I like CAST AI for its managed scaling capabilities and rebalancing features, which are beneficial for cost optimization. The initial setup was very easy.

I like using CAST AI for Kubernetes nodes management. I find the auto scaling and workload autoscaler features particularly useful. It automatically handles my Kubernetes nodes rebalancing and helps reduce our costs. I like the workload autoscaler the most because it reduces manual interactions, detects pod usage, and sizes nodes accordingly, saving costs for each service. It's great that it offers a single command setup which makes onboarding our cluster quite easy.

What stood out to me most was the automation. Once it was set up, CastAI continuously analyzed our workloads and adjusted resources in real time. We saw noticeable reductions in wasted compute, especially around underutilized nodes. The platform’s ability to automatically leverage Spot instances without compromising stability was a big win for us. It handled the complexity in the background, which gave our team more time to focus on product work instead of infrastructure tuning. The visibility into costs has also been valuable. Being able to break down spending by cluster and workload helped us understand exactly where our cloud budget was going. That transparency made it much easier to have productive conversations internally about optimization and accountability.