Cast AI Reviews & Product Details

The reliability of the node scaling continues to be a highlight; we have zero anxiety about node recreation even during high-traffic events. The 'set it and forget it' nature of the infra management is still the strongest selling point. Stability has been rock solid over the last year. Review collected by and hosted on G2.com.

I still find the cost reporting to be the weak point compared to the GKE/GCP console. I need better visibility into specific node template costs and a clearer breakdown of infrastructure prices. Currently, reconciling Cast AI's reported figures with our actual GCP billing lacks the necessary granularity. We need more transparency on the total amounts for specific node groups to fully trust the cost data. Review collected by and hosted on G2.com.

I love how CAST AI is quite intuitive, making the management of my company's Kubernetes easier and straightforward. The simplicity in the initial setup really impressed me, as it was very simple and facilitated a quick start. The cost reduction functionality through spot instances and the ability to quickly and easily hibernate non-productive clusters are features I consider extremely valuable. This not only optimizes my financial resources but also improves operational efficiency. Furthermore, the 10 out of 10 recommendation I would give to CAST AI reflects my complete satisfaction and confidence in the platform. Review collected by and hosted on G2.com.

Some type of self-healing before swapping instances could be improved. I would like there to be a check before shutting down a node to ensure that the applications on the target node are initialized correctly to avoid downtime. Review collected by and hosted on G2.com.

I use CAST AI to automate cluster scaling and reduce manual work in maintaining our Kubernetes infrastructure. I appreciate how it helps reduce cloud costs by taking care of scaling automatically. I like how well CAST AI handles spot instances and cluster autoscaling. It manages spot instances flawlessly, ensuring I don’t have to worry about interruptions. What used to be a manual, tedious process is now sorted automatically. I particularly enjoy that CAST AI can automatically manage spot instances and fall back to on-demand without causing downtime. Additionally, the setup process was straightforward, allowing us to get up and running with minimal effort. Review collected by and hosted on G2.com.

Sometimes, the pricing feels a bit high for small clusters. Review collected by and hosted on G2.com.

CAST AI automatically rightsizes workloads, removes underutilized nodes, and selects the most cost-effective instances in real time—saving up to ~ 60% on cloud bills without sacrificing performance.

Their autoscaler is fast and responsive, scaling workloads vertically and horizontally with minimal delay, and supports real-time bin-packing.

Built-in security scanning and real-time insights about vulnerabilities and misconfigurations across your clusters are helpful for compliance.

With policies, teams can enforce governance (e.g., disallowing GPU usage, or restricting instance types), which is useful in large or shared environments.

Especially for organizations with dynamic or spiky workloads, CAST AI’s automation leads to substantial cost reductions.

• Simplicity and Speed:

The UI is clean, onboarding is relatively quick, and node replacements happen in minutes.

• Great for SRE/Platform Teams:

Offloads the pain of managing autoscaling, provisioning, and node selection. Review collected by and hosted on G2.com.

• Learning Curve on Governance:

Policy setup and interpretation of some recommendations require a bit of learning, especially for teams new to Kubernetes internals.

• Limited Documentation Depth:

Some users may find the documentation lacking for advanced use cases, particularly when integrating with non-standard setups (e.g., GKE workload identity federation, custom networking). Review collected by and hosted on G2.com.

- 30% cloud cost savings over our whole compute

- Increase in my team’s productivity: a task that took seven days now gets done in three or four days

- We also unlocked extra cost savings from Spot Instances thanks to automated instance selection Review collected by and hosted on G2.com.

No complaints, the Cast support is great Review collected by and hosted on G2.com.

CAST AI offers robust Kubernetes cost monitoring, providing clear visibility into resource usage and expenses across clusters. Its actionable cost recommendations are particularly helpful, guiding users on how to optimize or reduce spending with specific, practical steps. Additionally, CAST AI supports org-level cluster monitoring, making it easy for organizations to manage and analyze the cost and performance of multiple clusters in one place. Overall, CAST AI is an effective tool for enterprises looking to gain better control over their Kubernetes costs and efficiency. Review collected by and hosted on G2.com.

While CAST AI offers powerful cost optimization features, there are a few areas that could be improved. The initial setup and integration with existing Kubernetes environments can be complex and may require substantial time and expertise. Some users have reported a learning curve when navigating the UI and understanding the full range of functionalities. Additionally, as a third-party platform, there may be concerns around data security and handing over cluster management. Pricing could also become a consideration for smaller teams or organizations with limited budgets. Review collected by and hosted on G2.com.

CAST AI's ability to automatically optimize Kubernetes workloads for cost and performance is incredibly powerful. I particularly appreciate the autoscaling and rightsizing features that reduce our cloud bill without manual intervention. The interface is intuitive, and integration with AWS and GCP was seamless. The real-time cost visibility and actionable recommendations help us stay on top of resource usage. Review collected by and hosted on G2.com.

There’s a learning curve during the initial setup, especially if you're new to Kubernetes internals. Additionally, I would like to see more documentation around custom policy configurations for companies with unique infrastructure needs. While support is helpful, response time could be a bit faster during critical issues. Review collected by and hosted on G2.com.

CAST AI is an easy tool to onboard the kubernetes clusters.It provides the easy dashbords to understand the CPU and RAM utilization of the Node and workloads.It is easy to implement the things with the help of CAST.Quick action on the issues with the 24X7 customer support. Schedule rebalacing is the great feature provided by CAST with which we can schedule the rebalancing with the flexible timings.We from our organization will be frequently viewing the console.It also provides the slack configurations and alerts on the metrics. Review collected by and hosted on G2.com.

CAST AI should improve on the below features like proving the logs for the workload autoscalers,Audit logs has to be improved for more understanding of the onboardings. Review collected by and hosted on G2.com.

CAST AI helps organizations in managing cloud resources and optimizing the costing part with high availability at low cost . Their consulting team is very dependable and are available anytime almost.

Integration to CAST AI is super easy and we have connect our cluster to CAST AI tool and using node templates and resource allocation the machine type and resources were scheduled to the pods in the Google Kubernetes Engine cluster.Even we can define the region where to spawn our pods.

We used terraform script to connect our clusters to CAST AI tools.The CAST AI team is very helpful in the integration part by providing the documentation to connect our cluster to CAST AI. Review collected by and hosted on G2.com.

Sometimes there are some issues that popup like machine types that might not supported by apps we provisioned by CAST AI tool which really annoys me. Review collected by and hosted on G2.com.

For a platform that uses k8s multi-tenancy , monitoring and optimizing costs easily across many clusters and namespaces is very important. Cast gives us a easy way to achive this. Review collected by and hosted on G2.com.

For un-even workloads across Pod-s in one Deployment or StatefulSet auto-scaling does not always yield the best results, but this is true for all k8s auto-scaling options out there. With cast.ai you can manually tweak the requests/limits Review collected by and hosted on G2.com.