Shared database anti-pattern in Microservices - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the main issue with shared databases in microservices.

Microservices

The shared database anti-pattern causes [1] between microservices.

Drag options to blanks, or click blank then click option'

Adata isolation

Bloose coupling

Cindependent scaling

Dtight coupling

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing loose coupling, which is the opposite of the problem.

Confusing data isolation with shared data.

Shared databases cause tight coupling because services depend on the same data structure.

2fill in blank

medium

Complete the code to explain a consequence of the shared database anti-pattern.

Microservices

One consequence is that [1] can become a bottleneck for all services.

Drag options to blanks, or click blank then click option'

Athe shared database

Bthe network

Cthe user interface

Dthe cache

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting network or cache, which are not the main bottlenecks here.

The shared database can slow down all services because they all access it.

3fill in blank

hard

Fix the error in the statement about shared database anti-pattern.

Microservices

Shared databases do not allow microservices to [1] their data independently.

Drag options to blanks, or click blank then click option'

Aisolate

Bshare

Cupdate

Dmanage

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'update' or 'manage' which imply control but miss the isolation issue.

Shared databases prevent services from isolating their data, causing tight coupling.

4fill in blank

hard

Fill both blanks to describe a better alternative to shared databases.

Microservices

Use [1] databases and [2] communication between services.

Drag options to blanks, or click blank then click option'

Aseparate

Bshared

Casynchronous

Dsynchronous

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing shared databases or synchronous communication, which keep tight coupling.

Separate databases reduce coupling, and asynchronous communication improves scalability.

5fill in blank

hard

Fill all three blanks to complete the microservices design avoiding shared database anti-pattern.

Microservices

Each service owns its [1], communicates via [2], and uses [3] for data consistency.

Drag options to blanks, or click blank then click option'

Adatabase

Bevents

Ceventual consistency

Dshared cache

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting shared cache, which reintroduces coupling.

Owning databases, using events for communication, and eventual consistency help avoid tight coupling.

Practice

1. What is the main problem caused by the shared database anti-pattern in microservices?

easy

A. Better fault isolation between services

B. Tight coupling between services due to shared data schema

C. Easier scaling of individual services

D. Improved performance by sharing data directly

Solution

1. Step 1: Understand the shared database anti-pattern

   This anti-pattern happens when multiple microservices use the same database schema directly.

2. Step 2: Identify the impact on service independence

   Sharing the database causes tight coupling, making services dependent on each other's data structure changes.

3. Final Answer:

   Tight coupling between services due to shared data schema -> Option B

4. Quick Check:

   Shared database = Tight coupling [OK]

Hint: Shared DB means tight coupling, breaking microservices independence [OK]

Common Mistakes:

• Thinking shared DB improves scaling
• Assuming shared DB isolates faults
• Believing shared DB simplifies service design

2. Which of the following is the correct way to avoid the shared database anti-pattern in microservices?

easy

A. Use a single database schema shared by all services

B. Store all data in a centralized monolithic database

C. Allow direct SQL queries from one service to another's database

D. Each service owns its own database and communicates via APIs

Solution

1. Step 1: Recall best practice for microservice data management

   Each microservice should have its own database to maintain independence.

2. Step 2: Identify the correct communication method

   Services communicate through APIs, not by sharing databases or direct queries.

3. Final Answer:

   Each service owns its own database and communicates via APIs -> Option D

4. Quick Check:

   Separate DB + APIs = Avoid shared DB anti-pattern [OK]

Hint: Separate DB per service + API calls avoid shared DB anti-pattern [OK]

Common Mistakes:

• Choosing shared schema for simplicity
• Allowing direct cross-service DB queries
• Centralizing all data in one DB

3. Consider two microservices, Service A and Service B, sharing the same database. Service A changes a table schema without informing Service B. What is the most likely outcome?

medium

A. Service B automatically adapts to the new schema

B. Service B continues working without issues

C. Service B experiences runtime errors due to schema mismatch

D. Both services improve performance

Solution

1. Step 1: Analyze the impact of schema change on shared DB

   When services share a database, schema changes affect all services using it.

2. Step 2: Predict Service B's behavior

   Service B expects the old schema; a change causes runtime errors like failed queries or crashes.

3. Final Answer:

   Service B experiences runtime errors due to schema mismatch -> Option C

4. Quick Check:

   Schema change + shared DB = runtime errors [OK]

Hint: Schema change in shared DB breaks other services [OK]

Common Mistakes:

• Assuming automatic schema adaptation
• Believing no impact on other services
• Thinking performance improves

4. You find that two microservices share a database causing tight coupling and deployment issues. Which change fixes this problem?

medium

A. Create separate databases and add API communication

B. Merge the two services into one monolith

C. Add more indexes to the shared database

D. Allow both services to write to the same tables

Solution

1. Step 1: Identify the root cause of tight coupling

   Sharing the same database schema causes deployment and coupling problems.

2. Step 2: Apply the correct fix

   Separating databases and using APIs decouples services and allows independent deployment.

3. Final Answer:

   Create separate databases and add API communication -> Option A

4. Quick Check:

   Separate DB + APIs fix shared DB anti-pattern [OK]

Hint: Separate DB + APIs fix tight coupling from shared DB [OK]

Common Mistakes:

• Merging services loses microservice benefits
• Adding indexes doesn't fix coupling
• Allowing shared writes keeps tight coupling

5. A company has three microservices sharing one database. They want to migrate to avoid the shared database anti-pattern. Which approach best balances data consistency and service independence?

hard

A. Split databases per service and use event-driven messaging for data sync

B. Keep shared database but add strict schema versioning

C. Merge all services into a single database schema with shared tables

D. Use direct SQL queries between services to keep data consistent

Solution

1. Step 1: Understand the trade-offs in migration

   Separating databases improves independence but can cause data consistency challenges.

2. Step 2: Choose a pattern that balances consistency and independence

   Event-driven messaging allows services to sync data asynchronously while keeping separate databases.

3. Final Answer:

   Split databases per service and use event-driven messaging for data sync -> Option A

4. Quick Check:

   Separate DB + events balance consistency and independence [OK]

Hint: Use separate DB + events for sync to avoid shared DB anti-pattern [OK]

Common Mistakes:

• Keeping shared DB limits independence
• Merging services loses microservice benefits
• Using direct SQL breaks service boundaries