat it as a calculated investment, not a tech-driven fantasy. The smartest companies get business buy-in, keep their runway visible at all times, and never lose sight of the cost management basics that keep organizations alive and competitive.

The Rewrite Decision as an Investment

Choosing a full rewrite is never just a technical decision—it’s a high-stakes, long-term investment that reshapes how your organization delivers value. The process will test your runway, your patience, and your ability to keep the business running while building for the future. No matter how tempting a greenfield project sounds, rewrites succeed only when there’s total alignment between business goals, technical vision, and the resources to weather the inevitable storms.

Most companies that pull off a successful rewrite aren’t the ones chasing the hottest technology or the fastest time-to-market. They’re the ones who treat cost management as a living discipline—who are willing to face hard truths early, communicate transparently with all stakeholders, and stick to phased, validated progress over the illusion of instant transformation.

A rewrite won’t save a broken business model or fix a team that lacks discipline. But in the right hands, with the right reasons and the right preparation, it can reset your cost baseline, unlock new growth, and give your business the technical foundation it needs to compete and scale.

If you’re staring down a major modernization and want a second set of eyes on your plan—or just need to talk through your options—reach out to our team. A short, frank conversation now could be the smartest investment you make all year.

Microservices: Optimizing Software Development Cost Through Incremental Modernization

In today’s rapidly evolving technology landscape, startups and enterprises face a critical decision when managing software development costs: stick with legacy systems, commit to a full rewrite, or adopt a microservices approach. This section explores how microservices architecture can provide a balanced, cost-effective strategy for startups looking to modernize their software incrementally.

Definition and Characteristics of Microservices Architecture

Microservices architecture is a development approach where an application is structured as a collection of loosely coupled, independently deployable services. Unlike monolithic applications where all functionality exists in a single codebase, microservices break down applications into smaller, function-specific components that communicate via well-defined APIs. Key characteristics of microservices include:

• Independent Deployment: Each service can be deployed without affecting other services
• Domain-Focused: Services are organized around business capabilities or domains
• Decentralized Data Management: Each service manages its own database
• API-First Design: Services communicate through standardized APIs
• Technological Diversity: Different services can use different technologies as needed
• Autonomous Teams: Separate teams can develop, deploy, and scale individual services

When Microservices Make Sense for Startups

Not every startup should immediately jump on the microservices bandwagon. This approach makes the most sense in specific scenarios:

1. Function Separation (Bounded Contexts)

When different parts of your system handle separate business processes or serve different stakeholders (e.g., billing vs. user onboarding), breaking these into microservices becomes logical. This separation allows teams to focus on specific business domains without getting entangled in unrelated code.

2. Organizational and Technological Scalability

Microservices shine when multiple teams need to work independently on different parts of the application. This approach accelerates development—provided there’s sufficient maturity in QA, CI/CD, and DevOps processes. For startups scaling their engineering teams, this can be a significant advantage.

3. Desire to Leverage Ready-Made Solutions

If your business core can be “wrapped” with APIs while using SaaS/PaaS solutions for peripheral functionality, microservices offer an elegant integration path. This allows startups to focus development resources on their unique value proposition while using off-the-shelf solutions for standard functions like compliance, billing, or user management.

Pros and Cons of the Microservices Approach

Pros

1. Incremental Modernization: Allows gradual migration from legacy systems without disrupting the entire application
2. Faster Feature Delivery: Independent services mean faster development cycles for individual features
3. Targeted Scaling: Resources can be allocated precisely where needed, optimizing infrastructure costs
4. Technology Flexibility: Freedom to choose the best technology for each specific service
5. Resilience: Failures in one service don’t necessarily bring down the entire application
6. Team Autonomy: Development teams can work independently, improving productivity

Cons

1. Operational Complexity: Managing multiple services requires sophisticated DevOps capabilities
2. Distributed System Challenges: Debugging, monitoring, and testing become more complex
3. Organizational Maturity Required: Without proper QA processes and DevOps practices, microservices can create more chaos than value
4. Potential for “Distributed Monolith”: Poor boundary mapping can lead to tightly coupled services that negate the benefits
5. Initial Setup Investment: Establishing the infrastructure for microservices requires upfront investment

Cost Implications of Microservices Implementation

Understanding the cost profile of microservices is crucial for startups making architectural decisions.

