| DevOps | Integrates development and IT operations to enhance efficiency, reliability, and security. |
| MLOps | Streamlines testing and deployment of machine learning models for data scientists and engineers. |
| DataOps | Optimizes data pipelines to connect diverse data sources and enable scalable workflows. |
| AIOps | Applies AI within IT operations to improve processes and outcomes. |
| ModelOps | Manages and governs models in production for IT or business operations teams. |
| NoOps | Automates IT infrastructure to eliminate the need for manual intervention. |
| DevSecOps | Integrates security checks and testing into the DevOps workflow from the start. |
| GitOps | Uses Git to automate the continuous delivery pipeline, serving as the single source of truth. |
| ITOps | Prioritizes stability and long-term reliability over speed and agility. (Opposite: CloudOps) |
| CloudOps | Emphasizes distribution, statelessness, and scalability. (Opposite: ITOps) |
| CIOps | Manages continuous integration systems to run builds, tests, and deployments, requiring infrastructure configuration by CI operators or administrators. |