Context: Today is relatively easy to create and train a conversational agent using Machine Learning Techniques, fire it up and showcase it in your computer Problem: Sharing your chatbot with the outside world is not as easy as training your models. Load Balancer, Unit Test, Integration Tests, Differential Tests ... Text Analytics and retrain the models to better serve your audience goes way beyond the simple agent that runs in the developer environment Solution: I want to show how from my experience of deploying bots to production, leveraging DevOps + DataScience skills along with an entry level knowledge of Databases, CI/CD and distributed systems you can take your prototypes to a next level, deploy, iterate and re-train your models faster. Pre-reqs: Entry level understanding of CI/CD Pipelines, NLP, jupyterhub, Version Control, Rasa