Ignite AIoT: DevOps and Infrastructure
Agile DevOps for Cloud and Enterprise Applications
Agile DevOps for AI
Many new concepts create challenges for AI DevOps
- New roles: data scientist, AI engineer
- New artefacts (in addition to code): Data, Models
- New methods / processes: AI/data-centric, e.g. „Agile CRISP-DM“, Cognitive Project Management for AI (CPMAI)
- New AI tools + infrastructure
Additional AI DevOps challenges
- Reproduceability of models
- Model validation
- Versioning: Models, code, data
- Lineage: Track evolution of models over time
- Testing and test automation: AI requires new methods and infrastructure
- Security: Deliberately skewed models as new attack vector / adversarial attacks
- Monitoring and re-training: Model decay requires constant monitoring and re-training
Agile DevOps for IoT
