Here's the most important information, guides, and tutorials to bring you up to speed on using the platform.

What is Cast AI, and what does it help you achieve?

Cast AI is an all-in-one Kubernetes automation, optimization, security, and cost management platform. It abstracts layers of provider-specific technical complexity so that you can easily manage Kubernetes operations on all three major cloud providers (GCP, AWS, Azure) and beyond with Cast AI Anywhere.

The platform includes cost monitoring for real-time and longer-period cost reports at the cluster, namespace, and workload levels. It also offers cost optimization suggestions and automatic optimization using autoscaling, Spot Instance automation, bin packing, and other features.

Cast AI also provides workload autoscaling to right-size your containers automatically based on actual resource usage, eliminating manual guesswork and reducing waste from overprovisioned resources.

Key platform features

Supported providers

• Amazon Elastic Kubernetes Service (EKS)
• Google Kubernetes Engine (GKE)
• Microsoft Azure Kubernetes Service (AKS)
• Oracle Cloud (OCI)
• Microsoft Azure for Government
• Red Hat OpenShift Service on AWS (Cost Monitoring and Optimization insights only)
• Cast AI Anywhere – for any Kubernetes cluster, including on-premises, neo-cloud providers, or hybrid environments (Read more)

How to get started in 5 minutes or less

There are two ways to get started with Cast AI:

Method 1: Agentless discovery (Cloud Connect)

For AWS and GCP customers, Cast AI offers an agentless approach to discover your clusters without installing any components:

1. Head to console.cast.ai to open a free account.

2. Click on Connect cloud in the cluster list and select your cloud provider.

3. Choose your permission scope – Select the permission level that fits your security requirements:

   • Default – Read-only access using AWS-managed ReadOnlyAccess policy or GCP Reader role
   • Minimal – Targeted permissions for core services (EC2, EKS, RDS, SageMaker, commitments)
   • AWS AI services – Additional List*, Describe*, and Get* permissions for AWS AI/ML services

   For detailed information about what's included in each permission scope, see the Cloud Connect permissions documentation.

4. Run the provided script – Copy and run the generated script in your cloud shell or terminal. This gives Cast AI read-only access to discover your existing clusters across your cloud account.

5. View discovered clusters – All your clusters will appear as Discovered in the console. You can see the optimization potential of these clusters without installing any components.

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   Note

   For AWS, discovered resources are synchronized every hour. For GCP, this is currently a one-time discovery process. Continuous synchronization is planned for future releases.

6. Onboard clusters – Select any discovered cluster to onboard it to Cast AI by installing the read-only agent to start saving on your infrastructure costs.

Method 2: Install the read-only agent

1. Connect your cluster – Select any discovered cluster to onboard it to Cast AI by installing a read-only agent in your terminal or cloud shell. You will be guided through the process in the console.

2. Run a savings report to see how much you can save by adjusting your cluster configuration settings.

3. Explore the proposed savings and implement them automatically. Start by setting the Autoscaler policies to manage the process for you.

4. Check your cost monitoring reports to get a detailed breakdown of your expenses at the cluster, namespace, and workload levels.

Alternatively, if you can't connect your own cluster right now, you can use Cast AI's demo module to explore the insights the platform can provide.

Working with non-standard environments

If you're running Kubernetes in environments beyond the major cloud providers—such as on-premises, other cloud providers, or hybrid setups—Cast AI Anywhere gives you access to our workload optimization and resource consolidation features. While it doesn't include all the features available for major cloud providers, it delivers significant cost savings through resource efficiency.

Prerequisites

Cast AI doesn't require much technical knowledge, but you need the following:

• basic understanding of how to run a Kubernetes cluster in the public cloud (AWS, GCP, Azure) or other environments;
• working knowledge of the kubectl command line utility for creating and managing Kubernetes clusters.

Where to get help