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L’analyse en temps réel
de Big Data
 Le monitoring de flux
par l’exemple
#DevoxxMA #BigData @a_bouchama
Abdellatif BOUCHAMA
Abdellatif BOUCHAMA
@a_bouchama
• Middleware architect, and
passionate about the new
technology: Big Data,IoT and
contributor in the Open source
• Co-founder of BusHorn.com
@a_bouchama#DevoxxMA #BigData
Agenda
Big Data in 2015:Trends & Statistics
The emergence of real time
Use Case: Flow Activity Monitoring
Demo
@a_bouchama#DevoxxMA #BigData
What is Big Data?
Big Data
Velocity
30KB/s --> 30GB/s
· Batch
· Real-Time
· Streaming
Volume
1-2 Terabytes  ∞
Variety
· Structured
· Semi-Structured
· UnStructured
Big Data Expectations:
Things That Excite Executives About Big Data
It’s the “next oil.” from the Ginni Rometty, CEO of IBM
The potential to revolutionize industries, and change business models (e.g.,
Uber and Airbnb), with what we learn from the data.
The ability to provide real-time graphing solutions for data relationships.
Real-time operational and business data allows people to make decisions
faster thereby saving significant money.
The opportunities it gives us to help clients solve real business problems.
https://dzone.com/articles/14-things-that-excite-executives-about-big-data?oid=big_data
Big Data view by Gartner:
@a_bouchama#DevoxxMA #BigData
Big Data in 2015:
75% of Companies Are Investing or Planning to Invest in Big Data in the NextTwoYears
Goals for Big Data initiatives:
1. Enhancing the customer experience
2.Streamlining existing processes
3.Achieving more targeted marketing and reducing costs
Last year, 37% of big data projects were initiated by the CIO, while 25% were initiated by business unit
heads. In 2015, the roles are nearly tied, at 32% and 31 %, respectively.
http://www.gartner.com/newsroom/id/3130817@a_bouchama#DevoxxMA #BigData
The emergence of Real-Time
Low
Pure Batch
Operationalizing
Near RealTime
Or
Interactive
Analytics
High
RealTime
Analytics
• Right timeReal time
• Smart dataBig Data
« It is the right time for Real Time to use Big Data as a Smart Data »
Use case: Flow Activity
Monitoring
@a_bouchama#DevoxxMA #BigData
ESB
ESB
ESB
Objectives
Monitor all data flows which goes through the
different layers (transport, mediation, ..etc).
Analyze and centralize data
Perform the correlation between the functional
and technical data
Provide a centralized view in real time.
Deals
Integrate all data flows, analyze them and
correlate them quickly.
Manage a very high data rate, near millions of
events
Manage a number of messages per second
@a_bouchama#DevoxxMA #BigData
Constraints & Requirements
Constraints
• Non intrusive system
• No modification on business flows.
• We can plug it and unplug it easily.
Requirements
• System cost should be mastered and
adaptable
• System automatized
• Measurement
@a_bouchama#DevoxxMA #BigData
Architecture
CH
ESB
US
ESB
FR
ESB
ElasticSearch
Why Elasticsearch stack?
Open source
Easy to deploy
Distributed
Linear scalability
REST Interface
Kibana & Logstash to complete the Landscape
@a_bouchama#DevoxxMA #BigData
Data flow and constraints
Collect
JMX
Store & transport
Transform & Access
Modelize & Analyze
Visualize & Predict
JMS
DemoTime!
Be prepared for it to fail, because demos always do
@a_bouchama#DevoxxMA #BigData
What’s Next ?
• Enrichment analysis, after adding business
information in the logs
• Integration of backend and frontend
applications
• Audit
@a_bouchama#DevoxxMA #BigData
THANKS FOR LISTENING
Any Questions?
#DevoxxMA #BigData @a_bouchama

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Analyse en temps réel de BigData par l'exemple

  • 1. L’analyse en temps réel de Big Data  Le monitoring de flux par l’exemple #DevoxxMA #BigData @a_bouchama Abdellatif BOUCHAMA
  • 2. Abdellatif BOUCHAMA @a_bouchama • Middleware architect, and passionate about the new technology: Big Data,IoT and contributor in the Open source • Co-founder of BusHorn.com @a_bouchama#DevoxxMA #BigData
  • 3. Agenda Big Data in 2015:Trends & Statistics The emergence of real time Use Case: Flow Activity Monitoring Demo @a_bouchama#DevoxxMA #BigData
  • 4. What is Big Data? Big Data Velocity 30KB/s --> 30GB/s · Batch · Real-Time · Streaming Volume 1-2 Terabytes  ∞ Variety · Structured · Semi-Structured · UnStructured
  • 5. Big Data Expectations: Things That Excite Executives About Big Data It’s the “next oil.” from the Ginni Rometty, CEO of IBM The potential to revolutionize industries, and change business models (e.g., Uber and Airbnb), with what we learn from the data. The ability to provide real-time graphing solutions for data relationships. Real-time operational and business data allows people to make decisions faster thereby saving significant money. The opportunities it gives us to help clients solve real business problems. https://dzone.com/articles/14-things-that-excite-executives-about-big-data?oid=big_data
  • 6. Big Data view by Gartner: @a_bouchama#DevoxxMA #BigData
  • 7. Big Data in 2015: 75% of Companies Are Investing or Planning to Invest in Big Data in the NextTwoYears Goals for Big Data initiatives: 1. Enhancing the customer experience 2.Streamlining existing processes 3.Achieving more targeted marketing and reducing costs Last year, 37% of big data projects were initiated by the CIO, while 25% were initiated by business unit heads. In 2015, the roles are nearly tied, at 32% and 31 %, respectively. http://www.gartner.com/newsroom/id/3130817@a_bouchama#DevoxxMA #BigData
  • 8. The emergence of Real-Time Low Pure Batch Operationalizing Near RealTime Or Interactive Analytics High RealTime Analytics • Right timeReal time • Smart dataBig Data « It is the right time for Real Time to use Big Data as a Smart Data »
  • 9. Use case: Flow Activity Monitoring @a_bouchama#DevoxxMA #BigData
  • 11. Objectives Monitor all data flows which goes through the different layers (transport, mediation, ..etc). Analyze and centralize data Perform the correlation between the functional and technical data Provide a centralized view in real time. Deals Integrate all data flows, analyze them and correlate them quickly. Manage a very high data rate, near millions of events Manage a number of messages per second @a_bouchama#DevoxxMA #BigData
  • 12. Constraints & Requirements Constraints • Non intrusive system • No modification on business flows. • We can plug it and unplug it easily. Requirements • System cost should be mastered and adaptable • System automatized • Measurement @a_bouchama#DevoxxMA #BigData
  • 14. Why Elasticsearch stack? Open source Easy to deploy Distributed Linear scalability REST Interface Kibana & Logstash to complete the Landscape @a_bouchama#DevoxxMA #BigData
  • 15. Data flow and constraints Collect JMX Store & transport Transform & Access Modelize & Analyze Visualize & Predict JMS
  • 16. DemoTime! Be prepared for it to fail, because demos always do @a_bouchama#DevoxxMA #BigData
  • 17. What’s Next ? • Enrichment analysis, after adding business information in the logs • Integration of backend and frontend applications • Audit @a_bouchama#DevoxxMA #BigData
  • 18. THANKS FOR LISTENING Any Questions? #DevoxxMA #BigData @a_bouchama