Documentation Grafana Alloy Monitor metrics and logs Monitor Windows

Monitor Microsoft Windows servers and desktops with Grafana Alloy

Microsoft Windows provides tools like Performance Monitor and Event Viewer to track system performance metrics and event logs. With Alloy, you can collect your performance metrics and event logs, forward them to a Grafana stack, and create dashboards to monitor your Windows performance and events.

The alloy-scenarios repository contains complete examples of Alloy deployments. Clone the repository and use the examples to understand how Alloy collects, processes, and exports telemetry signals.

In this example scenario, Alloy collects Windows performance metrics and event logs and forwards them to a Loki destination.

Before you begin

Ensure you have the following:

• Docker
• Git
• A Windows Server or Desktop. This scenario monitors a computer running Windows.
• Windows administrator access. You need administrator access to install Alloy and configure it to collect metrics and logs.

Clone and deploy the example

Follow these steps to clone the scenarios repository and deploy the monitoring example:

1. Clone the Alloy scenarios repository.

   shell Copy

   git clone https://github.com/grafana/alloy-scenarios.git

2. Start Docker to deploy the Grafana stack.

   shell Copy

   cd alloy-scenarios/windows
   docker compose up -d

   Verify the status of the Docker containers:

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   docker ps

3. Install Alloy on Windows.

4. Replace the default config.alloy file with the preconfigured config.alloy file included in the alloy-scenarios/windows directory. For detailed steps explaining how to stop and start the Alloy service, refer to Configure Alloy on Windows.

   1. Stop the Alloy service.
   2. Replace the config.alloy file in C:\Program Files\GrafanaLabs\Alloy with the config.alloy file from the alloy-scenarios/windows directory.
   3. Start the Alloy service.

5. (Optional) To access the Alloy UI from a remote computer, add --server.http.listen-addr=0.0.0.0:12345 to the Alloy runtime arguments. For detailed steps explaining how to update this command-line argument, refer to Expose the UI to other machines. This step makes the Alloy UI available at http://<WINDOWS_IP_ADDRESS>:12345.

6. (Optional) Stop Docker to shut down the Grafana stack when you finish exploring this example.

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   docker compose down

Monitor and visualize your data

Use Grafana to monitor your deployment’s health and visualize your data.

Monitor Alloy

To monitor the health of your Alloy deployment, open your browser and go to http://localhost:12345.

For more information about the Alloy UI, refer to Debug Grafana Alloy.

Visualize your data

To explore metrics, open your browser and go to http://localhost:3000/explore/metrics.

To use the Grafana Logs Drilldown, open your browser and go to http://localhost:3000/a/grafana-lokiexplore-app.

To create a dashboard to visualize metrics and logs, open your browser and go to http://localhost:3000/dashboards.

Understand the Alloy configuration

This example uses a config.alloy file to configure the Alloy components for metrics and logging. You can find the config.alloy file in the cloned repository at alloy-scenarios/windows/.

The configuration includes livedebugging to stream real-time data to the Alloy UI.

Configure metrics

The metrics configuration in this example requires three components:

• prometheus.exporter.windows
• prometheus.scrape
• prometheus.remote_write

prometheus.exporter.windows

The prometheus.exporter.windows component exposes hardware and OS metrics for Windows-based systems. In this example, the component requires the following arguments:

• enabled_collectors: The list of collectors to enable.

alloy Copy

prometheus.exporter.windows "default" {
  enabled_collectors = ["cpu","cs","logical_disk","net","os","service","system", "memory", "scheduled_task", "tcp"]
}

prometheus.scrape

The prometheus.scrape component scrapes Windows metrics and forwards them to a receiver. In this example, the component requires the following arguments:

• targets: The target to scrape metrics from.
• forward_to: The destination to forward metrics to.

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prometheus.scrape "example" {
  targets    = prometheus.exporter.windows.default.targets
  forward_to = [prometheus.remote_write.demo.receiver]
}

prometheus.remote_write

The prometheus.remote_write component sends metrics to a Prometheus server. In this example, the component requires the following argument:

• url: Defines the full URL endpoint to send metrics to.

alloy Copy

prometheus.remote_write "demo" {
  endpoint {
    url = "http://localhost:9090/api/v1/write"
  }
}

Configure logging

The logging configuration in this example requires three components:

• loki.source.windowsevent
• loki.process
• loki.write

loki.source.windowsevent

The loki.source.windowsevent component reads events from Windows Event Logs and forwards them to other Loki components. In this example, the component requires the following arguments:

• eventlog_name: The event log to read from.
• use_incoming_timestamp: Assigns the current timestamp to the log.
• forward_to: The list of receivers to send log entries to.

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loki.source.windowsevent "application"  {
    eventlog_name = "Application"
    use_incoming_timestamp = true
    forward_to = [loki.process.endpoint.receiver]
}

alloy Copy

loki.source.windowsevent "System"  {
    eventlog_name = "System"
    use_incoming_timestamp = true
    forward_to = [loki.process.endpoint.receiver]
}

loki.process

The loki.process component receives log entries from other Loki components, applies one or more processing stages, and forwards the results to the list of receivers. In this example, the component requires the following arguments:

• forward_to: The list of receivers to send log entries to.
• expressions: The key-value pairs that define the name of the data extracted and the value that it’s populated with.
• values: The key-value pairs that define the label to set and how to look them up.
• source: Name from extracted values map to use for the timestamp.
• overwrite_existing: Overwrite the existing extracted data fields.

alloy Copy

Expand code

loki.process "endpoint" {
  forward_to = [loki.write.endpoint.receiver]
  stage.json {
      expressions = {
          message = "",
          Overwritten = "",
          source = "",
          computer = "",
          eventRecordID = "",
          channel = "",
          component_id = "",
          execution_processId = "",
          execution_processName = "",
      }
  }

  stage.structured_metadata {
      values = {
          "eventRecordID" = "",
          "channel" = "",
          "component_id" = "",
          "execution_processId" = "",
          "execution_processName" = "",
      }
  }

  stage.eventlogmessage {
      source = "message"
      overwrite_existing = true
  }

  stage.labels {
      values = {
          "service_name" = "source",
      }
  }

  stage.output {
    source = "message"
  }

}

loki.write

The loki.write component writes the logs out to a Loki destination. In this example, the component requires the following argument:

• url: Defines the full URL endpoint in Loki to send logs to.

alloy Copy

loki.write "endpoint" {
    endpoint {
        url ="http://localhost:3100/loki/api/v1/push"
    }
}

Configure livedebugging

Livedebugging streams real-time data from components directly to the Alloy UI. Refer to the Troubleshooting documentation for more details about this feature.

livedebugging

livedebugging is disabled by default. Enable it explicitly through the livedebugging configuration block to make debugging data visible in the Alloy UI.

alloy Copy

livedebugging {
  enabled = true
}