Incremental migration plan in Microservices - Scalability & System Analysis

Scalability Analysis - Incremental migration plan

Growth Table: Incremental Migration Plan

Users	System State	Changes & Challenges
100 users	Monolith with initial microservices started	Basic microservices deployed; low traffic; minimal integration issues
10,000 users	Partial migration; some services fully independent	Increased inter-service communication; need for service discovery and API gateways
1,000,000 users	Majority services migrated; microservices communicate at scale	Database bottlenecks appear; need caching, read replicas; monitoring critical
100,000,000 users	Fully migrated; global distributed microservices	Network bandwidth and data partitioning bottlenecks; advanced sharding and CDN usage

First Bottleneck

At early scale (up to 10,000 users), the first bottleneck is the database because the monolith and microservices share the same database or have tightly coupled data. As traffic grows, database queries increase, causing latency and contention.

Scaling Solutions

• Database Decoupling: Gradually migrate data ownership to microservices with separate databases.
• Read Replicas & Caching: Use read replicas and caching layers (e.g., Redis) to reduce DB load.
• Service Discovery & API Gateway: Manage service communication efficiently.
• Horizontal Scaling: Add more instances of microservices behind load balancers.
• Sharding & Partitioning: Split databases by user or data type to handle large scale.
• CDN Usage: Cache static content closer to users to reduce bandwidth.

Back-of-Envelope Cost Analysis

• At 1M users, assume 10 requests/user/day -> ~10M requests/day ≈ 115 QPS average.
• Peak QPS can be 5x average -> ~575 QPS, within a few DB replicas' capacity.
• Storage grows with data; plan for TBs of data with backups and archiving.
• Network bandwidth must support inter-service calls and user traffic; consider 1 Gbps links for data centers.

Interview Tip

Start by describing the current system state and traffic. Identify the first bottleneck clearly. Then explain incremental steps to migrate and scale, focusing on decoupling, data ownership, and gradual rollout. Highlight monitoring and fallback plans to reduce risk.

Self Check

Your database handles 1000 QPS. Traffic grows 10x. What do you do first?

Answer: Implement read replicas and caching to reduce load on the primary database before considering more complex sharding or service scaling.

Key Result

Incremental migration starts with database bottlenecks at low scale; scaling solutions focus on decoupling data, caching, and horizontal scaling to handle millions of users smoothly.

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