Documentation

Kubernetes Management

Operate clusters, workloads, and Kubernetes-native delivery workflows.

NebuaCloud is Kubernetes-first. The platform is designed around importing and operating real Kubernetes clusters instead of requiring a specific cloud provider integration.

Overview

You can connect existing clusters with kubeconfig or bring private infrastructure online through the Nebua Agent. From there, NebuaCloud helps you manage workloads, add-ons, and day-to-day operations from one place.

Current Scope

Import existing Kubernetes clusters
Connect private or on-prem infrastructure through the Nebua Agent
Review workloads, namespaces, and cluster health
Work with Helm-based application deployments
Pair cluster operations with logs, monitoring, and pipelines

Cluster Onboarding

Import an Existing Cluster

Use this flow when you already have a working cluster and a valid kubeconfig.

Open the cluster wizard
Choose Import
Paste or upload the kubeconfig
Verify connectivity and finish registration

Connect Private Infrastructure

Use this flow when the cluster or data center is behind private networking.

Choose On-Prem in the cluster wizard
Generate the cluster or connector details
Install the Nebua Agent on the target nodes
Let the agent establish outbound connectivity back to NebuaCloud

Working With Applications

Once a cluster is connected, you can:

Review deployed workloads
Track pod and service health
Manage Helm-based applications
Investigate rollout or startup problems with logs and monitoring

Networking and Exposure

NebuaCloud works with standard Kubernetes primitives and common add-ons.

Typical patterns include:

ClusterIP services for internal traffic
Ingress controllers for HTTP and HTTPS exposure
Load balancer services when your environment provides them
On-prem load balancer add-ons such as MetalLB when needed

Operations

For day-to-day operations, combine the Kubernetes view with other NebuaCloud workspaces:

Logs for container output and troubleshooting
Monitoring for cluster and workload metrics
Auto-scaling for resource scaling policies
Pipelines for build and deployment workflows

Best Practices

Keep kubeconfig access limited to trusted administrators
Set resource requests and limits for deployed workloads
Validate ingress and storage settings before production rollouts
Review pod events and logs after every failed deployment
Follow the High Availability guide before moving to production