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Kappa Architecture:
IoT of the cars
Juantomás García
Who am I
• Data Solutions Manager at Open Sistemas
• Co-author of the first spanish book about free
software “La pastilla roja”
• Former president of Hispalinux (Spanish Linux User
Group).
• Co-organizer of Machine Learning Spain Meetup
What’s Kappa Architecture
July 2, 2014 Jay Kreps coined the term
Kappa Architecture in an article for
O’reilly Radar
Who is Jay Kreps
Jay has been involved in lots of projects:
Author of the essay:
The Log: What every software engineer
should know about real-time data's
unifying abstraction (12/16/2013)
https://engineering.linkedin.com/distributed-systems/log-what-every-software-
engineer-should-know-about-real-time-datas-unifying
Who is Jay Kreps
Author of the book: I ♥ Logs
Who is Jay Kreps
Involved with projects as:
Apache Kafka
Apache Samza
Voldemort
Azkaban
Ex-Linkedin
Now co-founder and CEO of Confluent
Usual data flow
Kappa Architecture Way
Tools we use to implement
Kappa Architecture
Tools we use to implement
Kappa Architecture
Tools we use to implement
Kappa Architecture
• Our favorite kafka features.
• Easy to use
• Robust & Resilient
• Kafka connectors
• Kafka streams
• Compact logs
• Very fast writes and reads
Tools we use to implement
Kappa Architecture
Some favorite Spark features
• If you have an schema spark SQL is
perfect.
• Spark streaming work very fine with spark
and almost all streaming sources.
• Structured queries will be a huge advance.
• We love scala and scala is the spirit of
spark.
Some favorite Spark features
• We love code like this:
A real case
• One of our clients want to monitor all the
cars informations via OBD II
• OBD II is a car interface with the car
electronics.
• Client develop an app to read all the car
information throw a ODB II with bluetooth
A real case
First Problems
• We need to scale the rest interfaces too
many requests.
• MySQL don’t scale
• Client wants to make realtime expensive
queries.
Some Numbers
Architecture V2
Architecture KappaV3
Now we’re more flexible
• We can have queries like:
• What are the drivers that are not client
of the X gas brand, has a few gas and
are near of gas station of the brand X
and if true, send a notification with a
discount coupon and a link with the
route.
Takeaways
• Kappa architecture is not a silver bullet but
helps in a lot of solutions.
• Kafka + spark streaming is our favorite
tools
• There a lots of improvements:
• OLAP like Apache Druid
• Graph databases like neo4j
• Kafka streams and compacts logs
¿Questions?
• My contact info:
• Juantomás García
• juantomas@opensistemas.com
• @juantomas

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Kappa Architecture, IoT of the cars - LibreCon 2016

  • 1. Kappa Architecture: IoT of the cars Juantomás García
  • 2. Who am I • Data Solutions Manager at Open Sistemas • Co-author of the first spanish book about free software “La pastilla roja” • Former president of Hispalinux (Spanish Linux User Group). • Co-organizer of Machine Learning Spain Meetup
  • 3. What’s Kappa Architecture July 2, 2014 Jay Kreps coined the term Kappa Architecture in an article for O’reilly Radar
  • 4. Who is Jay Kreps Jay has been involved in lots of projects: Author of the essay: The Log: What every software engineer should know about real-time data's unifying abstraction (12/16/2013) https://engineering.linkedin.com/distributed-systems/log-what-every-software- engineer-should-know-about-real-time-datas-unifying
  • 5. Who is Jay Kreps Author of the book: I ♥ Logs
  • 6. Who is Jay Kreps Involved with projects as: Apache Kafka Apache Samza Voldemort Azkaban Ex-Linkedin Now co-founder and CEO of Confluent
  • 9. Tools we use to implement Kappa Architecture
  • 10. Tools we use to implement Kappa Architecture
  • 11. Tools we use to implement Kappa Architecture • Our favorite kafka features. • Easy to use • Robust & Resilient • Kafka connectors • Kafka streams • Compact logs • Very fast writes and reads
  • 12. Tools we use to implement Kappa Architecture
  • 13. Some favorite Spark features • If you have an schema spark SQL is perfect. • Spark streaming work very fine with spark and almost all streaming sources. • Structured queries will be a huge advance. • We love scala and scala is the spirit of spark.
  • 14. Some favorite Spark features • We love code like this:
  • 15. A real case • One of our clients want to monitor all the cars informations via OBD II • OBD II is a car interface with the car electronics. • Client develop an app to read all the car information throw a ODB II with bluetooth
  • 17. First Problems • We need to scale the rest interfaces too many requests. • MySQL don’t scale • Client wants to make realtime expensive queries.
  • 21. Now we’re more flexible • We can have queries like: • What are the drivers that are not client of the X gas brand, has a few gas and are near of gas station of the brand X and if true, send a notification with a discount coupon and a link with the route.
  • 22. Takeaways • Kappa architecture is not a silver bullet but helps in a lot of solutions. • Kafka + spark streaming is our favorite tools • There a lots of improvements: • OLAP like Apache Druid • Graph databases like neo4j • Kafka streams and compacts logs
  • 23. ¿Questions? • My contact info: • Juantomás García • juantomas@opensistemas.com • @juantomas