Incremental migration plan in Microservices - System Design Guide

Problem Statement

Rewriting or replacing a large monolithic system all at once causes long downtime, high risk of failure, and difficulty isolating issues. This can lead to lost revenue and frustrated users if the new system breaks critical functionality.

Solution

The incremental migration plan breaks the migration into small, manageable steps. Parts of the old system are gradually replaced by microservices, allowing continuous operation and easier rollback. This approach reduces risk by isolating changes and enabling testing of each component independently.

Architecture

┌───────────────┐       ┌───────────────┐       ┌───────────────┐
│   Monolith    │──────▶│ Microservice 1│──────▶│ Microservice 2│
│ (Legacy Code) │       │ (New Service) │       │ (New Service) │
└───────────────┘       └───────────────┘       └───────────────┘
        │                      │                       │
        │                      │                       │
        ▼                      ▼                       ▼
   Clients/Users           API Gateway             Database

This diagram shows a monolithic system gradually replaced by microservices. Traffic flows from clients through an API gateway that routes requests to either the monolith or new microservices during migration.

Trade-offs

✓ Pros

→

Reduces downtime by allowing the system to remain partially operational during migration.

→

Limits risk by isolating changes to small components, making debugging easier.

→

Enables gradual testing and validation of new microservices before full cutover.

→

Allows teams to migrate at their own pace, improving resource management.

✗ Cons

→

Requires maintaining and supporting both old and new systems simultaneously, increasing complexity.

→

Integration between monolith and microservices can introduce latency and data consistency challenges.

→

Migration planning and coordination overhead can be significant.

When migrating large, complex monoliths with critical uptime requirements and multiple teams available to work on incremental components.

When the system is small or simple enough to be rewritten and deployed in a single release without unacceptable downtime.

Real World Examples

Netflix

Migrated from a monolithic DVD rental system to microservices incrementally to avoid service disruption and allow continuous streaming service.

Amazon

Gradually decomposed their monolithic e-commerce platform into microservices to improve scalability and deployment speed.

Uber

Incrementally replaced monolithic dispatch and pricing systems with microservices to enable faster feature development and reliability.

Code Example

The before code shows a monolithic service handling all logic. The after code splits payment processing into a new microservice, allowing incremental migration by delegating specific functionality.

Microservices

### Before: Monolith handles all requests
class OrderService:
    def create_order(self, data):
        # All logic tightly coupled
        pass

### After: Incremental migration with microservice for payment
class OrderService:
    def create_order(self, data):
        # Delegate payment to new microservice
        payment_result = PaymentMicroservice.process_payment(data['payment'])
        if payment_result.success:
            # Continue order creation
            pass

class PaymentMicroservice:
    @staticmethod
    def process_payment(payment_data):
        # New isolated payment logic
        return PaymentResult(success=True)

class PaymentResult:
    def __init__(self, success):
        self.success = success

Alternatives

Big Bang Migration

Replaces the entire system in one large deployment instead of step-by-step.

Use when: When the system is small or downtime can be tolerated for a short period.

Strangler Fig Pattern

Wraps the old system with a new facade and gradually replaces functionality behind it.

Use when: When you want to isolate legacy system completely behind a new API gateway.

Summary

Incremental migration breaks a large system rewrite into small, manageable steps to reduce downtime and risk.

It allows old and new systems to run side-by-side, enabling gradual testing and rollback.

This approach is best for complex systems requiring continuous availability during migration.

Practice

1. What is the main goal of an incremental migration plan in microservices?

easy

A. To avoid testing during migration

B. To rewrite the entire system at once

C. To remove all old services immediately

D. To move functionality step-by-step to reduce risk

Solution

1. Step 1: Understand migration goals

   Incremental migration aims to reduce risk by breaking changes into small steps.

2. Step 2: Compare options

   Options B, C, and D involve big changes or skipping testing, which increase risk.

3. Final Answer:

   To move functionality step-by-step to reduce risk -> Option D

4. Quick Check:

   Incremental migration = step-by-step safe moves [OK]

Hint: Think small safe steps, not big risky jumps [OK]

Common Mistakes:

• Assuming migration happens all at once
• Ignoring the need for testing
• Believing old services must be removed immediately

2. Which of the following is a correct step in an incremental migration plan?

easy

A. Deploy all new microservices simultaneously without routing changes

B. Use feature flags or routing to direct some traffic to new services

C. Stop the old system before starting migration

D. Skip monitoring during migration to save resources

Solution

1. Step 1: Identify safe deployment practices

   Using feature flags or routing allows gradual traffic shift to new services safely.

2. Step 2: Eliminate unsafe options

   Deploying all at once, stopping old system early, or skipping monitoring are risky.

3. Final Answer:

   Use feature flags or routing to direct some traffic to new services -> Option B

4. Quick Check:

   Routing traffic gradually = safe migration [OK]

Hint: Use routing or flags to control traffic flow [OK]

Common Mistakes:

• Deploying everything at once
• Stopping old system too early
• Ignoring monitoring during migration

3. Consider this migration step code snippet for routing traffic:

if (user.isBetaTester) {
  routeToNewService();
} else {
  routeToOldService();
}

What will happen if a user is not a beta tester?

medium

A. User traffic is dropped

B. User traffic goes to the new service

C. User traffic goes to the old service

D. User traffic causes an error

Solution

1. Step 1: Analyze the condition

   If user.isBetaTester is false, the else branch runs.

2. Step 2: Determine routing for else branch

   The else branch calls routeToOldService(), so traffic goes to old service.

3. Final Answer:

   User traffic goes to the old service -> Option C

4. Quick Check:

   Non-beta users = old service routing [OK]

Hint: False condition triggers else branch routing [OK]

Common Mistakes:

• Assuming all users go to new service
• Thinking traffic is dropped or errors occur
• Ignoring the else branch logic

4. A team started migrating a service incrementally but suddenly disabled monitoring. What is the likely problem?

medium

A. They lose visibility into errors and performance

B. They can detect issues faster

C. Migration speed increases without risks

D. Old services automatically update

Solution

1. Step 1: Understand monitoring role

   Monitoring helps detect errors and performance issues during migration.

2. Step 2: Assess impact of disabling monitoring

   Without monitoring, the team loses visibility into problems, increasing risk.

3. Final Answer:

   They lose visibility into errors and performance -> Option A

4. Quick Check:

   No monitoring = no error visibility [OK]

Hint: Never disable monitoring during migration [OK]

Common Mistakes:

• Assuming disabling monitoring improves speed
• Thinking old services update automatically
• Believing issues are easier to detect without monitoring

5. You plan to migrate a monolith to microservices incrementally. Which approach best ensures minimal downtime and rollback capability?

hard

A. Deploy new microservices behind a feature flag and route a small % of traffic gradually

B. Replace the monolith entirely in one deployment window

C. Migrate database schema all at once without backward compatibility

D. Disable old services immediately after deploying new ones

Solution

1. Step 1: Evaluate migration strategies

   Deploying behind feature flags and routing small traffic allows gradual testing and rollback.

2. Step 2: Compare risks of other options

   Replacing all at once or disabling old services causes downtime; schema changes without compatibility break systems.

3. Final Answer:

   Deploy new microservices behind a feature flag and route a small % of traffic gradually -> Option A

4. Quick Check:

   Feature flags + gradual traffic = safe migration [OK]

Hint: Use feature flags and gradual traffic shift for safety [OK]

Common Mistakes:

• Trying big-bang replacement causing downtime
• Ignoring backward compatibility in database changes
• Disabling old services too early