The document discusses the transition from monolithic architecture to event-driven microservices, highlighting the benefits of smaller codebases and autonomous teams. It addresses challenges related to distributed data, including consistency and querying, and introduces concepts such as domain-driven design, event sourcing, command query responsibility segregation, and sagas for maintaining data integrity. Ultimately, it emphasizes the importance of using event-driven architectures for achieving eventual consistency and facilitating faster innovation in software development.

1. Patterns & Practices for Implementing
Event-driven Microservices
Nikhil Barthwal
@nikhilbarthwal
nikhilbarthwal@hotmail.com
www.nikhilbarthwal.com

2. Agenda (1/2)
• Motivations to move from Monolithic to Microservices
• Understanding the Distributed Data in Microservices
• Using Domain Driven Design for partitioning data
• Problems with Distributed Data
• Event Driven Microservices
2

3. Agenda (2/2)
• Communication Patterns for Microservices
• Event Sourcing
• Command Query Responsibility Segregation
• Introducing Sagas
• Resources for further reading
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4. Monolithic: The old school approach …
• Large code base → Slower development
• More time to test & deploy
• Too much team interdependency
Database
Web Service
Easy to Develop, Test and Deploy …
But doesn’t scale!
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5. Microservices: The Brave new world ...
• Smaller code base to understand & change
• Autonomous teams
• Faster testing & deployment
Assembly of Loosely
coupled services!
Image Source: https://www.slideshare.net/JontheBeach/distributed-sagas-a-protocol-for-coordinating-microservices
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6. Loose Coupling → Distributed Data
Database per Service!
Faster Innovation!
Loosely coupled services
Reduces team interdependencies
Image Source: http://microservices.io/patterns/microservices.html
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7. How to create service boundaries?
An approach to software development for complex needs
by connecting the implementation to an evolving model.
• Entities
• Value Objects
• Bounded Context
• Aggregates
Infrastructure Layer
Domain Layer
Application Layer
User Interface
Use Domain Driven Design (DDD)!
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8. DDD: Aggregates
• Cluster of domain objects that
can be treated as a single unit
• One of its component is root
• All outside reference would
only go to the aggregate root
Domain Model
=
Collection of Aggregates
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9. Data Partition Strategies: Use DDD
Aggregates
provide
boundaries
for
partition
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10. Problems with Distributed Data
• How do we keep data consistent?
• How do we query scattered data?
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11. Cannot use ACID Transactions
BEGIN TRANSACTION
SELECT ADDRESS FROM CUSTOMERS WHERE CUSTOMER_ID = XXX
SELECT PRICE FROM PRODUCTS WHERE CUSTOMER_ID = YYY
INSERT INTO ORDERS ...
COMMIT TRANSACTION
Private to Customer service
Private to Product service
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12. Cannot use 2-Phase Commit
• Coordinator is a single point of failure
• Very chatty, with O(4n) messages, O(n2) with retries
• Locks would decrease throughputs
• Impacts availability (CAP theorem limitations)
Guarantees consistency, but …
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13. Consistency Eventual Consistency
Availability
Partition (Network)
Eventual Consistency
Use Event Driven Microservice Architecture!
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14. Event Driven Architecture
• Event occurs when a change happens in system
• All listeners get notified of the event, may take action
• Highly distributed/loosely coupled architecture
• Often used for asynchronous flows of information
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15. Communication: Direct Messaging
Benefits:
• Easier implementation
• Better Error control
Drawbacks:
• Increased coupling
• Difficult to scale
Order Service
Product
Service
Customer
Service
Fulfillment
Service
Payment
Service
Shipping
Service
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16. Communication: Via Message broker
Benefits:
• More scalable
• Increased Decoupling
Drawbacks:
• Requires Broker as Highly
Available component
Order Service
Product
Service
Customer
Service
Fulfillment
Service
Payment
Service
Shipping
Service
Message Broker
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17. Communication Patterns
Request/Response
(synchronous)
Event-Driven
(asynchronous)
Tier-3: Little to No impact for Customer
Tier-2: Impacting Customers indirectly
Tier-1: Directly Customer facing
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18. Event Sourcing: Introduction
• Modeling state changes as sequence of events
• Storing the event that could trigger the state change
• Enables rolling back to particular time in history
Examples:
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19. Event Sourcing: Snapshots
Alternative to playing events: Snapshots
19

20. Event Sourcing: Multiple views
Image Source: https://www.confluent.io/wp-content/uploads/2016/09/Event-sourced-based-architecture.jpeg
Adding applications that process event …
but create a different view!
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21. Event Sourcing: Benefits & Drawbacks
Benefits:
• 100% accurate audit logging
• Easy temporal queries
• Applications can process
same events but create views
Drawbacks:
• Adds Complexity
• No Strict Consistency
• Longer bootup times
(Snapshots can help)
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22. Command Query Responsibility
Segregation
CQRS Pattern
Must for Event Sourcing!
Read
Write
Image Source: https://martinfowler.com/bliki/CQRS.html
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23. CQRS: Benefits & Drawbacks
Benefits:
• Needed for Event Sourcing
• Improved separation of
concerns
• Supports scalable multiple
denormalized views
Drawbacks:
• Increased complexity
• Potential code duplication
• Replication lag as No Strict
Consistency
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24. Sagas: Introduction
• Based on a 1987 paper
• Initially for a single database running
on one node
• Now adapted for distributed systems
with asynchrony and partial failure
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25. Transaction & Rollback Transaction
• Every Transaction has a Rollback transaction
• This logic must be included in the service
T1 T2 T3
R1 R2 R3
Transactions →
Rollback Transactions →
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26. Sagas: Example
This action initiates the saga
Check Credit Service Withdrawal Service Deposit Service
Deposit Check
Long running transactions …
use compensating actions to handle failures!
Does Sender have
enough money in his
account?
Withdraw the money
(unless it is on hold)?
Deposit the money
(unless account is
deactivated)?
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27. Resources
• Using DDD to develop Microservices: https://www.infoq.com/news/2016/02/ddd-
microservices
• Overview of Saga Pattern: http://microservices.io/patterns/data/saga.html
• Distributed Sagas: https://www.slideshare.net/JontheBeach/distributed-sagas-a-
protocol-for-coordinating-microservices
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28. Summary
• Microservices enable faster innovation
• DDD can used to define service boundaries
• Data is distributed which create challenges
• Use Event Driven Architecture for eventual consistency
• Understand Event Sourcing & CQRS
• Use Sagas to maintain data consistency across services
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29. Thank you!
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Nikhil Barthwal
Questions?
@nikhilbarthwal
nikhilbarthwal@hotmail.com
www.nikhilbarthwal.com