# Kedify Dashboard

The dashboard provides a fleet view of independent Kedify-connected clusters, their components and workload scaling activity. It receives the enabled telemetry through each cluster’s Agent connection. Managing an estate is distinct from distributing one workload across clusters.

![Kedify cluster dashboard](https://docs.kedify.io/assets/images/kedify-cluster-dashboard.png)

## Connect and inspect a cluster

1. Select the Kubernetes context and the intended Kedify organization. Record the namespace and any existing KEDA installation.

2. In the dashboard, select **Connect Cluster**, then follow [Helm installation](https://docs.kedify.io/installation/helm/) using that cluster’s installation identity.

3. Find the cluster in the dashboard. Compare component versions and readiness with `kubectl get pods -n keda` and `helm list --all-namespaces`.

4. Inspect one workload’s scaling activity. Check timestamps and filters; an Agent connection alone does not confirm that optional scalers are enabled.

For isolated KEDA operators and optional KPA controllers within a shared cluster, use [Multi-tenant scaling](https://docs.kedify.io/features/multitenant-keda/) and its [installation guide](https://docs.kedify.io/how-to/multitenant-scaling/).

If cluster data is missing or stale, check Agent readiness, organization identity and [outbound gRPC connectivity](https://docs.kedify.io/troubleshooting/#kedify-agent-is-unable-to-connect-to-the-kedify-service). Use [workload diagnostics](https://docs.kedify.io/troubleshooting/workload-scaling/) when data arrives but scaling fails.

## Use the right view for the question

- Component health and workload behavior: [Workload diagnostics](https://docs.kedify.io/troubleshooting/workload-scaling/) connects metrics and controller status to application outcomes.

- Resource recommendations: [Insights](https://docs.kedify.io/features/insights/) shows advisory CPU/memory changes for monitored workloads.

- Capacity and estimated cost: [FinOps](https://docs.kedify.io/features/finops/) explains windows, baselines and pricing coverage.

- Check scaling health: [Autoscaling Checks](https://docs.kedify.io/features/autoscaling-checks/) tests the signal-to-replica path before expanding a rollout.

## Fleet versus distribution

[Distributed multi-cluster scaling](https://docs.kedify.io/features/multi-cluster-scaling/) requires explicit member registration, remote access and placement policy; connecting clusters to the Dashboard does not register them for distributed scaling.

For organization credentials, telemetry and tenant boundaries, use [Access and data boundaries](https://docs.kedify.io/security-and-compliance/access-and-data/). If a cluster’s data is stale, compare Agent connection and local status before interpreting dashboard values.

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Canonical: https://docs.kedify.io/concepts/kedify-dashboard/
Source: src/content/docs/concepts/kedify-dashboard.md
Documentation index: https://docs.kedify.io/llms.txt