# Monitor Cluster Load with the Load Factor Dashboard > For the complete documentation index, see [llms.txt](https://docs.redpanda.com/llms.txt). Component-specific: [streaming-full.txt](https://docs.redpanda.com/streaming-full.txt) --- title: Monitor Cluster Load with the Load Factor Dashboard latest-redpanda-tag: v26.2.2 latest-console-tag: v3.11.0 latest-operator-version: v26.2.3 # EOL = End-of-Life (support lifecycle status) page-is-nearing-eol: "false" page-is-past-eol: "false" page-eol-date: July 28, 2027 latest-connect-version: 4.108.0 docname: monitor-load-factor page-component-name: streaming page-version: "26.2" page-component-version: "26.2" page-component-title: Streaming page-relative-src-path: monitor-load-factor.adoc page-edit-url: https://github.com/redpanda-data/docs/edit/main/modules/manage/pages/monitor-load-factor.adoc description: Use the Redpanda Load Factor Grafana dashboard to see how close each broker is running to the capacity of its host, across CPU, I/O scheduler, disk IOPS, memory, network bandwidth, and client connections. page-topic-type: how-to personas: platform_admin learning-objective-1: Identify the metrics endpoint and cluster property the Load Factor dashboard requires learning-objective-2: Import the Redpanda Load Factor dashboard into Grafana learning-objective-3: Interpret the load factor to decide when a cluster needs more capacity page-git-created-date: "2026-08-31" page-git-modified-date: "2026-08-31" support-status: supported --- Starting in Redpanda v26.2, the Redpanda Load Factor Grafana dashboard shows how close each broker is running to the capacity of its host. The dashboard compares live utilization against each resource’s capacity and reports the result as a percentage, the load factor, for each resource: CPU, I/O scheduler, disk read and write IOPS, memory, network bandwidth, and client connections. For disk and network, that capacity is estimated from the broker’s cloud instance type; the other resources use fixed or calculated limits (CPU utilization is already a percentage, memory reaches 100% when available memory falls to 10% of total, and connections use the lower of 1,000 per GiB of memory or 3,000 per shard). Use it to see how much headroom a cluster has, to decide when to scale, and to identify which resource saturates first as traffic grows. After reading this page, you will be able to: - Identify the metrics endpoint and cluster property the Load Factor dashboard requires - Import the Redpanda Load Factor dashboard into Grafana - Interpret the load factor to decide when a cluster needs more capacity ## [](#prerequisites)Prerequisites - All brokers must be running Redpanda v26.2 or later. - Prometheus must scrape either the [public metrics endpoint](https://docs.redpanda.com/streaming/current/manage/monitoring/) (`/public_metrics`) or the internal metrics endpoint (`/metrics`). Import the dashboard variant that matches the endpoint you scrape (see [Import the dashboard](#import-the-dashboard)). - The [`enable_host_metrics`](https://docs.redpanda.com/streaming/current/reference/properties/cluster-properties/#enable_host_metrics) cluster property must be enabled (the default). If it has been disabled, re-enabling it requires a broker restart. - `rpk` v26.2.2 or later, to generate the dashboard with [`rpk generate grafana-dashboard`](https://docs.redpanda.com/streaming/current/reference/rpk/rpk-generate/rpk-generate-grafana-dashboard/). With an earlier `rpk`, download the dashboard JSON directly instead (see [Import the dashboard](#import-the-dashboard)). - A [Grafana instance connected to your Prometheus data source](https://grafana.com/docs/grafana/latest/fundamentals/getting-started/first-dashboards/get-started-grafana-prometheus/). ## [](#how-load-factor-works)How load factor works Traditional utilization metrics tell you how busy a resource is, but not how much capacity remains. Load factor closes that gap by comparing utilization against what the host can deliver: - **Instance capacity metrics** estimate what the broker’s host can sustain. Redpanda recognizes the cloud instance type it runs on and emits the vendor’s nominal figures for it: vCPUs, memory, disk size, read and write IOPS, and network throughput (the `redpanda_instance_*` metric family, labeled with `cloud_provider` and `instance_type`). Capacity figures are emitted only when Redpanda recognizes the instance type. - **Host OS metrics** report actual disk activity from the host’s `/proc`: read and write counts and bytes for the block devices that back the Redpanda data and cache directories (the `redpanda_host_diskstats_*` family, gated by the `enable_host_metrics` cluster property). The `redpanda_io_queue_config_*` metrics report the I/O rates measured for the