Short-Term Costs

• Infrastructure Setup: Establishing CI/CD pipelines, monitoring systems, and service discovery mechanisms
• DevOps Investment: Building or hiring DevOps expertise to manage the distributed environment
• Learning Curve: Training developers in microservices patterns and distributed systems concepts
• API Design and Management: Resources dedicated to designing robust APIs and managing their lifecycle

Medium-Term Costs

• Operational Overhead: Managing multiple services, databases, and deployment pipelines
• Monitoring and Observability: Implementing comprehensive monitoring across services
• Integration Testing: Ensuring services work together correctly despite independent development
• Documentation: Maintaining clear documentation for service interfaces and dependencies

Long-Term Benefits

• Reduced Development Bottlenecks: Teams can work in parallel without blocking each other
• Targeted Scaling Economics: Resources can be allocated precisely where needed, avoiding over-provisioning
• Technology Refresh Flexibility: Individual services can be updated or replaced without system-wide disruption
• Talent Utilization: Developers can specialize in specific services, improving productivity
• Reduced Technical Debt: Problems are contained within service boundaries rather than spreading system-wide

Integration Strategies with Legacy Systems

One of the most compelling aspects of microservices for startups is the ability to gradually modernize existing systems. Here are proven strategies for integration:

Hybrid Approach

The most successful strategy is typically a gradual migration—separating the most important functions into new microservices while maintaining APIs/adapters to the legacy system. This approach allows for incremental improvement without disrupting business operations.

API-First Strategy

Instead of attempting a “big bang” migration, wrap legacy components with modern APIs. This “strangler pattern” gradually replaces legacy functionality while maintaining system stability.

Prioritization Framework

Not all services should be migrated simultaneously. Consider these factors when prioritizing:

• Business value of the functionality
• Current pain points in the legacy system
• Complexity of the migration
• Dependencies between components

Phased Migration

Establish a clear roadmap that outlines which legacy functions each new microservice will replace, and ultimately which legacy modules can be decommissioned. This creates a measurable path to modernization.

Real-World Example: Startup Success with Microservices

Case Study: Virbe’s SaaS Platform for Virtual Beings

Challenge: Virbe, a startup creating Virtual Beings for the Metaverse in sales, HR, education, and customer support, needed to develop a scalable platform while handling the unpredictability inherent to startups, including strategy and market changes.

Approach: The team designed and architected a platform using a microservices approach, developing with Scala, Node.js, Python, and FastAPI. They built AWS-based microservices with automated CI/CD pipelines and provided ongoing maintenance and feature additions.

Results:

• Delivered a platform exceeding requirements by 10%
• Received highly positive feedback from customers and QA teams
• Facilitated continual improvements driven by user suggestions
• The microservices architecture allowed independent scaling of services
• Optimized resource usage and reduced operational costs through targeted deployments
• Automated CI/CD workflows improved development efficiency

This case demonstrates how microservices can provide the flexibility startups need while maintaining cost efficiency through targeted resource allocation.

Best Practices and Implementation Considerations

1. Start with Clear Service Boundaries

Properly defining service boundaries based on business domains (bounded contexts) is crucial. Poor boundary mapping leads to a “distributed monolith”—all the complexity of microservices with none of the benefits.

2. Ensure Organizational Readiness

Without mature QA processes, DevOps capabilities, and conscious product management, microservices can generate chaos and higher costs than a monolith. Assess your team’s readiness before committing.

3. Implement Robust Monitoring and Observability

Distributed systems require comprehensive monitoring. Invest in tools that provide visibility across services, tracking not just uptime but also performance, dependencies, and business metrics.

4. Adopt Infrastructure as Code

Automating infrastructure provisioning and configuration is essential for managing multiple services efficiently. Tools like Terraform, AWS CloudFormation, or Kubernetes manifests should be part of your toolkit.

5. Establish Clear Communication Patterns

Decide early on how services will communicate (synchronous REST, asynchronous messaging, etc.) and establish standards for API design and versioning.

6. Plan for Failure

Design services to be resilient when dependent services fail. Implement circuit breakers, retries, and fallback mechanisms to maintain system stability.

7. Start Small and Expand

Begin with a few well-defined microservices rather than attempting to break down the entire application at once. This allows your team to learn and adapt your approach as you go.

