• Home

  • Schedule

  • Speakers

  • Registration

  • Call For Proposals

  • Our Sponsors

  • Financial Aid

  • FAQ

  • Blog

  • Contact Us

  •  

    Sponsors
    Screen Shot 2016-07-15 at 8.37.57 PM
    Screen Shot 2016-07-15 at 8.37.57 PM
    Bloomberg
    Bloomberg
    HERE_Logo_RGB (1)
    HERE_Logo_RGB (1)
    new-twitter-logo-150x150_edited
    new-twitter-logo-150x150_edited
    Yelp
    Yelp
    sentry
    sentry
    Google
    Google
    Google
    Twist Bioscience
    Twist Bioscience
    Screen Shot 2016-08-05 at 3.09.22 PM_edited
    Screen Shot 2016-08-05 at 3.09.22 PM_edited
    cloudera_logo
    cloudera_logo
    sauce-labs200x200
    sauce-labs200x200
    hired-logo
    hired-logo
    PSF
    PSF
    shippo
    shippo
    twilio
    twilio
    Minted
    Minted
    Paypal-logo-20141
    Paypal-logo-20141
    anaconda-logo
    anaconda-logo
    microsoft-logo
    microsoft-logo
    eventbrite
    eventbrite
    Show More
    PyBay Connect
    • Meetup_square
    • White Twitter Icon

    Subscribe to PyBay Updates

    TOP

    Trisha Kothari

    Bio

    Trisha works as a Software Engineer at Affirm, a take on modern banking started by Max Levchin. At Affirm, Trisha has worked on several projects including the creation of the underlying financial system, architecture of systems for underwriting data processing, and several other product features. She graduated from the University of Pennsylvania studying Computer Science.

    Aug 21 2:30p - 3:20p, Fisher East
    Data in a dynamic system: Strategies for backwards compatibility

    Dealing with Data, Intermediate

    ​

    Description 

    There are several unanswered questions in deploying huge schema or logic changes: How do you modify systems with zero downtime or service interruption? How do you optimize online data migrations to allow for fallbacks? Any changes in schema or code in dynamic systems may cause existing users to experience downtime. The talk focuses on strategies to ensure backwards compatibility and prevent breaking data integrity.

    ​

    Abstract

    In an ideal scenario, feature development is easy. Just replace the old code with new code, and you’re done. This is, in fact, true for a system in state of inertia. However, in a dynamic system, with constantly moving pieces of business logic, this presents a hard problem. There are several unanswered questions while deploying huge schema or logic changes: How do you make code and schema changes with zero downtime or service interruption? How do you optimize online migrations of data to allow for fallbacks? Any changes in schema or code in dynamic systems may cause existing users to experience downtime. The talk focuses on strategies to ensure backwards compatibility and prevent breaking data integrity.

    ​

    • Meetup_square
    • Black Facebook Icon
    • Black Twitter Icon