Manage Clusters
Once your KubeRaya cluster is created, CloudRaya provides management tools to help you monitor, scale, and control the cluster lifecycle safely and efficiently.
This page explains what you can manage from the CloudRaya Control Panel, how each area works, and when to use each action.
Cluster management in KubeRaya follows Kubernetes best practices while keeping operational complexity low.
What You Can Manage
From the CloudRaya dashboard, you can:
- View cluster configuration and status
- Inspect cluster resources and nodes
- Scale worker nodes manually or automatically
- Perform cluster lifecycle actions
- Delete clusters when no longer needed
Each action is scoped to infrastructure and cluster-level operations.
Application-level management remains fully Kubernetes-native.
Viewing Cluster Details
The Overview tab provides a high-level summary of your cluster.
Cluster Information
This section shows core metadata, including:
- Cluster package – selected node specification
- Kubernetes version – control plane and node version
- Billing cycle – hourly-based billing
- Creation and launch time
- Cluster description (if provided)
Package Information
Describes resource capacity per node:
- vCPU
- Memory
- Disk size
- Bandwidth allocation
These specifications apply to each node and determine workload capacity.
Cluster Status
Summarizes the operational state:
- Node composition – control plane (master) node(s) and worker node(s)
- High Availability – enabled or disabled
- Primary IP – control plane endpoint
- Additional public IPs – if attached
The Primary IP is used for cluster access and management, not for exposing applications.
Viewing Cluster Resources
The Resources tab displays infrastructure components running inside the cluster.
Node Resources
You can view:
- Control plane (master) node instance(s)
- Worker node instance(s)
- Creation timestamps for each node
This helps confirm topology and basic node health.
Additional Public IPs
If attached, public IPs appear here.
Public IPs are used only when required by specific exposure models.
Clusters do not receive public IPs automatically.
Scaling Worker Nodes
KubeRaya allows you to scale worker nodes based on workload demand.
You can choose between:
- Manual scaling – fixed number of worker nodes
- Automatic scaling – nodes scale within a defined range
Scaling behavior, limits, and cost implications are detailed below.
📄 See: Scale KubeRaya Nodes
Cluster Lifecycle Actions
From the cluster detail page, you can:
- Stop the cluster
- Restart the cluster
- Delete the cluster
These actions affect cluster availability and infrastructure, not application configuration.
Deletion is irreversible and should be performed with caution.
📄 See: Start / Stop KubeRaya Cluster
📄 See: Delete a KubeRaya Cluster
Shared Responsibility Reminder
CloudRaya manages:
- Kubernetes control plane infrastructure
- Cluster provisioning and availability
- Node lifecycle operations
You manage:
- Workloads and applications
- Kubernetes objects and configurations
- Scaling decisions
- Security at the workload level
Understanding this boundary ensures safe and predictable operations.