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KIP-633: The New Way of Configuring Grace Periods for
Windowed Operations in Kafka Streams
Israel Ekpo
Kafka Summit Americas
September 2021
About the Speaker
• Dad, Husband, Son, Brother, Friend
• Cloud Solutions Architect with Microsoft GPS
• Apache Kafka Contributor
• Open Source Proponent – Storage, Processing, Analysis
• Passionate about Event-Driven Architectures
• IzzyAcademy.com
• @IzzyAcademy – Twitter, YouTube, Github
Outline
• Motivation for KIP-633
• The Team
• The Changes
• Follow Up Resources, Next Steps
Motivation for KIP-633
• Stream-to-Stream Joins
• Stream Aggregations
• Grace period controls how long to wait
for windowed operations & process
events that arrive after a window ends
• Records coming in after the grace
period has elapsed will be dropped
from those windows.
• Results for window are
processed/finalized after grace period
• Default grace period is 24-hours
Motivation for KIP-633
• Problems and confusion for users
• Results are getting suppressed
• Results won’t show up for 24 hours
• KIP-633: Drop 24-hour default of
grace period in Streams
Motivation for KIP-633
• Set Expectations for New Users
• Eliminate Confusion for New Users
• Clarity in Usage
• Better Control in Streams Apps
• Improved User Experience
Team of Contributors
• Sophie Blee-Goldman
• Israel Ekpo
• Matthias J. Sax
• Bruno Cadonna
• Guozhang Wang
• Luke Chen
API Changes in 3.0
API Changes in 3.0
Compatibility, Deprecation, and Migration Plan
• Migrate to one of the two new APIs
• Make a conscious decision to skip the
grace period and close a window
immediately
• Still apply the old default of 24 hours
• Choose a new grace period entirely
Follow Up Resources – Check it Out!
https://github.com/izzyacademy/kip-633-demo-grace-periods
https://izzyacademy.com/tutorials
@IzzyAcademy – YouTube, GitHub, Twitter

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The New Way of Configuring Grace Periods for Windowed Operations in Kafka Streams | Israel Ekpo, Microsoft Corperation

  • 1. KIP-633: The New Way of Configuring Grace Periods for Windowed Operations in Kafka Streams Israel Ekpo Kafka Summit Americas September 2021
  • 2. About the Speaker • Dad, Husband, Son, Brother, Friend • Cloud Solutions Architect with Microsoft GPS • Apache Kafka Contributor • Open Source Proponent – Storage, Processing, Analysis • Passionate about Event-Driven Architectures • IzzyAcademy.com • @IzzyAcademy – Twitter, YouTube, Github
  • 3. Outline • Motivation for KIP-633 • The Team • The Changes • Follow Up Resources, Next Steps
  • 4. Motivation for KIP-633 • Stream-to-Stream Joins • Stream Aggregations • Grace period controls how long to wait for windowed operations & process events that arrive after a window ends • Records coming in after the grace period has elapsed will be dropped from those windows. • Results for window are processed/finalized after grace period • Default grace period is 24-hours
  • 5. Motivation for KIP-633 • Problems and confusion for users • Results are getting suppressed • Results won’t show up for 24 hours • KIP-633: Drop 24-hour default of grace period in Streams
  • 6. Motivation for KIP-633 • Set Expectations for New Users • Eliminate Confusion for New Users • Clarity in Usage • Better Control in Streams Apps • Improved User Experience
  • 7. Team of Contributors • Sophie Blee-Goldman • Israel Ekpo • Matthias J. Sax • Bruno Cadonna • Guozhang Wang • Luke Chen
  • 10. Compatibility, Deprecation, and Migration Plan • Migrate to one of the two new APIs • Make a conscious decision to skip the grace period and close a window immediately • Still apply the old default of 24 hours • Choose a new grace period entirely
  • 11. Follow Up Resources – Check it Out! https://github.com/izzyacademy/kip-633-demo-grace-periods https://izzyacademy.com/tutorials @IzzyAcademy – YouTube, GitHub, Twitter