Big Data Hardware/IoT Internet of Things (IoT) Machine-Learning Python general
Infarm is a FaaS, Farming as a Service, and whether you believe it or not, our business is in-house farming at scale.
We design and build our farms, grow vegetables and sell them, and the backbone of our infrastructure is based on Python.
You can check this video to see what we do -> https://twitter.com/christianbarra/status/1096399602159439874
More than 10 million observations are recorded from our farms, feeding our farm management system that allows operators, plant scientists, and supervisors to monitor each farm in real-time.
During this talk I will briefly introduce the world's problems we are trying to resolve at Infarm and then talk about our IoT farms, infrastructure, how we use Python and how we plan to improve the capabilities of our farms by adding edge machine learning.
- What are the problems we are trying to solve at Infarm
- Our 4 tech pillars
- How we started with Python
- Issues we are facing while scaling our Python infrastructure to support > 400 farms
- How we plan to evolve our software and infrastructure on 4 different levels: consolidate, architecture, cloud native and observability
- How Python is going to support our automated farms and its role in making the farms smarter (edge computing with AI)
Type: Talk (45 mins); Python level: Intermediate; Domain level: Intermediate
I am Senior Software Engineer, Tech Lead and speaker living in Berlin where I work at infarm, one of the top 10 startups in Berlin.
My focus is on microservices, event-driven architecture, devops for microservices and machine learning and data engineering.
I am an active member of the tech community in Berlin, organizer of PyCon DE and a Python Software Foundation Fellow.