Implementation Steps and Timeline for Cost-Effective Microservices

1. Assessment Phase (1-2 months)
   • Analyze current system architecture
   • Identify bounded contexts and potential service boundaries
   • Assess team capabilities and infrastructure needs
   • Define success metrics
2. Foundation Building (1 month)
   • Establish CI/CD pipelines
   • Implement monitoring and logging infrastructure
   • Define API standards and communication patterns
   • Set up development, testing, and production environments
3. First Service Migration (1-2 months per service)
   • Select a non-critical but valuable service for initial migration
   • Develop and test the new microservice
   • Deploy alongside the legacy system
   • Gradually shift traffic to the new service
4. Expansion and Refinement (Ongoing)
   • Migrate additional services based on priority
   • Refine processes based on lessons learned
   • Gradually decommission legacy components
   • Continuously measure and optimize performance

When to Choose the Microservices Approach

The microservices approach offers a balanced path for startups looking to modernize their software while managing costs effectively. It’s particularly well-suited for:

• Startups with growing engineering teams that need to work in parallel
• Companies with clearly defined business domains that can be separated into services
• Organizations with sufficient DevOps maturity or willingness to invest in it
• Businesses that need to gradually modernize without disrupting operations
• Startups looking to leverage best-of-breed technologies for different functions

Microservices are not a solution for everyone—without organizational maturity, they generate more chaos than value.

Jacek Głodek

Founder @ Iterators

The key is to make an informed decision based on your specific business context, technical requirements, and organizational capabilities.

By taking an incremental, thoughtful approach to microservices adoption, startups can achieve the benefits of modern architecture while managing costs and risks effectively.

Comparison of Approaches

Legacy Systems

• Short term: You add features fast at moderate cost.
• Medium term: Workarounds pile up, bugs increase, costs rise.
• Long term: Feature delivery grinds to a halt, maintenance costs explode.

Full Rewrite

• Short term: You pause feature work, rebuild core, costs spike.
• Medium term: Migration and testing keep costs high, no new user features.
• Long term: Feature delivery surges post-launch, maintenance costs drop dramatically.

Microservices

• Short term: You invest in architecture and CI/CD, few new features.
• Medium term: Features ramp up steadily, costs spread out.
• Long term: You ship features fast, maintenance costs stabilize but ops complexity grows.

When it comes to software development costs, the initial build is just the tip of the iceberg. Our approach considers the total cost of ownership, including maintenance, scalability, and future adaptation.

Jacek Głodek

Founder @ Iterators

Decision Matrix

Microservices aren’t always the answer. Sometimes a well-designed monolith is more cost-effective for smaller teams and projects.Mateusz KubuszokSoftware Developer @ Precog

Łukasz Sowa

Founder @ Iterators

How Cost and Features Evolve

• Legacy: Costs creep up, feature velocity stalls.
• Rewrite: You face a long feature drought, then a big surge.
• Microservices: Costs and features grow in parallel, then stabilize.

Choosing the Right Approach

1. Map functionalities
   • Identify your core features and quick wins.
2. Calculate Total Cost of Ownership
   • Include maintenance, recruitment, compliance, training, migrations.
3. Assess risks
   • Factor in delays, key people leaving, tech limitations.

Use this framework to pick a path that fits your budget, team size, and growth plans.

Schedule a free consultation with our experts to discuss your software development cost optimization.

Final Thoughts: Balancing Software Development Cost, Quality, and Speed

You’ve explored three paths to manage development costs:

• Legacy Systems
  • Typical maintenance eats up 20–30% of your annual dev budget.
  • Low upfront investment ($0–$10K) and fastest launch (weeks).
  • Long-term risk: 10–15% yearly tech-debt growth, slower feature rollouts.
• Full Rewrite
  • Upfront effort: 3–6 months of dev time (roughly $50K–$200K).
  • Eliminates legacy constraints, boosts velocity by 25% after release.
  • Long-term payoff: 30–40% lower maintenance costs after 12–18 months.
• Microservices Modernization
  • Incremental modules at $15K–$40K each, deliver key features every 2–4 weeks.
  • Balances risk: isolate failures, scale high-traffic services independently.
  • Watch overhead: orchestration and monitoring add ~5–10% extra cost.

To choose wisely, lean on our Decision Framework (Assess ➔ Prioritize ➔ Plan ➔ Execute). Map your product roadmap and must-have features, calculate your runway in months, set your market-launch deadline, and inventory team skills. If you’ve got under six months of funding and a rapid MVP to hit, legacy tweaks or a couple of microservices might be ideal. If you’re backed for 12+ months and need a complete overhaul, a full rewrite can deliver lower TCO over two years.