Monitoring

This page outlines how to set up monitoring for the GRR components. GRR keep tracks of many metrics which can be used to create charts about GRR’s performance, health, and workload.

When Monitoring.http_port is configured, each GRR component exports metrics at http://<host>:<port>/metrics. The export is human-readable plain-text and follows the Open Metrics standard. More importantly however, Prometheus can parse the metrics.

Example Setup

This example will walk you through a basic Prometheus setup. For this example, the GRR Frontend, Worker, and Admin UI will be launched on your local machine. Please refer to Installing GRR Server for a real-world setup.

  1. Install GRR, for example from pip.

  2. Run the GRR components locally. Execute each of the three commands in a separate terminal:

    grr_server --component admin_ui -p Monitoring.http_port=44451
    
    grr_server --component frontend -p Monitoring.http_port=44452
    
    grr_server --component worker -p Monitoring.http_port=44453
    

    Note: Custom monitoring port assignment is only required because the ports would clash when running multiple GRR components on one machine. Prometheus requires to know which type of component listens on which ports. If you use Monitoring.http_port_max, make sure that only one type of GRR components (e.g. only workers) listen on a given range of ports.

  3. Open http://localhost:44451/metrics in your browser. You should see a plain-text list of metrics.

  4. Install Prometheus, e.g. by downloading and unpacking the archive file.

  5. Configure Prometheus to scrape GRR. Save the following configuration as prometheus.yml in the Prometheus folder.

    global:
      scrape_interval: 15s
     
    scrape_configs:
      - job_name: 'grr_admin_ui'
        static_configs:
        - targets: ['localhost:44451']
    
      - job_name: 'grr_frontend'
        static_configs:
        - targets: ['localhost:44452']
    
      - job_name: 'grr_worker'
        static_configs:
        - targets: ['localhost:44453']
    
  6. Start Prometheus, by running the following command from the Prometheus folder:

    ./prometheus --config.file=prometheus.yml
    
  7. Open http://localhost:9090/targets in your browser. After a couple seconds, you should see three targets (grr_admin_ui, grr_frontend, grr_worker), each having 1 instance up.

  8. Open the Expression Browser by clicking on Graph (http://localhost:9090/graph). On this page, click on the Graph tab (next to Console). Then, try any of the example queries to query GRR metrics. Be aware that you might only see very few data points, very low values, or no data at all since GRR is not under any real workload and has 0 connected clients in this example.

Example Queries

To get you started, this page contains some example queries. These queries give you a good insight on GRRs health and workload.

QPS rate for the Frontend

rate(frontend_request_count_total{job="grr_frontend"}[1m])

Latency for requests to the Frontend

rate(frontend_request_latency_sum{job="grr_frontend"}[5m]) /
rate(frontend_request_latency_count{job="grr_frontend"}[5m])

Active Tasks running on the Frontend

frontend_active_count

Rate of successful flows on the Worker

rate(grr_flow_completed_count_total{job="grr_worker"}[5m])

Rate of failed flows on the Worker

rate(grr_flow_errors_total{job="grr_worker"}[5m])

Threadpool latency in the Worker

rate(threadpool_working_time_sum{job="grr_worker"}[5m]) /
rate(threadpool_working_time_count{job="grr_worker"}[5m])

Threadpool queueing time in Worker

rate(threadpool_queueing_time_sum{job="grr_worker"}[5m]) /
rate(threadpool_queueing_time_count{job="grr_worker"}[5m])

Number of outstanding tasks in the Worker

threadpool_outstanding_tasks{job="grr_worker"}

Number of threads running on the Worker

threadpool_threads{job="grr_worker"}

Rate of client crashes reported to the Worker

rate(grr_client_crashes_total{job="grr_worker"}[5m])

Real-World Setup

Although Prometheus can display basic charts using the expression browser, we recommend the usage of a dedicated visualization software, e.g. Grafana. You can set up a quick configuration of Grafana to scrape the metrics from Prometheus by following these instructions.

To set up metric-based alerts, refer to Prometheus Alerting and Grafana Alerting.

