Using Prometheus and Grafana to View OpenViking Metrics

Connect the metric endpoint to a dashboard in four steps:

1. Start OpenViking and verify that /metrics is accessible
2. Start Prometheus to scrape OpenViking metrics
3. Start Grafana and connect the Prometheus data source
4. Import the OpenViking built-in dashboard or query directly in Explore

If you can already access http://<host>:<port>/metrics, you can skip ahead to the "Start Prometheus" section of this document.

Architecture Overview

OpenViking does not directly provide a Grafana page. The standard pipeline is:

OpenViking -> /metrics -> Prometheus -> Grafana

Where:

• OpenViking is responsible for exposing Prometheus exposition text
• Prometheus is responsible for periodically scraping /metrics
• Grafana is responsible for reading from Prometheus and displaying dashboards

Prerequisites

Before starting, please confirm:

• OpenViking Server is installed and can start normally
• Docker is installed and can be used to quickly start Prometheus and Grafana
• You know the HTTP address that OpenViking is currently listening on, for example http://localhost:30300

Step 1: Confirm OpenViking Exposes /metrics

OpenViking must have metrics enabled first. Minimal configuration reference:

{
  "server": {
    "observability": {
      "metrics": {
        "enabled": true
      }
    }
  }
}

Merge the metrics section into ~/.openviking/ov.conf, then restart OpenViking Server.

If you have not started the service yet, you can refer to:

openviking-server doctor
openviking-server --port 30300

Then verify:

curl http://localhost:30300/metrics

If the response includes text with the openviking_ prefix, metrics are enabled. For example:

# HELP openviking_http_requests_total OpenViking metric.
# TYPE openviking_http_requests_total counter
openviking_http_requests_total{method="POST",route="/api/v1/search/find",status="200"} 12

If the response returns Prometheus metrics are disabled., the configuration has not taken effect or the service has not been restarted.

The examples use port 30300; OpenViking defaults to 1933. Keep the scrape target aligned with the port you actually start.

Step 2: Deploy Using the Repository's Built-in Compose Files

The repository already provides a set of ready-to-run observability examples, located at:

• examples/grafana/docker-compose.yml
• examples/grafana/prometheus.yml
• examples/grafana/grafana/provisioning/datasources/prometheus.yml
• examples/grafana/grafana/provisioning/dashboards/openviking.yml

In addition, for the scenario where OpenViking continues to listen on 127.0.0.1 / localhost on Linux, the repository also provides a localhost-specific set of examples:

• examples/grafana/docker-compose.localhost.yml
• examples/grafana/prometheus.localhost.yml
• examples/grafana/grafana/provisioning-localhost/datasources/prometheus.yml
• examples/grafana/grafana/provisioning-localhost/dashboards/openviking.yml

The difference between the two approaches is:

• docker-compose.yml: the general-purpose approach, where Prometheus accesses the host from the container network, suitable when OpenViking listens on 0.0.0.0
• docker-compose.localhost.yml: the Linux localhost approach, where Prometheus and Grafana directly use the host network, suitable when OpenViking continues to listen on 127.0.0.1

If you do not currently want to expose OpenViking on 0.0.0.0, it is recommended to use docker-compose.localhost.yml first.

By default, this configuration does several things:

• Starts Prometheus and maps the host port to 30909
• Starts Grafana and maps the host port to 13000
• Configures the Grafana data source as http://prometheus:9090 in the general setup, or http://127.0.0.1:30909 in the host-network setup
• Automatically loads the OpenViking demo dashboard from the repository
• Automatically loads OpenViking - Feedback Baseline, making it easy to directly view the baseline metrics for openviking_feedback_* and openviking_feedback_channel_*

These are local demonstration configurations with admin/admin credentials. The host-network variant still binds Prometheus to 0.0.0.0; its name describes how it reaches OpenViking, not restricted dashboard exposure. For local use, bind the dashboard services to loopback (Prometheus --web.listen-address=127.0.0.1:30909, Grafana GF_SERVER_HTTP_ADDR=127.0.0.1) or restrict their network access.

