Optimized cloud workloads and cut costs while highlighting needs for clearer predictive insightsCAST AI is a useful platform for automating Kubernetes infrastructure and reducing cloud costs. However, I see improvement needed in cost visibility and reporting. There is a dashboard, but it doesn't showcase predictive scaling. A predictive scaling feature could be added where I can see more transparency around automated infrastructure decisions, especially when nodes and workloads are being replaced. There is a predictive cost involved, and that should be readily seen by CAST AI's dashboard so I could make better infrastructure choices and auto-scale in a better way. I would position myself to focus on better cost reporting and smarter predictive scaling as an added feature which could be a selling point for CAST AI. Additionally, there is the team saving concept where there could be visibility for different teams. Regarding understanding CAST AI's use case, I attended AWS re:Invent, where they sent out a demo to use CAST AI and other resources. I downloaded the necessary features and undertook the course to understand most of CAST AI's features. Although there was a demo and educational materials, CAST AI's use case needs to be more user-friendly for new users to understand what CAST AI is, what it is truly useful for, and where it exactly stands. The engagement with new users was limited. I could watch videos and have understanding about Kubernetes and where I could use CAST AI, but what about a person who would not know about Kubernetes or any scaling features? If a new organization wants to know about CAST AI and its use cases, they might face feasibility issues in understanding CAST AI and its applications. If there is a handbook, playbook, or basic guide showing where CAST AI can work well for them, that would help a lot for new users of CAST AI. I have mentioned most of the improvements I identified.
