ChatOps: Why you should be talking to your applications

Development Practices
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What if your application could send a message to the right developer if there was something that needed attention? What if your app could join relevant instant messaging channels during a production incident, responding to questions and grabbing the logs you need to be looking at? What if you could tell your app what you wanted it to do?

This is ChatOps: a collaboration model that connects people, tools, processes, and automation into a real-time workflow. DevOps experts use instant messaging collaboration tools like Slack to communicate - not only with each other, but also with the tools they use to do their jobs. It's an idea that started at GitHub, where they created a bot called Hubot to improve their DevOps experience.

We want to get you thinking whether adopting elements of ChatOps could improve your DevOps workflow and give you practical tips to get started.

To help give you some ideas for what you can do with your own application, we'll show you a demo using a common open-source micro-services app running in Kubernetes. We'll show how we get it to post messages to our team Slack channel when there is something that a dev-ops person should be be looking at. And we'll give an example of how to perform simple admin tasks from Slack.

The principles behind what we'll demonstrate are applicable to your own applications - our goal is to get you thinking how you could introduce this into your own application workflow!

Lori French


Software Engineer, Designer & Inventor working in the IBM Client Engineering Team, based in London. I have a passion for delivering innovative prototypes for Enterprises, being a member of the Wimbledon Technical Team.

Dale Lane


Dale is a developer for IBM. He spent several years as a developer in IBM Watson, helping to create several Watson cloud services. He is the author of "Machine Learning for Kids", and the creator of the supporting website which is used by children around the world to learn about artificial intelligence by creating and playing with their own machine learning models.