1.
Coral: a Web API for Real-Time
Streaming Computing
@natalinobusa | linkedin.com/in/natalinobusa
Towards Real-Time
Banking APIs

2.
Distributed computing Machine Learning
Statistics Big/Fast Data Streaming Computing
@natalinobusa | linkedin.com/in/natalinobusa

3.
Why Streaming Processing?
@natalinobusa | linkedin.com/in/natalinobusa

4.
Why Streaming Processing?
1. Relevant up-to-date information.
2. Delivers actionable events.
@natalinobusa | linkedin.com/in/natalinobusa

5.
Streaming Processing.
Inspiration:
@natalinobusa | linkedin.com/in/natalinobusa

6.
"Pedalboard (995939579)-2" by Pedalboard_(995939579).jpg: Michael
Morel from Barcelona, Spainderivative work: Atlantictire (talk) -
Pedalboard_(995939579).jpg. Licensed under Creative Commons
Attribution 2.0 via Wikimedia Commons -

7.
It’s all about the right “sound”
@natalinobusa | linkedin.com/in/natalinobusa

8.
It’s all about the right “sound”
@natalinobusa | linkedin.com/in/natalinobusa
Read from
Twitter stream
Sentiment
Analytics
Push
recommendations

9.
These resources
can be modeled via a web API !
@natalinobusa | linkedin.com/in/natalinobusa

10.
It’s all about the right “sound”
@natalinobusa | linkedin.com/in/natalinobusa

11.
It’s all about the right “sound”
@natalinobusa | linkedin.com/in/natalinobusa
Two sort of resources:
- devices
- waves

12.
resource type #1: Actors
Trigger Emit
Params
State
@natalinobusa | linkedin.com/in/natalinobusa

13.
resource type #1: Actors
Trigger Emit
Params
State
POST http://coral/api/actors
{
"type":"stats",
"params":{
"field": "amount"
},
"group":{
"by":"tag"
}
}
@natalinobusa | linkedin.com/in/natalinobusa

14.
resource type #1: Actors
Trigger Emit
Params
State
GET http://coral/api/actors/23
{
"actors": {
"def": {
"type": "stats",
"params": {
"field": "amount"
}
},
"state": {
"count": 134,
"avg": 39.84,
"min": 1.99,
"max": 204.19,
"sd": 38.01
}
}
}
@natalinobusa | linkedin.com/in/natalinobusa

15.
REST API:
dynamically compose your data-flow
processing
@natalinobusa | linkedin.com/in/natalinobusa

16.
resource type #2: Data quants/events
Data
events
data resources:
● RESTful
● Ephemeral
● Form Free
● Json
@natalinobusa | linkedin.com/in/natalinobusa

17.
resource type #2: Data quants/events
Data
events
POST http://coral/api/actors/23/in
{
"amount":23.45,
"user": 76232,
"city": "Berlin"
}
@natalinobusa | linkedin.com/in/natalinobusa

18.
resource type #2: Data quants/events
Data
events
POST http://coral/api/actors/23/in
The “in” endpoint describes not the
single events but the stream as a
ever-changing RESTful resource.
@natalinobusa | linkedin.com/in/natalinobusa

19.
Connecting to the world
@natalinobusa | linkedin.com/in/natalinobusa

20.
How do RESTful Actors produce and
consume data?
@natalinobusa | linkedin.com/in/natalinobusa
Actor can connect as a
● Client
● Server

21.
How do RESTful Actors produce and
consume data?
Actor can communicate as
● http req/resp
● (long) polling
● Server Sent Events
● Web Sockets
@natalinobusa | linkedin.com/in/natalinobusa

22.
Some examples:
API: REST server
Actor: REST client
API
Old Skool
polling
@natalinobusa | linkedin.com/in/natalinobusa

23.
How to get streaming? Some examples:
API: REST server
Actor: REST client
API
API: SSE Streaming Server
Actor: Streaming client
API
Old Skool
polling
Streaming
Server-Sent-Events
@natalinobusa | linkedin.com/in/natalinobusa

24.
Some examples:
API: REST server
Actor: REST client
API
Client Client: Http client
Actor: REST server
API: SSE Streaming Server
Actor: Streaming client
API
Old Skool
polling
Streaming
Server-Sent-Events
IoT scenario’s
@natalinobusa | linkedin.com/in/natalinobusa

25.
10 yrs 5 yrs 1 yr 1 month 1 day 1hour 1m
time
population:events,transactions,
sessions,customers,etc
Customer
Journey
Analytics
Recent data
streaming analytics
historical big data
Positioning Streaming and Real-Time
@natalinobusa | linkedin.com/in/natalinobusa
Stream
ing
and
R
eat-Tim
e

26.
Some words about the architecture:
@natalinobusa | linkedin.com/in/natalinobusa
Why stop at http?
Enable Kafka, and datastores connections too ...

27.
The Coral model
is a hybrid streaming/batch architecture:
● in process computing (akka)
● in memory state persistence (cassandra)
● in memory analytics (spark)
Some words about the architecture:
@natalinobusa | linkedin.com/in/natalinobusa

28.
The Product: Coral
● a web api to define/manage/run streaming data-flows
● configuration over programming
● open source and community managed
● it's event processing as a service!
@natalinobusa | linkedin.com/in/natalinobusa

29.
Star us on github!
@natalinobusa | linkedin.com/in/natalinobusa
https://github.com/coral-streaming

30.
Distributed computing Machine Learning
Statistics Big/Fast Data Streaming Computing
@natalinobusa | linkedin.com/in/natalinobusa