This document discusses event driven architecture (EDA). EDA consists of independent components that process asynchronous events. There are two approaches to EDA - publish/subscribe where events are sent to subscribers, and event streaming where events are written to a log. EDA provides advantages like scalability and flexibility but also challenges like increased maintenance. The document presents a case study of how EDA was used to integrate different healthcare systems for a dialysis services provider.

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Introduction to Event Driven Architecture
May 20, 2019 | Authors: Manish Pathak & Rohit Kukreti, CitiusTech
CitiusTech Thought
Leadership

2. 2
Agenda
▪ Introduction to Event Driven Architecture (EDA)
▪ EDA – Advantages & Disadvantages
▪ EDA in Cloud
▪ EDA in Healthcare – Case Study
▪ Conclusion
▪ References

3. 3
Event Driven Architecture (EDA) is a software architecture pattern for facilitating
communication or integration between disparate software systems or components. It
consists of atomic decoupled components responsible for asynchronous event processing.
This EDA design helps in building highly scalable and distributed systems.
There are a few terms to be kept in mind:
▪ Event – It’s a signal emitted by component or application every time there’s a change
in the system. It’s an independent unit of message, and consists of adequate
information for event processors to continue work. This decouples the event producers
from event processors
▪ Event Producer & Event Processors – These are the components that generate and
react to events respectively
Introduction to Event Driven Architecture (1/3)

4. 4
There are two ways to implement an Event Driven Architecture:
▪ Pub / Sub
• In this model, the messaging infrastructure keeps track of all the subscriptions
• When an event is published, the messaging infrastructure re-sends the event to
each event processor (also called a subscriber)
• After an event is received, it cannot be replayed and new subscribers don’t see the
event
▪ Event Streaming
• In the event streaming model, events are written to a log or a store
• Events are strictly ordered (within a partition) and are durable
• Event processors (also called clients) don't subscribe to the stream, but can read
from any part of the stream
• Clients handle advancing its position in the stream which allows them to join
anytime and replay events
Introduction to Event Driven Architecture (2/3)

5. 5
Event processing is further categorized as:
▪ Simple Event Processing – The client processes the event immediately after receiving
it. It’s used for real-time or near real-time workflows and can help reduce lag time
▪ Complex Event Processing – The client processes a series of events and based on
the results it performs respective activities. E.g., Consumers read data from wireless
health monitoring system for a certain period and generates notifications if
the aggregated values cross the threshold
▪ Event Streaming Processing – In event streaming processing, data streaming platforms
like Azure IoT Hub or Apache Kafka is used to ingest events. Different stream
processors read and process the event stream for any transformation activities
Introduction to Event Driven Architecture (3/3)

6. 6
Advantages Disadvantages
Scalability – Enables highly scalable
distributed systems as producers and
processors are independent of each other
High Maintenance – As the system grows
and additional events and processors
become a part of the system, the
maintenance overhead tends to increase
Flexibility – Helps create a flexible system as
the components / services are loosely
coupled making it easier to add new or
modify an existing component / service
Constant Updates – Evolving and changing
event schema requires changes to all the
processors
High Performance – As broadcasters do not
wait for the processors to process the
messages, the system tends to be much
more performant
Consistency – Maintaining consistency of
data state across multiple processors is non-
trivial
EDA – Advantages and Disadvantages

7. 7
▪ Recently, public cloud vendors have started providing services like Queues, Topics, etc.
making seamless integration possible between various components
▪ Technologies like serverless architecture, micro services, stream analytics, etc. enable
designing of complex scenarios and services like Azure IoT Hub, Event Hub or Apache
Kafka on the cloud
▪ This has allowed event processing for heavy work load feasible along with several
types of transformation for multiple sub-systems
EDA in Healthcare (typical uses cases)
▪ Integrating different systems like enrollment, billing, etc. can be accomplished using
EDA. Here data entry in one system raises an event for other systems to process and
perform actions
▪ Personal Health Monitoring systems like remote patient monitoring systems are suited
for EDA. Devices can stream patient health data to services like Azure IoT Hub or
Apache Kafka and the recipient processing services can process the data as required
EDA in Cloud

8. 8
Situation
The client is a leading provider of Dialysis Services. They wanted to build a communication
platform to provide curated content to individual physicians; automate the existing legacy
manual compliance processes; and provide an application for important physician
resources.
Solution
▪ CitiusTech partnered with the client to develop the system using a polygot approach
▪ The components were developed in Java, node.js, Python and the pub / sub model of
EDA was used to establish communication between these components
▪ Each component published an appropriate set of events / messages to the service bus
queue where it’s read and processed by the consumer components
▪ Many services behaved as a publisher and a subscriber, both. This enabled different
development teams to enhance individual components / modules using development
languages / tools of their choice
EDA in Healthcare – Case Study (1/2)

9. 9
With EDA, these components / modules could seamlessly communicate with each
other, and the client was able to develop new features and enhance its applications
to meet changing business requirements without the need to rewrite existing
modules.
EDA in Healthcare – Case Study (2/2)
Figure – System Schematic

10. 10
Today interconnectivity has become a core architectural need. EDA enables different
independent systems / components to connect seamlessly in a cost-effective manner. EDA
is a good fit for systems where:
▪ Low latency and near real time responsive times are crucial
▪ 2 phase commit or processing order / sequence is important
▪ Traditional batch processing or data collection methodologies need to be replaced.
▪ EDA in conjunction with request driven or synchronous systems can create a highly
scalable, consistent and always available systems
Conclusion

11. 11
▪ https://wso2.com/whitepapers/event-driven-architecture-the-path-to-increased-agility-and-high-
expandability/
▪ https://thenewstack.io/3-key-design-considerations-event-driven-architecture/
References

12. 12
Thank You
Authors:
Manish Pathak & Rohit Kukreti
Cloud Practice
thoughtleaders@citiustech.com
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