Event store concept in Microservices - Architecture Diagram

System Overview - Event store concept

An event store system records all changes in the form of events. It supports microservices by storing events as the source of truth. Key requirements include reliable event storage, event replay, and supporting asynchronous communication between services.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
Command Service ---> Event Store ---> Event Bus ---> Multiple Microservices
                              |
                              v
                        Snapshot Store

Components

User

client

Initiates commands or queries to the system

Load Balancer

load_balancer

Distributes incoming requests evenly to API Gateway instances

API Gateway

api_gateway

Routes requests to appropriate services and handles authentication

Command Service

service

Receives commands, validates them, and writes events to the event store

Event Store

database

Stores all events in an append-only log for durability and replay

Event Bus

message_queue

Publishes events asynchronously to interested microservices

Multiple Microservices

service

Consume events to update their own state or trigger actions

Snapshot Store

database

Stores periodic snapshots of state to speed up event replay

Request Flow - 7 Hops

User → Load Balancer

Load Balancer → API Gateway

API Gateway → Command Service

Command Service → Event Store

Event Store → Event Bus

Event Bus → Multiple Microservices

Multiple Microservices → Snapshot Store

Failure Scenario

Component Fails:Event Store

Impact:New events cannot be stored, causing command failures; event replay and state recovery are blocked

Mitigation:Use replication and backups for event store; fallback to read-only mode from snapshots and caches; alert operators for quick recovery

Architecture Quiz - 3 Questions

Which component ensures commands are evenly distributed to avoid overload?

A Load Balancer

B Event Bus

C Snapshot Store

D API Gateway

Design Principle

This architecture uses event sourcing to store all changes as events in an append-only log. It decouples command processing from state updates by asynchronously publishing events via an event bus. Snapshots optimize recovery by reducing replay time. Load balancing and API gateway ensure scalability and security.

Practice

1. What is the primary purpose of an event store in a microservices architecture?

easy

A. To save every change as an immutable event in order

B. To store user credentials securely

C. To cache frequently accessed data for faster reads

D. To manage service discovery and load balancing

Solution

1. Step 1: Understand event store role

   An event store records all changes as events, preserving order and immutability.

2. Step 2: Compare options with event store purpose

   Only To save every change as an immutable event in order describes saving changes as immutable events in order, which matches event store's main function.

3. Final Answer:

   To save every change as an immutable event in order -> Option A

4. Quick Check:

   Event store = immutable ordered events [OK]

Hint: Event store saves changes as events, not data or cache [OK]

Common Mistakes:

• Confusing event store with caching layer
• Thinking event store manages security or load balancing
• Assuming event store modifies events after saving

2. Which of the following best describes the structure of data in an event store?

easy

A. A mutable key-value store with random access

B. An append-only log of immutable events

C. A relational database with tables and joins

D. A cache with time-to-live expiration

Solution

1. Step 1: Identify event store data structure

   Event stores keep data as an append-only log where events cannot be changed once stored.

2. Step 2: Match options to event store structure

   An append-only log of immutable events correctly describes an append-only log of immutable events, unlike mutable stores or caches.

3. Final Answer:

   An append-only log of immutable events -> Option B

4. Quick Check:

   Event store = append-only immutable log [OK]

Hint: Event store data is append-only and immutable, not mutable [OK]

Common Mistakes:

• Thinking event store allows event updates
• Confusing event store with relational databases
• Assuming event store is a cache with expiration

3. Given the following sequence of events stored in an event store:

1: UserCreated {userId: 1, name: "Alice"}
2: UserNameUpdated {userId: 1, name: "Alicia"}
3: UserDeleted {userId: 1}

What is the current state of the user with userId=1 after replaying these events?

medium

A. User with name "Alice" and deleted flag true

B. User with name "Alicia" exists

C. User with name "Alice" exists

D. User does not exist

Solution

1. Step 1: Replay events in order

   First event creates user Alice, second updates name to Alicia, third deletes the user.

2. Step 2: Determine final user state

   After deletion event, user no longer exists regardless of previous name changes.

3. Final Answer:

   User does not exist -> Option D

4. Quick Check:

   Last event is deletion, so user is gone [OK]

Hint: Last event determines existence; deletion means no user [OK]

Common Mistakes:

• Ignoring the delete event
• Assuming user name remains after deletion
• Confusing event replay order

4. You notice that your event store is allowing events to be updated after they are stored. What is the main issue with this behavior?

medium

A. It enables faster event replay by skipping old events

B. It improves performance by reducing storage needs

C. It breaks the immutability principle, causing inconsistent system state

D. It allows easier debugging by fixing event data

Solution

1. Step 1: Understand immutability in event stores

   Events must be immutable to ensure reliable replay and audit trails.

2. Step 2: Analyze impact of updating events

   Updating events breaks immutability, leading to inconsistent or incorrect system state.

3. Final Answer:

   It breaks the immutability principle, causing inconsistent system state -> Option C

4. Quick Check:

   Event immutability = consistent state [OK]

Hint: Events must never change after storing [OK]

Common Mistakes:

• Thinking event updates improve debugging
• Assuming updates improve performance
• Believing updates speed up replay

5. In a microservices system using an event store, how can you efficiently rebuild the current state of a service that has millions of events without replaying all events every time?

hard

A. Use snapshots to save intermediate states periodically

B. Delete old events after a certain time to reduce replay

C. Store only the latest event per entity to minimize data

D. Replay events in parallel without ordering

Solution

1. Step 1: Identify replay challenges with many events

   Replaying millions of events is slow and inefficient for rebuilding state.

2. Step 2: Evaluate solutions to speed up rebuilding

   Snapshots save the state at points in time, allowing replay from snapshot forward, reducing events to process.

3. Final Answer:

   Use snapshots to save intermediate states periodically -> Option A

4. Quick Check:

   Snapshots optimize replay by reducing event count [OK]

Hint: Snapshots speed up state rebuild, don't delete events [OK]

Common Mistakes:

• Deleting old events breaks audit and consistency
• Storing only latest event loses history
• Replaying events out of order causes errors