Analytics in Real Time: The [Grey's] Anatomy of Event Streaming - - PowerPoint PPT Presentation

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Analytics in Real Time: The [Grey's] Anatomy of Event Streaming - - PowerPoint PPT Presentation

Analytics in Real Time: The [Grey's] Anatomy of Event Streaming Adam Ahringer | adam.ahringer@abc.com Context - Who is This Guy Up There? Software Dev Manager (Seattle) - ABC Digital Media, Data Platform ABC part of Media Networks


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Analytics in Real Time: The [Grey's] Anatomy of Event Streaming

Adam Ahringer | adam.ahringer@abc.com

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Context - Who is This Guy Up There?

  • Software Dev Manager (Seattle) - ABC Digital Media, Data Platform
  • ABC part of Media Networks Business Segment
  • Distributed team - Burbank/Seattle
  • Technology Architecture
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ABC Digital Media Engineering

Streaming of ABC content on variety of platforms

  • iOS, Android, Fire TV, Apple TV, Android TV, Roku, Web
  • Current and former ABC shows, classics, originals, live stream
  • Some content gated
  • Shameless Plugs
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Topics

  • Challenges
  • Possible Solutions
  • Architecture chosen
  • Outputs/Examples
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Challenges

  • Business wants real time analytics around user behavior during interaction with ABC

streaming apps

  • Operations needs real time analytics regarding performance of app, infra, etc
  • Business needs more timely and more detailed reporting over a variety of dimensions
  • Avoid proliferation of data and having to transform/shuffle/etc data to many systems
  • Omniture data just not sufficient
  • “Every Event is Sacred”
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Demo

Because - Why Not!?

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Solutions Considerations - Producers

  • Latency
  • Bandwidth
  • Local Buffering/Retry
  • Size of Messages
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Solutions Considerations - Streaming System

  • Cloud Agnostic
  • Serverless
  • On-Prem

Dataflow PubSub Kinesis

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Solutions Considerations - Consumers

What’s Your Use Case?

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Architecture So Far...

KPL Kinesis KCL

???

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Solutions Considerations - Data Store

Use Case Really Drives Decision Making!!!

  • Batch Analytics/BI
  • Real Time Analytics and Metrics
  • Compatibility with Common Tools
  • Scale
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DATG Choice

  • “Real Time Data Warehouse”
  • Ability to insert data at extremely high rate
  • Column Store - Excellent compression of data
  • In Memory Store - Primary keys, geospatial indexes
  • Tool compatibility
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Putting It All Together

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Examples

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Enhanced User Experience

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User Segmentations

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Dedupe Process Monitoring

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Recap

  • Understand your use case!!!
  • Keep architecture as simple as possible
  • Leverage your strengths, but don’t hesitate to ask for help
  • Be ready and open to pivots
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Questions?