The rise of “XOps'' is emerging as Agile and DevOps practices permeate deeper into the enterprise. DevSecOps, AIOps, MLOps, BizOps, or whatever new roles are being created with data engineering in mind must eventually be part of the deeper fabric of a business. By keeping these roles separate in two different spheres, it muddies the waters of team collaboration. Everyone can and should be able to work in the same tool chain.

The overall evolution and continued convergence of the DevOps space is that the Ops teams rooted in DevOps require specialized skills in order to effectively work together. There are similarities in the way DevOps teams get work done and they should all observe the same basic principles. In the future, new domain responsibilities for Ops will increasingly overlap with DevOps and the same evolution will need to occur.

Today, people with differing domains of expertise may already be working in the same pipelines or reviewing the same pull requests. Data engineers, for example, are already being tasked to deliver information on many of the applications DevOps teams are delivering; it's the fuel that they run on. So treating all those independent roles as a snowflake will eventually need to melt away.

In this talk, I will share how organizations should be able to leverage the power of DevOps and apply that to machine learning, data engineering, etc. to usher in a new team model and approach to cross-functional collaboration. I will also share why, over time, the creation of “fusion teams” is going to force a convergence of MLOps, AIOps and DevOps teams.