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Challenges at Kiwi.com: Connecting hundreds

Challenges at Kiwi.com: Connecting hundreds

Tin Markovič (Booking Backend team leader at Kiwi.com) @ Brno-Moscow Python Meetup 2

"What is Kiwi.com? Why is engineering so important to a travel agency? How do we solve our problems? Tin will answer these questions and more when he explains the methodology of this budding techno-travel giant. We'll look at the problems of growing at breakneck speed, the advantages of being in a friendly environment and the challenges that make it all exciting".

Video: http://www.moscowpython.ru/meetup/2/kiwi-challenges/

Moscow Python Meetup
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December 05, 2018
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  1. Tin Marković, Senior Software Eng
    Challenges at Kiwi.com
    Connecting hundreds

    View Slide

  2. 2
    Introduction and Overview

    How does Kiwi.com work

    Who are we? Why are we here?

    What are our daily problems

    Our daily challenges

    Assets and the work we do

    View Slide

  3. 3
    Speaker

    Tin

    Team Leader at Kiwi.com

    Software Architecture as passion

    Experiences working big projects (edX, Texas U, Kiwi)

    Where do I fit in the Kiwi picture?

    View Slide

  4. 4
    Company: Kiwi.com

    Making travel better

    Our vision is to make travelling simple and
    accessible to everyone

    View Slide

  5. 5
    Kiwi.com and Python

    We develop using mainly Python

    Startup beginnings (and present)

    Adaptability and quick scaling

    Try. Fail. Learn.

    EAFP

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  6. 6
    The Problems

    Our scale is enormous with worldwide scope

    We need better standards

    Our environment changes often

    Growing pains of a huge company

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  7. 7
    The Problems II

    Python lets us move rapidly, but...

    Issues:

    Type security

    Dictionaries: mutable, dynamic, nested

    There's more than one way to do it

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  8. 8
    The Challenges

    Speed of delivery

    Changes have to come weekly and daily

    Downtime is unacceptable

    Dozens of bookings a minute

    Making travel better

    Customer experience: reliable and verbose

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  9. 9
    The Assets

    Great Tooling

    Continuous Integration & Source Control

    Process, but measured

    Code review, trainings and education budget

    Safety nets

    Blameless, failures are expected

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  10. 10
    The Assets II

    Static:

    PyLint, mypy, Coala, SonarQube

    Logging:

    Sentry, Pagerduty, Datadog, Kibana logs

    More? → Refactoring in Python (PyConf
    Moscow)

    View Slide

  11. 11
    The Work

    What do I do?

    The Bag Man, Mambo

    Precise, when it can be

    A lot of obscurity and vague rules

    Visible impacts

    Conversion rate, consumer satisfaction

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  12. 12
    The Work II

    Booking → Monolith

    Scrape off part by part — services separated

    From: Method/Function oriented approach

    To: Resource/Item oriented approach (OOP!)

    REST-ish → Swagger/OpenAPI + Connexion

    Doing it right, but mindful of business needs

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  13. 13
    The Work III

    Demanding:

    Mapping the processes

    Edge cases and their validity

    History of code

    Issues with service split:

    Edge cases get reimplemented

    Hereditary implementation - undocumented

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  14. 14
    The Work IV

    Splitting services - summation:

    Mapped processes invalidate edge cases

    System can be forced into a stronger model

    Operation based API doesnt scale: focus on resources

    Stricter validation with Python: scheme everything

    Use modules generously: encapsulate everything
    shared and share business logic through all services

    View Slide

  15. ANY QUESTIONS?
    You can find me at [email protected]
    Thanks!

    View Slide