Streams for Apache Kafka | Event Streaming And Real Time Data Processing - Short RH1

with Red Hat Streams for Apache Kafka

Building an Event Streaming and Real Time Data Processing system

Untitled presentation - Google Slides

Globex Online

1. Activity tracker service to track user activity and stream to a kafka topic

2. Recommendation Engine Service to consume from this topic and send a list popular products to another Kafka topic 

3. The Webstore application uses this list to display featured products


Globex Architecture

Kafka
Topics
Event
Streaming
And
Real
Time
Data
Processing
AMQ
streams,
Quarkus
Track
user
activity
Analyse
real
time
with
Kafka
Streams
and
display
Featured
Products

[External] Cloud Native Architecture Workshop Overview - Google Slides

A
globex-app-user1
A
kafdrop
A
strimzi-kafka
K
kafka
D
activi…acking
D
recomm…engine
D
catalog
D
inventory
D
activi…ulator
D
invent…tabase
D
catalog-database
D
kafdrop
D
kafka-…erator
D
globex-ui

Topology · Red Hat OpenShift

OpenAPI UI (Powered by Quarkus 2.13.3.Final)

Name
Hide internal topics 
Name
tracking
Clear all filters
Name
	Status 	Partitions	Consumer groups	
Storage
	

globex.tracking
Managed
	
 Fully replicated	1	1	31.373 KiB

Red Hat streams for Apache Kafka console

Message
Partition
0
Offset
88
Size 
291 B
Timestamp (local)
November 26, 2024 at 2:40:41 PM PST
Timestamp (UTC)
November 26, 2024 at 10:40:41 PM UTC
Unix timestamp
1732660841
Value
Key
Headers
{
idSite:"globex-retail",
activity:{
userId:"d2a290f5-104a-4f88-baea-299f96e94bfc",
url:"https://globex-retail.com/product/329199/details",
rand:"f32edba8-c4c9-4e8d-b734-7e25b3e48965",
type:"like"
},
userInfo:{
localTime:"2024-11-26T22:40:37+0000"
},
actionInfo:{
productId:"329199"
}
}

globex.recommendation-product-score-aggregated-changelog

Message
Partition
0
Offset
0
Size 
583 B
Timestamp (local)
November 26, 2024 at 2:40:41 PM PST
Timestamp (UTC)
November 26, 2024 at 10:40:41 PM UTC
Unix timestamp
1732660841
Value
Key
Headers
[
{
productId:"329199",
score:17,
category:"product"
},
{
productId:"RHNL-006",
score:15,
category:"product"
},
{
productId:"444434",
score:10,
category:"product"
},
{
productId:"RHNL-002",
score:7,
category:"product"
},
{
productId:"RHNL-017",
score:5,
category:"product"
},
{
productId:"RHNAM-250",
score:4,
category:"product"
},
{
productId:"RHNAM-054E-RED",
score:3,
category:"product"
},
{
productId:"RHNAM-234",
score:3,
category:"product"
},
{
productId:"RHNAM-219-BLKGRY",
score:3,
category:"product"
},
{
productId:"RHNL-016",
score:3,
category:"product"
}
]

Learn more about Red Hat's Kafka Offering

 We've now successfully built an event streaming platform using Red Hat Streams for Apache kafka to track user activity on an ecommerce website to find out the most popular products in the store and build a recommendation engine. 

We hope you found this walkthrough useful. Below are some resources that can help you get started with your event streaming and real time data processing journey