Prometheus supports automatic Service Discovery for many types of infrastructure. Depending on your hosting setup and size of your GRR installation, this can be an improvement over manually hardcoding hostnames in the Prometheus configuration.

Security Considerations

A minimal HTTP service, based on prometheus_client is listening at Monitoring.http_port for each GRR component. This HTTP service exports read-only metrics under /metrics and /varz and does not enforce any access control. People with access to it can read aggregated metrics about your GRR installation. With these metrics, facts about the number of workers, flow activity, and service health can be derived. Make sure to limit access to the port, for example by employing a firewall. Furthermore, read Prometheus Security.

Example visualization and alerting setup

This example will walk you through setting up Grafana as a dedicated visualization software to parse, display and query metrics scraped from GRR server components by Prometheus. You will also be able to set up a simple alerting system using Grafana. These instructions assume that GRR server and Prometheus are both up and running.

  1. Install Grafana by following the instructions:
sudo apt-get install -y apt-transport-https
sudo apt-get install -y software-properties-common wget
wget -q -O - https://packages.grafana.com/gpg.key | sudo apt-key add -

sudo apt-get update
sudo apt-get install grafana

This will install the latest OSS release.

  1. After Grafana is installed, you may start the Grafana server by executing in a terminal (assuming your operating system either Debian or Ubuntu and you installed the latest OSS release):
sudo systemctl daemon-reload
sudo systemctl start grafana-server
sudo systemctl status grafana-server

This will get the Grafana server up and running on http://localhost:3000.

  1. Grafana is now set up and can be visited at http://localhost:3000. The username and password should be “admin”; please change it. If the Grafana UI doesn’t show up, either the installation of Grafana or the server run failed; make sure to check the official documentation.
  2. Set up Prometheus as a data source for Grafana, so that Grafana can display the metrics from Prometheus. To do that, follow the guide here (in step 3, we suggest naming the data source grr-server so that it will match the configuration file for the provided sample dashboards later on).
  3. Grafana is set up and ready to show metrics scraped by Prometheus. You can start by either creating your own dashboards or importing exisiting dashboards into Grafana. You may choose to import sample GRR dashboards from the Grafana folder in GRR repository before creating your own. These dashboards contain some example graphs of metrics scraped by Prometheus, and also implement sample alerts. To do that, first download the dashboards from the repository, and then head over to http://localhost:3000/dashboard/import. There, you can click ‘Upload .json file’ and upload the dashboard you have downloaded from the repository. The dashboard is now imported; you can access it by going to http://localhost:3000/dashboards and clicking the dashboard’s name, e.g “Frontends Dashboard”. Each of the sample GRR dashboards correspond to a different component of GRR server, e.g the Frontends Dashboard shows aggregated metrics from all Frontends that are active in GRR server. Each of the dashboards contain several panels; each such panel consists of a graph that may contain one or more metrics queried from Prometheus, and possibly alerting rules.
  4. If you wish to use the alerts, you first need to define a notification channel for the alerts. This can be done by heading over to http://localhost:3000/alerting/notification/new and following the form to add a notification channel. Once a notification channel is set up, you will start receiving alerts from the existing dashboards, as those contain definitions for simple alerts. There are two alerting rules: in each dashboard, there is a panel that counts the number of active processes for the specific job. For example, in the Workers dashboards, there is a panel called “Active Processes” which shows the current number of active Workers processes. If the number of active workers is zero - an alert will be fired. If you wish to disable or remove an alert, go to the dashboard and the corresponding panel, and there you may remove the alerting rule.
  5. You can now use the dashboards. The dashboards can give a general overview over the main components of the GRR server, which can be utilized by the user to monitor different metrics of each component. Examples for such metrics can be found in the examples above. Remember that the dashboards and alerts are flexible, and can be expanded or modified to adjust to your exact needs. Additional metrics can be used by exploring http://<host>:<port>/metrics for each component of GRR server (change the port according to the GRR server component you want), and if you wish to create your own custom dashboards, panels and alerts, make sure to go over the corresponding documentation in Grafana.