Jannis GrönbergArchitecture, Data Engineering, DevOps
You struggle choosing the right #orchestration tool in #Python ? Join this #PyCon talk about when it's best to use #Kubeflow, #Airflow or #Prefect and learn how to automate your #data #pipelines and #ML workflows. #DataScience #dataengineering #DevOps #MLOps
David MelamedCloud, Coding / Code-Review, DevOps, Security
No need to reinvent the CI/CD wheel for every service - learn how to build centralized git workflows for all your repos in Python.
Efe ÖgeAPIs, Architecture, Backend, Cloud, DevOps, Django
Managing files won't be easier but more obvious after this talk.
Jan-Benedikt Jagusch, Christian BourjauData Engineering, DevOps, Packaging
In this session, you will learn how to use ONNX for your machine learning model deployments, which can reduce your single-row inference time by up to 99% while also drastically simplifying your model management.
Philipp StephanBest Practice, Development Methods, DevOps, Packaging
After a review of the current state of Python dependency management, we’d like to present a versatile method of using git submodules to handle internal dependencies in a dockerized microservice architecture, where common libraries have to be iterated quickly.
Jordi SmitAPIs, DevOps, Use Case
Most developers work with Slack every day, yet very few of them know about the awesome things you can do when you build your own slack bot. During this talk, we will teach you to build and deploy your first slack bot.
Tobias HeintzData Engineering, Development Methods, DevOps
How alcemy uses DevOps techniques to streamline and accelerate our daily development. Let's look at a number of real-world examples and best practices taken straight from the pipelines we use to release code several times a day.
Jessica Greene (she/her), Vanessa AguilarData Visualization, DevOps, Performance
We know what your app did last summer. Do you? Join us for this practical & theoretical session if you’re looking to grasp the key concepts of observability, useful metrics, and ensuring operational excellence for your Python applications using Prometheus!
Lina WeichbrodtBest Practice, Backend, DevOps
How to implement #MachineLearning #monitoring for the impatient. Lessons I learned from running more than 30 models in production. And good news, you can use your existing monitoring and dashboard stack like #Prometheus and #Grafana