"Microservices" was the buzzword of the 2010s. Every tech conference, every blog post, every architecture diagram showed boxes connected by arrows, promising infinite scalability and team autonomy. In 2026, the industry has corrected course. The truth is more nuanced: microservices solve real problems, but they create even more problems if adopted prematurely. At Futureaiit, we have helped dozens of companies navigate this decision, and the answer is almost never "start with microservices."
The Microservices Tax
Splitting your application into 10 services sounds architecturally elegant, until you encounter the operational overhead. Here is what nobody tells you about microservices:
1. Distributed Transactions Are Hard
In a monolith, transactions are simple. You start a database transaction, make your changes, and either commit or rollback. In microservices, you have distributed transactions across multiple databases.
Example: A user places an order. You need to:
- Deduct inventory in the Inventory Service
- Charge the payment in the Payment Service
- Create the order in the Order Service
- Send a confirmation email via the Notification Service
What happens if the payment succeeds but the inventory deduction fails? You cannot use a database transaction across services. You need complex patterns like Sagas, two phase commit, or eventual consistency. Each adds significant complexity.
At Futureaiit, we have seen teams spend months building saga orchestration frameworks when a simple database transaction would have worked fine.
2. Network Latency Compounds
In a monolith, a function call takes nanoseconds. In microservices, every inter service call is a network request taking milliseconds. A single user request might fan out to 5 services, each making additional calls, creating a cascade of network hops.
What was a 50ms request in a monolith becomes a 500ms request in microservices. Users notice. Conversion rates drop.
3. Debugging Becomes a Nightmare
"Why did this request fail?" In a monolith, you check one log file. In microservices, you need distributed tracing across 10 services, correlating request IDs, and piecing together what happened.
Tools like Jaeger and Datadog help, but they add cost and complexity. And when something goes wrong at 3am, you are still hunting through multiple log streams trying to find the root cause.
4. Deployment Complexity Explodes
Deploying a monolith: push to production, run migrations, restart the app. Deploying microservices: coordinate deployments across 10 services, manage API versioning, handle backward compatibility, orchestrate rollouts.
You need sophisticated CI/CD pipelines, feature flags, canary deployments, and rollback strategies. This is not impossible, but it is a massive investment.
The Solution: Modular Monolith
The best architecture for most companies is a modular monolith: one codebase, one deployment, but with strict module boundaries enforced at build time.
How It Works
Organize your code into modules with clear interfaces. Tools like Nx (for JavaScript) or Turborepo enforce these boundaries. If Module A tries to import a private function from Module B, the build fails.
Example structure:
modules/users/: User authentication and profilesmodules/orders/: Order managementmodules/inventory/: Inventory trackingmodules/payments/: Payment processing
Each module exposes a public API. Other modules can only call these public functions, not reach into internal implementation details.
Benefits of Modular Monolith
- Simple transactions: Use database transactions, no distributed sagas
- Fast inter-module calls: Function calls, not network requests
- Easy debugging: One log file, one stack trace
- Simple deployment: One artifact, one deploy
- Team autonomy: Teams own modules, not services
At Futureaiit, we have built modular monoliths for companies processing billions of dollars in transactions. They scale to hundreds of engineers without the microservices tax.
When to Actually Split into Microservices
Microservices are not inherently bad. They solve real problems. Extract a service only when you have a specific, compelling reason:
1. Independent Scaling Requirements
Your image processing workload needs 50 CPU heavy instances, but your API only needs 5. Splitting them into separate services lets you scale each independently.
Example: At Futureaiit, we worked with a video platform where transcoding required massive compute, but the API was lightweight. Splitting transcoding into a separate service saved $100k per year in infrastructure costs.
2. Different Technology Stacks
Your main app is in Python, but you need a real time recommendation engine in Go for performance. A separate service makes sense.
Warning: Do not split services just to use different languages. "We want to try Rust" is not a valid reason. Use different stacks only when there is a clear performance or ecosystem advantage.
3. Team Boundaries
You have acquired a company with a separate engineering team. Keeping their product as a separate service preserves team autonomy and avoids a risky migration.
This is organizational, not technical. But it is a valid reason.
4. Security Isolation
Your payment processing must be PCI compliant, but the rest of your app does not. Isolating payments into a separate service reduces your compliance scope.
Similarly, HIPAA compliance might require isolating healthcare data into a separate service with stricter access controls.
The Migration Path
If you start with a modular monolith and later need to extract a service, the migration is straightforward:
- Identify the module to extract: Choose a module with clear boundaries
- Create a new service: Copy the module code into a new repository
- Add an API layer: Expose the module's public functions as HTTP endpoints
- Update callers: Replace function calls with HTTP requests
- Migrate data: Move the module's database tables to a separate database
- Deploy and monitor: Roll out gradually, watch for issues
Because you enforced module boundaries from the start, the extraction is mechanical, not a risky rewrite.
Common Microservices Mistakes
1. Too Many Services
Do not create a service for every entity. "User Service," "Order Service," "Product Service," "Cart Service," "Wishlist Service"—this is overkill. You end up with dozens of tiny services that are harder to manage than a monolith.
Rule of thumb: Start with one service. Split only when you have a compelling reason.
2. Shared Databases
If your microservices share a database, they are not microservices. They are a distributed monolith, combining the worst of both worlds: monolith coupling with microservices complexity.
Each service must own its data. Other services access it only through APIs, never by querying the database directly.
3. Synchronous Communication Everywhere
If Service A calls Service B synchronously, and Service B calls Service C, you have a chain of blocking requests. One slow service brings down the entire chain.
Use asynchronous messaging (Kafka, RabbitMQ, SQS) for non critical paths. This decouples services and improves resilience.
4. No API Versioning
You deploy a breaking change to Service A. Service B, which depends on it, breaks. Now you have a production incident.
Always version your APIs. Support multiple versions simultaneously during transitions. This is non negotiable in microservices.
How Futureaiit Can Help
At Futureaiit, we help companies make the right architectural decisions for their stage and scale. We can help you:
- Design modular monoliths: Structure your codebase for long term maintainability
- Evaluate microservices readiness: Determine if you actually need microservices
- Plan service extraction: Identify which modules to split and when
- Implement distributed systems patterns: Sagas, event sourcing, CQRS when needed
- Set up observability: Distributed tracing, logging, and monitoring
- Rescue failed migrations: Fix microservices projects that have gone off the rails
We have built both monoliths and microservices at scale. We know when each makes sense, and we can guide you to the right choice for your business.
Conclusion
The microservices vs monolith debate is not about which is better. It is about which is better for your specific situation. For most companies, especially early stage startups, a modular monolith is the right choice. It gives you the benefits of modularity without the operational overhead of distributed systems.
When you do need microservices—for independent scaling, technology diversity, or organizational boundaries—extract them deliberately, one at a time, with clear justification.
At Futureaiit, we have seen too many companies adopt microservices prematurely and regret it. We have also seen companies stay with monoliths too long and struggle to scale. The key is making the right choice at the right time, based on your actual needs, not industry hype.
Need help with your architecture decisions? Contact Futureaiit to discuss whether a monolith, modular monolith, or microservices is right for your company.
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