A list of -Ops in software development.
DevOps (role, category, practice, Devs + IT) – Everything around optimizing the software development lifecycle. From developer experience (configuring environments) to helping developers deploy their code (now, to the cloud). The center of gravity for DevOps engineers is now managing cloud infrastructure (infrastructure-as-code, cloud APIs, internal platforms).
DataOps (category, Data + IT) – Building the platform around data analytics. The main role might be a Data Engineer that manages data infrastructure. The center of gravity for this category is the cloud data warehouse (e.g., Snowflake) and all of the infrastructure that connects to it (ETL, data orchestration, etc.). Slowly converging with DevOps as the underlying infrastructure converges (e.g., on Kubernetes).
GitOps (practice) – A subset of the DevOps methodology where events around the version control system (usually Git) as the single source of truth and trigger for the DevOps workflow. For example, all infrastructure is defined in configs or code and cannot be deployed except by pushing a commit.
ChatOps (practice) – Triggering DevOps workflows from chat (e.g., Slack or Discord).
FinOps (category, Finance + IT) – Mainly focused on cloud and third-party SaaS costs, extracting data to centralize and optimize procurement and manage costs. Companies like Vantage can be categorized as FinOps.
DevSecOps (role, category, practice) – "Shifting security left" so that developers think about security before applications are deployed.
MLOps (role, category) – The infrastructure centered around the production machine learning stack. Everything from how distributed training is done to optimizing and serving inference. Can also include the platform that's needed for exploration and experimentation. The MLOps stack is rapidly changing, so there's no center of gravity. However, if one needed to be named, it would be Databricks.