Database per service pattern in Microservices - Architecture Diagram

System Overview - Database per service pattern

This system uses the Database per Service pattern to ensure each microservice has its own dedicated database. This design isolates data, improves service independence, and allows teams to choose the best database type for their service needs.

Key requirements include data isolation, independent service scaling, and avoiding direct database sharing between services.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  +-------------------+-------------------+
  |                   |                   |
Service A           Service B           Service C
  |                   |                   |
DB A                DB B                DB C
  

Components

User

client

Initiates requests to the system

Load Balancer

load_balancer

Distributes incoming requests evenly across API Gateway instances

API Gateway

api_gateway

Routes requests to appropriate microservices and handles authentication

Service A

service

Handles specific business logic and owns its own database DB A

Service B

service

Handles different business logic and owns its own database DB B

Service C

service

Handles another business domain and owns its own database DB C

DB A

database

Stores data exclusively for Service A

DB B

database

Stores data exclusively for Service B

DB C

database

Stores data exclusively for Service C

Request Flow - 8 Hops

User → Load Balancer

Load Balancer → API Gateway

API Gateway → Service A

Service A → DB A

DB A → Service A

Service A → API Gateway

API Gateway → Load Balancer

Load Balancer → User

Failure Scenario

Component Fails:DB B

Impact:Service B cannot read or write its data, causing failures in that service's features. Other services remain unaffected.

Mitigation:Implement database replication and failover for DB B. Service B can degrade gracefully or use cached data if available.

Architecture Quiz - 3 Questions

Why does each service have its own database in this pattern?

A To isolate data and allow independent service scaling

B To reduce the number of databases needed

C To allow users to access databases directly

D To share data easily between services

Design Principle

This pattern emphasizes strong service independence by giving each microservice its own database. This avoids tight coupling and allows teams to choose the best database technology per service, improving scalability and fault isolation.

Practice

1. What is the main advantage of the Database per service pattern in microservices architecture?

easy

A. It reduces the number of databases needed in the system.

B. All services share the same database for easier data management.

C. Each service can be developed, deployed, and scaled independently.

D. It allows direct database access between services.

Solution

1. Step 1: Understand the pattern's goal

   The Database per service pattern means each microservice owns its own database to avoid tight coupling.

2. Step 2: Analyze the benefits

   This independence allows each service to be developed, deployed, and scaled without affecting others.

3. Final Answer:

   Each service can be developed, deployed, and scaled independently. -> Option C

4. Quick Check:

   Service independence [OK]

Hint: Database per service means independent databases per microservice [OK]

Common Mistakes:

• Thinking all services share one database
• Assuming database sharing improves independence
• Believing it reduces total databases

2. Which of the following is the correct way for microservices to access data in the Database per service pattern?

easy

A. Directly query another service's database.

B. Use database triggers to sync data between services.

C. Share a common database connection pool.

D. Use APIs to communicate and request data from other services.

Solution

1. Step 1: Recall communication rules in this pattern

   Services do not share databases; they communicate via APIs to maintain independence.

2. Step 2: Identify correct data access method

   Using APIs ensures loose coupling and clear service boundaries.

3. Final Answer:

   Use APIs to communicate and request data from other services. -> Option D

4. Quick Check:

   API communication [OK]

Hint: Microservices talk via APIs, not direct DB access [OK]

Common Mistakes:

• Trying to query other service databases directly
• Assuming shared connection pools exist
• Using database triggers for cross-service sync

3. Consider two microservices: OrderService and InventoryService, each with its own database. If OrderService needs to check stock before placing an order, what is the correct flow?

medium

A. OrderService sends an API request to InventoryService to get stock information.

B. InventoryService pushes stock updates to OrderService's database.

C. OrderService writes stock info to its own database and reads from there.

D. OrderService queries InventoryService's database directly to check stock.

Solution

1. Step 1: Identify data ownership

   InventoryService owns stock data in its own database; OrderService cannot access it directly.

2. Step 2: Determine communication method

   OrderService must call InventoryService's API to get current stock info.

3. Final Answer:

   OrderService sends an API request to InventoryService to get stock information. -> Option A

4. Quick Check:

   API call for data [OK]

Hint: Always use API calls to get data from other services [OK]

Common Mistakes:

• Direct DB queries between services
• Duplicating data in multiple databases
• Relying on push updates to other service DBs

4. A developer tries to implement the Database per service pattern but notices data inconsistency between services. What is the most likely cause?

medium

A. Services are sharing the same database schema.

B. Services are directly querying each other's databases.

C. Services communicate asynchronously via APIs.

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

Solution

1. Step 1: Identify incorrect practice

   Directly querying another service's database breaks independence and can cause stale or inconsistent data.

2. Step 2: Understand correct communication

   Services should communicate via APIs to keep data consistent and boundaries clear.

3. Final Answer:

   Services are directly querying each other's databases. -> Option B

4. Quick Check:

   Direct DB queries cause inconsistency [OK]

Hint: Avoid direct DB queries between services to prevent inconsistency [OK]

Common Mistakes:

• Assuming shared schema is the problem
• Thinking async API calls cause inconsistency
• Believing separate DBs cause inconsistency

5. You are designing a microservices system with the Database per service pattern. How can you ensure data consistency across services when a transaction involves multiple services?

hard

A. Implement eventual consistency using event-driven communication and compensating actions.

B. Use distributed transactions with two-phase commit across all databases.

C. Allow services to share a single database to simplify transactions.

D. Synchronize databases by copying data between services periodically.

Solution

1. Step 1: Understand distributed transaction challenges

   Two-phase commit is complex and reduces service independence, so it's rarely used in microservices.

2. Step 2: Identify best practice for consistency

   Event-driven communication with eventual consistency and compensating actions allows services to stay independent and handle failures gracefully.

3. Final Answer:

   Implement eventual consistency using event-driven communication and compensating actions. -> Option A

4. Quick Check:

   Event-driven eventual consistency [OK]

Hint: Use events and compensations for cross-service consistency [OK]

Common Mistakes:

• Trying distributed two-phase commit in microservices
• Sharing a single database defeats independence
• Periodic data copying causes stale data