Incremental migration plan in Microservices - Deep Dive

Overview - Incremental migration plan

What is it?

An incremental migration plan is a step-by-step approach to move parts of a software system from a monolithic or legacy architecture to a microservices architecture. Instead of rewriting everything at once, it breaks the migration into smaller, manageable pieces. This helps reduce risk and allows continuous delivery of value during the transition.

Why it matters

Without an incremental migration plan, migrating to microservices can be risky, costly, and disruptive. A big-bang rewrite often leads to long downtime, bugs, and lost business opportunities. Incremental migration allows teams to keep the system running smoothly while gradually improving it, making the process safer and more predictable.

Where it fits

Before learning incremental migration plans, you should understand monolithic and microservices architectures. After this, you can explore advanced topics like service mesh, API gateways, and continuous delivery pipelines that support microservices.

Mental Model

Core Idea

Incremental migration breaks a big, risky change into small, safe steps that keep the system working while improving it.

Think of it like...

It's like renovating a house room by room instead of tearing down the whole house at once, so you can still live there and fix problems as you go.

┌───────────────┐
│ Legacy System │
└──────┬────────┘
       │ Identify a small part to migrate
       ▼
┌───────────────┐
│ Extract Service│
│ & Deploy      │
└──────┬────────┘
       │ Redirect traffic gradually
       ▼
┌───────────────┐
│ New Microservice│
└───────────────┘
       │ Repeat for next part
       ▼
┌───────────────┐
│ Fully Migrated │
│ Microservices  │
└───────────────┘

Build-Up - 7 Steps

1

Foundation

Understanding Monolith vs Microservices

Concept: Learn the difference between a monolithic system and microservices.

A monolithic system is built as one big application where all parts are tightly connected. Microservices split the system into small, independent services that communicate over the network. This separation allows teams to develop, deploy, and scale parts independently.

Result

You can identify why moving from monolith to microservices can improve flexibility and scalability.

Understanding the starting point and target architecture is essential before planning migration.

2

Foundation

Why Migration Needs a Plan

Concept: Recognize the risks of migrating without a clear strategy.

Migrating all at once can cause system downtime, bugs, and lost revenue. A plan helps break the work into smaller steps, reducing risk and allowing continuous operation.

Result

You see why incremental migration is safer and more practical than a big rewrite.

Knowing the dangers of big-bang migration motivates careful planning.

3

Intermediate

Identifying Migration Units

🤔Before reading on: do you think migration units should be based on technical layers or business capabilities? Commit to your answer.

Concept: Learn how to choose which parts of the system to migrate first.

Migration units are small, meaningful parts of the system, often aligned with business capabilities like user management or payments. Choosing the right unit helps isolate complexity and deliver value quickly.

Result

You can break the system into manageable pieces for migration.

Understanding how to slice the system reduces complexity and risk during migration.

4

Intermediate

Designing the Migration Steps

🤔Before reading on: do you think migration steps should be done in parallel or sequentially? Commit to your answer.

Concept: Plan the order and method of migrating each unit safely.

Each step involves extracting a service, deploying it, and redirecting traffic gradually. Steps are usually sequential to control risk, but some can run in parallel if independent.

Result

You have a clear roadmap for moving parts of the system one by one.

Knowing how to sequence migration steps helps maintain system stability.

5

Intermediate

Handling Data During Migration

Concept: Understand strategies to manage data consistency between old and new systems.

Data can be duplicated, synchronized, or migrated gradually. Techniques like database replication, event sourcing, or API adapters help keep data consistent while parts move to microservices.

Result

You can plan how to keep data accurate and available during migration.

Handling data carefully prevents errors and downtime during migration.

6

Advanced

Traffic Routing and Canary Releases

🤔Before reading on: do you think all users should switch to the new service at once or gradually? Commit to your answer.

Concept: Learn how to route user requests between old and new services safely.

Techniques like canary releases send a small percentage of traffic to the new service first. Monitoring helps catch issues early. Gradually increasing traffic reduces risk and builds confidence.

Result

You can deploy new services with minimal impact on users.

Gradual traffic shifting is key to safe, incremental migration.

7

Expert

Dealing with Cross-Service Dependencies

🤔Before reading on: do you think tightly coupled services make migration easier or harder? Commit to your answer.

Concept: Understand challenges when services depend heavily on each other.

Tightly coupled services require careful coordination during migration. Techniques like API gateways, service contracts, and backward compatibility help manage dependencies. Sometimes refactoring is needed before migration.

Result

You can handle complex dependencies without breaking the system.

Recognizing and managing dependencies prevents migration failures and downtime.

