Why each service owns its data in Microservices - Quick Recap

Recall & Review

beginner

What does it mean for a microservice to own its data?

It means the microservice has full control over its database or data storage. No other service directly accesses this data. This helps keep services independent and reduces errors.

beginner

Why should microservices avoid sharing databases?

Sharing databases creates tight connections between services. Changes in one service can break others. Owning data separately keeps services loosely connected and easier to change.

intermediate

How does owning data improve scalability in microservices?

Each service can scale its database independently based on its needs. This avoids bottlenecks and lets teams optimize performance for their specific data.

intermediate

What is a common pattern for services to share data without sharing databases?

Services communicate through APIs or events. One service publishes data changes, and others consume them. This keeps data ownership clear and services independent.

advanced

What risks arise if multiple services directly access the same database?

It can cause data conflicts, inconsistent states, and harder debugging. It also makes it difficult to deploy or update services independently.

Why does each microservice own its data?

A To use the same database for all services

B To share data easily with other services

C To keep services independent and reduce errors

D To avoid using APIs

Owning data keeps services independent and reduces errors caused by shared data access.

What is a downside of multiple services sharing one database?

A Tight coupling and harder maintenance

B Faster development

C Better scalability

D Clear data ownership

Sharing a database creates tight coupling and makes maintenance harder.

How do microservices share data without sharing databases?

A Direct database queries

B Using APIs or event messages

C Copying databases

D Ignoring data consistency

Services use APIs or events to share data while keeping ownership separate.

What benefit does data ownership bring to scaling microservices?

A All services scale together

B No need to scale databases

C Scaling is automatic without effort

D Each service can scale its data independently

Each service can scale its own data storage based on its needs.

What problem can arise if services share data storage directly?

A Data conflicts and inconsistent states

B Improved data security

C Faster deployment

D Simplified debugging

Direct sharing can cause conflicts and inconsistent data.

Explain why each microservice should own its data and not share databases.

Think about how sharing data can cause problems between teams and systems.

Describe how microservices can share data without breaking the rule of owning their own data.

Consider how messages or requests can pass data instead of sharing databases.

Practice

1. Why should each microservice own its own data instead of sharing a common database?

easy

A. To ensure services are independent and can evolve separately

B. To reduce the total amount of data stored in the system

C. To make it easier to write SQL queries across services

D. To allow all services to access data faster by sharing it

Solution

1. Step 1: Understand service independence

   Each microservice owning its data means it can change its database without affecting others.

2. Step 2: Recognize benefits of separate data ownership

   This independence improves scalability and reduces tight coupling between services.

3. Final Answer:

   To ensure services are independent and can evolve separately -> Option A

4. Quick Check:

   Service independence = D [OK]

Hint: Think about service independence and avoiding tight coupling [OK]

Common Mistakes:

• Assuming shared databases improve performance
• Believing data sharing reduces storage needs
• Thinking SQL queries are easier with shared data

2. Which of the following is the correct way for microservices to access data owned by another service?

easy

A. Directly querying the other service's database

B. Sharing a common database schema

C. Using APIs or messaging to request data

D. Copying the entire database locally

Solution

1. Step 1: Identify proper data access method

   Microservices should not access each other's databases directly to avoid tight coupling.

2. Step 2: Recognize communication via APIs or messages

   Services communicate data through APIs or messaging systems to maintain independence.

3. Final Answer:

   Using APIs or messaging to request data -> Option C

4. Quick Check:

   Data access via APIs/messages = B [OK]

Hint: Remember: no direct DB access, use APIs or messages [OK]

Common Mistakes:

• Trying to query another service's database directly
• Assuming shared schema is best practice
• Copying entire databases unnecessarily

3. Consider two microservices: Service A owns customer data, and Service B owns order data. Service B needs customer info to process orders. Which approach correctly respects data ownership?

medium

A. Service B queries Service A's database directly for customer info

B. Service B calls Service A's API to get customer info

C. Service B duplicates customer data in its own database

D. Service B uses a shared database for both customer and order data

Solution

1. Step 1: Identify correct data access respecting ownership

   Service B should not access Service A's database directly or share databases.

2. Step 2: Use API calls for data retrieval

   Calling Service A's API allows Service B to get needed data without breaking ownership rules.

3. Final Answer:

   Service B calls Service A's API to get customer info -> Option B

4. Quick Check:

   API calls respect ownership = A [OK]

Hint: Use APIs to get data from other services, not direct DB access [OK]

Common Mistakes:

• Direct DB queries across services
• Duplicating data causing inconsistency
• Using shared databases breaking independence

4. A team notices that two microservices share a database schema and directly query each other's tables. What is the main problem with this design?

medium

A. It causes tight coupling and reduces service independence

B. It improves scalability by sharing data

C. It simplifies API design between services

D. It reduces the need for data synchronization

Solution

1. Step 1: Analyze impact of shared database schema

   Sharing schema and direct queries create tight coupling between services.

2. Step 2: Understand consequences on independence

   Tight coupling reduces the ability to change or scale services independently.

3. Final Answer:

   It causes tight coupling and reduces service independence -> Option A

4. Quick Check:

   Tight coupling problem = C [OK]

Hint: Shared DB means tight coupling, which is bad for microservices [OK]

Common Mistakes:

• Thinking shared DB improves scalability
• Assuming it simplifies API design
• Believing it removes sync needs

5. You are designing a microservices system with three services: User, Inventory, and Order. Each service owns its data. How should you handle a scenario where the Order service needs to confirm inventory availability before placing an order?

hard

A. All services share a single database to simplify data access

B. Order service queries Inventory service's database directly to check stock

C. Order service duplicates inventory data locally and updates it periodically

D. Order service calls Inventory service's API to check stock availability

Solution

1. Step 1: Respect data ownership in design

   Each service must own and manage its own data; direct DB queries or shared DB break this.

2. Step 2: Use API calls for inter-service communication

   Order service should call Inventory service's API to get real-time stock info, ensuring data consistency and independence.

3. Final Answer:

   Order service calls Inventory service's API to check stock availability -> Option D

4. Quick Check:

   API communication respects ownership = A [OK]

Hint: Always use APIs for cross-service data, never direct DB access [OK]

Common Mistakes:

• Direct DB queries breaking independence
• Duplicating data causing stale info
• Using shared DB increasing coupling