Generative AI is reshaping cloud operations - drafting Terraform, proposing remediations, and summarizing incidents. But speed alone is not success. Without trusted context and governance, agentic automation becomes unsafe fast.
This paper introduces Agentic Lifecycle Management: an operating model that combines Infrastructure Lifecycle Management (ILM) and Security Lifecycle Management (SLM) to make autonomy auditable, repeatable, and safe.
What You’ll Learn:
- Why AI succeeds in Day 0–1 but fails in Day 2+
- How a context layer and infrastructure graph enable safe autonomy
- A reference architecture for governed agentic workflows
- Practical use cases: vulnerability response, secret rotation, cost optimization
- A clear maturity path from copilots to autonomous operations
Click on the link to download your copy of Agentic Lifecycle Management.
