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Gdg cloud london 2017 kappa architecture 2.0 copia

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This document summarizes a presentation by Juantomás García on Kappa Architecture 2.0. It introduces Kappa Architecture, which was coined in 2014 as a way to handle both batch and real-time processing of streaming data. The presentation describes the traditional data flow, and how Kappa Architecture uses tools like Apache Kafka, Apache Spark, and Apache Samza to allow for real-time and batch processing of data. It also provides examples of how Kappa Architecture has been applied to use cases involving monitoring vehicle data in real-time and scaling APIs to handle many requests.

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Juantomás García - Open Sistemas Kappa Architecture 2.0 GDG cloud London

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Good Evening London first

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Juantomás García • Data Solutions Manager @ OpenSistemas • GDE (Google Developer Expert) for cloud Others • Co-Author of the first Spanish free software book “La Pastilla Roja” • President of Hispalinux (Spanish Linux User Group) • Organizer of the Machine Learning Spain and GDG Cloud Madrid. Who I am

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What’s Kappa Architecture? July 2, 2014 Jay Kreps coined the term Kappa Architecture in an article for O’reilly Radar “Maybe we could call this the Kappa Achitecture, though it may be too simple of an idea to merit a Greek letter”

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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) ✓ Author of the book I love Logs Who is Jay Kreps?

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•Involved with projects as: ✓ Apache Kafka ✓ Apache Samza ✓ Voldemort ✓ Azkaban ✓ Ex-Linkedin ✓ Now co-founder and CEO of Confluent Who is Jay Kreps?

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Usual Data Flow

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Usual Data Flow

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Usual Data Flow

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Kappa Architecture Way

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Tools we use

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Tools we use

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Tools we use

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✓ If you have an schema spark SQL, is perfect. ✓ Spark streaming works very fine with spark and almost each streaming sources. ✓ Structured queries will be a huge advance. ✓ We love Scala, the spirit of Spark. Some Favorite Spark Features

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We love code like this: Some Favorite Spark Features

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• One of our clients wanted to monitor all the car's information via OBD II • OBD II is a car interface with the car electronics. • Our client developed an app for reading all the car information throw ODB II with bluetooth A Real Use Case

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A Real Use Case

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• We needed to scale the rest interfaces. There were too many requests. • MySQL don’t scale • Client wanted to do realtime expensive queries. First Problems

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Some metrics

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Architecture v 2.0

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Architecture v 3.0

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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." Now we’re more flexible!!

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• Kappa architecture is not a silver bullet but helps with a lot of solutions. • Kafka + spark streaming are our favorite tools • There are a lots of improvements: Takeaways ✓ OLAP like Apache Druid ✓ Graph databases like neo4j ✓ Kafka streams and compacts logs ✓ Apache Beams ✓ Scio Scala bindings

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Takeaways: Apache Beam

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Takeaways: Scio Scala Binding

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Think Big

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Think Big • Forget Legacy Architectures • Forget Old Tools • Use Light Technologies / Serverless • Use pieces of Lego • Mix different technologies from diverse sources

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Spark Use Cases Not to do list •Avoid install & config a server even a VM. •Avoid installs tools instead use containers and/or cloud services. •In general: think if there is a simpler way to do it and needs less effort

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Spark Use Cases Architecture & Tools •To use Cloud Services is not a brainer decision. •Git + Containers + Kubernetes •Use the best language* for each module. •Use Notebooks: Jupyter, Zeppelin, DSX (*) Even java might be an option - unprovable

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Google Cloud Version

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Kappa Architecture Questions? •email: juantomas@opensistemas.com •twitter: @juantomas This talk have a free questions lifetime warranty: If you have any questions or concerns about this talk, feel free to contact me anytime. Selfie Time: If you like the talk just smile while I take the selfie ;-)

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Kappa Architecture Thank you

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Gdg cloud london 2017 kappa architecture 2.0 copia

  • 1. Juantomás García - Open Sistemas Kappa Architecture 2.0 GDG cloud London
  • 3. Juantomás García • Data Solutions Manager @ OpenSistemas • GDE (Google Developer Expert) for cloud Others • Co-Author of the first Spanish free software book “La Pastilla Roja” • President of Hispalinux (Spanish Linux User Group) • Organizer of the Machine Learning Spain and GDG Cloud Madrid. Who I am
  • 4. What’s Kappa Architecture? July 2, 2014 Jay Kreps coined the term Kappa Architecture in an article for O’reilly Radar “Maybe we could call this the Kappa Achitecture, though it may be too simple of an idea to merit a Greek letter”
  • 5. 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) ✓ Author of the book I love Logs Who is Jay Kreps?
  • 6. •Involved with projects as: ✓ Apache Kafka ✓ Apache Samza ✓ Voldemort ✓ Azkaban ✓ Ex-Linkedin ✓ Now co-founder and CEO of Confluent Who is Jay Kreps?
  • 14. ✓ If you have an schema spark SQL, is perfect. ✓ Spark streaming works very fine with spark and almost each streaming sources. ✓ Structured queries will be a huge advance. ✓ We love Scala, the spirit of Spark. Some Favorite Spark Features
  • 15. We love code like this: Some Favorite Spark Features
  • 16. • One of our clients wanted to monitor all the car's information via OBD II • OBD II is a car interface with the car electronics. • Our client developed an app for reading all the car information throw ODB II with bluetooth A Real Use Case
  • 17. A Real Use Case
  • 18. • We needed to scale the rest interfaces. There were too many requests. • MySQL don’t scale • Client wanted to do realtime expensive queries. First Problems
  • 22. 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." Now we’re more flexible!!
  • 23. • Kappa architecture is not a silver bullet but helps with a lot of solutions. • Kafka + spark streaming are our favorite tools • There are a lots of improvements: Takeaways ✓ OLAP like Apache Druid ✓ Graph databases like neo4j ✓ Kafka streams and compacts logs ✓ Apache Beams ✓ Scio Scala bindings
  • 27. Think Big • Forget Legacy Architectures • Forget Old Tools • Use Light Technologies / Serverless • Use pieces of Lego • Mix different technologies from diverse sources
  • 28. Spark Use Cases Not to do list •Avoid install & config a server even a VM. •Avoid installs tools instead use containers and/or cloud services. •In general: think if there is a simpler way to do it and needs less effort
  • 29. Spark Use Cases Architecture & Tools •To use Cloud Services is not a brainer decision. •Git + Containers + Kubernetes •Use the best language* for each module. •Use Notebooks: Jupyter, Zeppelin, DSX (*) Even java might be an option - unprovable
  • 31. Kappa Architecture Questions? •email: juantomas@opensistemas.com •twitter: @juantomas This talk have a free questions lifetime warranty: If you have any questions or concerns about this talk, feel free to contact me anytime. Selfie Time: If you like the talk just smile while I take the selfie ;-)