Check out more about this presentation here: https://www.youtube.com/watch?v=nSsssYHiylQ&t=17s Presentation from the performance given by our team during the NSML Summit. Authors: Krzysztof Zarzycki, Marek Wiewiórka Linkedin: https://www.linkedin.com/in/kzarzycki/ https://www.linkedin.com/in/marekwiewiorka/ ___ Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets. Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries. https://getindata.com​

1. MLOps implemented - how we
combine the cloud & open-source
to boost data scientists work

2. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Marek Wiewiórka
Chief Data Architect
marek.wiewiorka@getindata.com
Krzysztof Zarzycki
Chief Technology Officer
krzysztof.zarzycki@getindata.com

3. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Founded by ex-Spotify
engineers in 2014
Focus only on Big Data and
Cloud (from day 1)
Community builders
(Big Data Tech Warsaw, blogs,
OSS)
80+ Big Data engineers
(and growing)
GetInData in a Nutshell

4. © Copyright. All rights reserved. Not to be reproduced without prior written consent.

5. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
How We Got to MLOps
2015
Google publishes
“Hidden Technical Debt in
Machine Learning Systems“
2018
Started building a
cloud-native ML platform at
ING Bank
2019
started building a ML
Platform for a large Polish
telecom
2020
Built ML Platform for
Kcell, the largest Kazakh
Telecom
2020
MLOps projects started
with retail (cloud),
mobile app
2021
MLOps project started
for the largest Polish
bank (cloud)
and more...

6. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
● Software Engineering-like process but for ML models
● The pipeline is the result, not the model
● No IT required, for Data Science to production
● Freedom of choice of tools
● Loosely coupled mix of cloud services and open-source
● Best of breed instead of all-in-one approach
Our MLOps Principles

8. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Data Science Workbench - Our Vision

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Data Scientists IDE - Batteries Included
●

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Data Scientists IDE - Batteries Included
●

11. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Kedro - Data Scientist’s Swiss Knife
● Kedro is an open-source Python framework for
creating reproducible, maintainable and
modular data science code
● Kedro’s main concepts:
○ Project template
○ Configuration and environments
○ Data catalog
○ Nodes and pipelines

12. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
● common directory structure for all
projects
● customizable Cookiecutter
templates
● boilerplate code for a ML project
using Kedro framework
● official and in-house baked
kedro new --starter=pyspark
Kedro - Project starters

13. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Kedro - Data Catalog
Data source definition:
● Separation of
transformations code
and data connectors
● Can be reused
between projects

14. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
● Node - a Python function
that has zero to many inputs
and/or output datasets
● Pipeline - a DAG. A
collection of nodes with
defined relationships and
dependencies.
kedro run
Kedro viz
Kedro Nodes and Pipelines

15. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
1. Log into JupyterLab
2. Create a project with a Kedro starter
3. EDA with notebooks & pipeline
implementation using VS Code
4. Run your project and automatically track
experiment with a local MLflow
5. Optionally schedule it with a local Airflow
6. Repeat until you’re happy with your model !
Local development with Kedro and MLflow

16. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
● Pipeline containerization with
kedro-docker
● DAGs generation and scheduling
with one of our plugins:
○ kedro-airflow-k8s
○ kedro-kubeflow
● Dataset stability with
kedro-popmon (together with ING)
● Kubernetes pods profiling(R&D)
● CI/CD for maximum automation
Delivering ML Model to Production

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● Freedom of toolkit choice
with containerized execution
● Scalable training
● Experiments and models
tracking
● “Continuous Training”
Schedule- or event-driven
Model Training

18. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
● CI/CD
● Models from registry
● Batch & online
● Scalability
● Extensive monitoring
Model Serving

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Model Deployment to Production!
writes
produces

20. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
Kedro-kubeflow
kedro-airflow-k8s
Model deployer
Jupyter plugins
Prebaked images
Google
AI Platform
Experimentation Training Serving

21. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
MLOps R&D
● Align Data and ML engineering
● Feature Store
○ Feast, GCP, AWS
● Kedro
○ Company-wide data discovery tools
○ Hyperparameters tuning
○ Serving, model deployment
● Advanced deployments
● Retraining, data drift
● Business monitoring, outcome attribution

22. © Copyright. All rights reserved. Not to be reproduced without prior written consent.
● Focus on unlocking data scientists
○ Start with Data Science Workbench
○ Make code reproducible by CI
○ Then build Scalable Training
How to Start with MLOps?

23. Thank you! - Dziękujemy!
github.com/getindata/kedro-kubeflow
github.com/getindata/kedro-airflow-k8s