host during startup. These metric families are published on both metrics endpoints. On the internal endpoint (`/metrics`), the same metrics carry the `vectorized_` prefix instead of `redpanda_`. The dashboard computes a load factor for each resource and highlights the highest one, which shows the resource that saturates first. A load factor near 100% means the cluster is running close to its redline on that resource: sustained growth requires scaling up or out. > 📝 **NOTE** > > Redpanda does not emit a single `load_factor` metric. The load factor is computed by the dashboard from the metric families above. ## [](#limitations)Limitations - **Capacity estimates are nominal**: For disk and network, capacity estimates are the vendor’s nominal figures for the detected instance type. These figures are often achievable, but the actual capacity available to Redpanda may differ, for example, when achieved device performance differs from the vendor figures, or when another process on the same host consumes some of the resource. - **Unrecognized instance types**: When Redpanda does not recognize the instance type, capacity gauges are not emitted and the dashboard cannot compute a load factor for the affected resources. - **Host resource detection works only on AWS**: Load factors that depend on detected host resources are not reported on other cloud providers or on self-hosted hardware. You can modify the dashboard to use fixed, known values as the denominator in the load factor calculation instead. ## [](#import-the-dashboard)Import the dashboard 1. Generate the dashboard JSON with `rpk` (v26.2.2 or later): ```bash rpk generate grafana-dashboard --dashboard load-factor > redpanda-load-factor.json ``` `rpk` downloads the dashboard from the [Redpanda observability repository](https://github.com/redpanda-data/observability) and verifies its checksum. To skip `rpk`, download the latest [`Redpanda-Load-Factor-Dashboard.json`](https://github.com/redpanda-data/observability/blob/main/grafana-dashboards/Redpanda-Load-Factor-Dashboard.json) directly. 2. In Grafana, go to **Dashboards**, click **New**, and select **Import**. 3. Upload the JSON file, select your Prometheus data source, and click **Import**. The dashboard appears as **Redpanda - Load Factor (Public Metrics)**. > 📝 **NOTE** > > If your Prometheus scrapes the internal metrics endpoint (`/metrics`) rather than `/public_metrics`, import the [internal-metrics variant](https://github.com/redpanda-data/observability/blob/legacy_metrics/grafana-dashboards/Redpanda-Load-Factor-Dashboard.json) instead. That variant queries the `vectorized_` metric series and appears in Grafana as **Redpanda - Load Factor**. ## [](#read-the-dashboard)Read the dashboard The top row answers the headline question: - **Load Factor**: The current load factor per resource, as a percentage of estimated capacity. - **Highest Load Factor**: The single highest load factor across resources, which shows how close the broker is to its first bottleneck. The information panels describe the environment the estimates are based on: - **Host Info** and **Host Metrics Info**: The host-level statistics feeding the disk and network factors. If this panel warns that `host_metrics_info` is missing, check the [prerequisites](#prerequisites): Prometheus may not be scraping the metrics endpoint the dashboard variant expects, or `enable_host_metrics` may be disabled. - **Instance Info**: The detected cloud provider and instance type, and whether capacity estimates are available for it. - **IO Properties**: The I/O rates measured for the host during startup. The remaining panels break each factor down over time so you can attribute load to a resource: reactor and CPU utilization (per instance and per shard), I/O scheduler utilization, disk read and write IOPS, available memory, client connections, and network receive and transmit rates. ## [](#next-steps)Next steps - [Monitor Redpanda](https://docs.redpanda.com/streaming/current/manage/monitoring/) - [Public Metrics Reference](https://docs.redpanda.com/streaming/current/reference/public-metrics-reference/) - [Internal Metrics Reference](https://docs.redpanda.com/streaming/current/reference/internal-metrics-reference/) - [Manage Throughput](https://docs.redpanda.com/streaming/current/manage/cluster-maintenance/manage-throughput/) ## Suggested labs - [Owl Shop Example Application in Docker](https://docs.redpanda.com/labs/docker-compose/owl-shop/) - [Start a Single Redpanda Broker with Redpanda Console in Docker](https://docs.redpanda.com/labs/docker-compose/single-broker/) - [Start a Cluster of Redpanda Brokers with Redpanda Console in Docker](https://docs.redpanda.com/labs/docker-compose/three-brokers/) [Search all labs](https://docs.redpanda.com/labs)