DevOps Session List
Battle of Pipelines - who will win python orchestration in 2022?
Jannis Grönberg
Architecture, Data Engineering, DevOpsYou 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
Forget Mono vs. Multi-Repo - Building Centralized Git Workflows with Python
David Melamed
Cloud, Coding / Code-Review, DevOps, SecurityNo need to reinvent the CI/CD wheel for every service - learn how to build centralized git workflows for all your repos in Python.
It is all about files and HTTP
Efe Öge
APIs, Architecture, Backend, Cloud, DevOps, DjangoManaging files won't be easier but more obvious after this talk.
Making Machine Learning Applications Fast and Simple with ONNX
Jan-Benedikt Jagusch, Christian Bourjau
Data Engineering, DevOps, PackagingIn 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.
Quitting pip: How we use git submodules to manage internal dependencies that require fast iteration
Philipp Stephan
Best Practice, Development Methods, DevOps, PackagingAfter 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.
Slack bots 101: An introduction into slack bot-based workflow automation
Jordi Smit
APIs, DevOps, Use CaseMost 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.
The state of DevOps for Python projects
Tobias Heintz
Data Engineering, Development Methods, DevOpsHow 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.
We know what your app did last summer. Do you? Observing Python applications using Prometheus.
Jessica Greene (she/her), Vanessa Aguilar
Data Visualization, DevOps, PerformanceWe 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!
What I learned from monitoring more than 30 Machine Learning Use Cases
Lina Weichbrodt
Best Practice, Backend, DevOpsHow 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
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