Under the Hood

Incremental migration works by isolating parts of the system and gradually replacing them with independent microservices. This involves code extraction, data synchronization, and traffic routing. Underneath, network calls replace internal function calls, and data consistency is maintained through replication or event-driven patterns. Monitoring and rollback mechanisms ensure stability during each step.

Why designed this way?

This approach was created to avoid the risks of big-bang rewrites, which often fail due to complexity and downtime. Incremental migration balances progress with stability, allowing teams to learn and adapt. Alternatives like full rewrites were rejected because they disrupt business and increase failure chances.

┌───────────────┐       ┌───────────────┐       ┌───────────────┐
│ Legacy System │──────▶│ Extract Service│──────▶│ New Microservice│
└──────┬────────┘       └──────┬────────┘       └──────┬────────┘
       │                       │                       │
       │  Data Sync & Routing  │                       │
       └──────────────────────▶│                       │
                               │                       │
                               └──────────────────────▶│
                                                       │
                                               Traffic Routing

Myth Busters - 4 Common Misconceptions

Quick: Do you think incremental migration means no downtime at all? Commit yes or no.

Common Belief: Incremental migration guarantees zero downtime during the whole process.

Reality: While incremental migration reduces downtime risk, some small downtime or degraded performance may still occur during certain steps.

Why it matters: Expecting zero downtime can lead to unrealistic plans and surprise outages.

Quick: Do you think you can migrate any part of the system in any order? Commit yes or no.

Common Belief: You can migrate services in any order without planning dependencies.

Reality: Migration order matters because some services depend on others; ignoring this causes failures.

Why it matters: Ignoring dependencies can break the system and cause costly rollbacks.

Quick: Do you think data migration is simple and automatic? Commit yes or no.

Common Belief: Data migration happens automatically when code is moved to microservices.

Reality: Data migration requires careful planning and tools to keep data consistent and available.

Why it matters: Poor data handling leads to data loss, corruption, or inconsistent user experience.

Quick: Do you think incremental migration is always faster than a full rewrite? Commit yes or no.

Common Belief: Incremental migration always completes faster than rewriting the whole system.

Reality: Incremental migration can take longer overall but reduces risk and improves stability.

Why it matters: Misjudging timelines can cause project delays and stakeholder frustration.

Expert Zone

1

Incremental migration often requires temporary adapters or anti-corruption layers to translate between old and new systems.

2

Monitoring and observability must be enhanced during migration to detect subtle issues early.

3

Sometimes partial rollback of migrated services is needed without affecting the whole system.

When NOT to use

Incremental migration is not ideal when the legacy system is very small or simple, where a full rewrite is faster. Also, if the system is unstable or poorly understood, a big-bang rewrite with a fresh design might be better. Alternatives include strangler pattern or greenfield development.

Production Patterns

Real-world migrations use feature toggles, API gateways for routing, event-driven data sync, and continuous integration pipelines to automate deployment. Teams often migrate business-critical services first to gain confidence and deliver value early.

Connections

Strangler Fig Pattern

Incremental migration builds on the strangler fig pattern by gradually replacing legacy parts.

Knowing the strangler fig pattern helps understand how to peel away legacy code safely.

Continuous Delivery

Incremental migration relies on continuous delivery to deploy small changes frequently and safely.

Understanding continuous delivery practices is essential to automate and control migration steps.

Urban Planning

Both incremental migration and urban planning involve phased development to avoid disruption.

Seeing migration as urban planning highlights the importance of managing dependencies and minimizing impact on users.

Common Pitfalls

#1 Migrating too many services at once causing system instability.

Wrong approach:

Extract and deploy 5+ services simultaneously without testing or traffic control.

Correct approach:

Migrate one service at a time, test thoroughly, and gradually shift traffic.

Root cause:

Underestimating complexity and overconfidence in system stability.

#2 Ignoring data synchronization leading to inconsistent user data.

Wrong approach:

Move service code but leave data only in legacy database without syncing.

Correct approach:

Implement data replication or event-driven sync between old and new databases.

Root cause:

Misunderstanding that code migration alone does not move data.

#3 Not planning for rollback causing prolonged outages on failure.

Wrong approach:

Deploy new service and switch all traffic immediately without fallback.

Correct approach:

Use canary releases and have rollback procedures ready to revert traffic quickly.

Root cause:

Lack of risk management and contingency planning.

Key Takeaways

Incremental migration breaks a big system change into small, manageable steps to reduce risk.

Choosing the right parts to migrate first and handling dependencies carefully is crucial for success.

Data synchronization and traffic routing strategies keep the system stable during migration.

Monitoring and rollback plans are essential to catch and fix issues quickly.

Incremental migration balances progress with stability, making it safer than big-bang rewrites.

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