Approach A: General-Purpose

Run from the OpenViking repository root. Choose one Compose setup, since both use the same host ports:

docker compose -f examples/grafana/docker-compose.yml up -d

After startup completes, you can access:

Prometheus: http://localhost:30909
Grafana:    http://localhost:13000

In this example, the default Grafana credentials are fixed as:

• Username: admin
• Password: admin

Approach B: Linux localhost

If your OpenViking continues to listen on 127.0.0.1:30300, and you do not want to change OpenViking to 0.0.0.0 just for Prometheus scraping, use the following compose setup:

docker compose -f examples/grafana/docker-compose.localhost.yml up -d

The characteristics of this approach are:

• Prometheus uses the host network and directly scrapes 127.0.0.1:30300/metrics
• Grafana also uses the host network and directly connects to http://127.0.0.1:30909
• There is no need to change OpenViking to 0.0.0.0
• Dev mode can remain bound to loopback; see Authentication before changing the OpenViking bind address

The access addresses are still:

Prometheus: http://localhost:30909
Grafana:    http://localhost:13000

If 30909 or 13000 on the host is already occupied:

• For the Prometheus port, change --web.listen-address=0.0.0.0:30909 in examples/grafana/docker-compose.localhost.yml
• For the Grafana port, change GF_SERVER_HTTP_PORT=13000 in examples/grafana/docker-compose.localhost.yml
• At the same time, change http://127.0.0.1:30909 in examples/grafana/grafana/provisioning-localhost/datasources/prometheus.yml to the new port

If you only want a quick deployment, once you reach this point you can jump ahead to "How to Verify the Entire Pipeline Is Working".

Step 3: Understanding the Prometheus Scrape Configuration

The contents of examples/grafana/prometheus.yml used in the compose example are as follows:

global:
  scrape_interval: 15s

scrape_configs:
  - job_name: openviking
    metrics_path: /metrics
    static_configs:
      - targets: ["host.docker.internal:30300"]

Explanation:

• If Prometheus runs inside a Docker container while OpenViking runs on the host, it is recommended to write targets as host.docker.internal:30300
• If Prometheus also runs on the host, change it to localhost:30300
• If host.docker.internal is not available in your Linux Docker environment, change it to the actual host IP, for example 192.168.1.10:30300

If your OpenViking is not listening on 30300, change the target address in this file to your actual port, then re-run:

docker compose -f examples/grafana/docker-compose.yml restart prometheus

If you are using the Linux localhost approach, the corresponding file to modify is:

• examples/grafana/prometheus.localhost.yml

For example, if OpenViking is actually listening on 127.0.0.1:1933, change it to:

targets: ["127.0.0.1:1933"]

Then re-run:

docker compose -f examples/grafana/docker-compose.localhost.yml restart prometheus

Step 4: Optional - Create a Docker Network for Manual Deployment

If you are using the compose files above, you do not need to perform this step manually, because Compose automatically creates the default network.

For separate docker run commands, create a shared network first:

docker network create openviking-observability

If it reports that the network already exists, you can ignore it.

Step 5: Optional - Manually Start Prometheus

If you have already used docker compose -f examples/grafana/docker-compose.yml up -d, you can skip this section.

On many machines, 9090 is already occupied by another service. To reduce conflicts, it is recommended here to map the host port to 30909:

docker run -d \
  --name prometheus \
  --network openviking-observability \
  -p 127.0.0.1:30909:9090 \
  --add-host host.docker.internal:host-gateway \
  -v "$PWD/examples/grafana/prometheus.yml:/etc/prometheus/prometheus.yml:ro" \
  prom/prometheus

After startup, open in your browser:

http://localhost:30909

Once in the Prometheus UI, enter the following in the query box:

openviking_http_requests_total

Or:

openviking_service_readiness

If you can find time series, it means Prometheus has successfully scraped OpenViking metrics.

If the Prometheus Container Fails to Start

Common cause: the host port is occupied, for example:

Bind for 0.0.0.0:9090 failed: port is already allocated

How to handle:

• Change the host port, for example continue using 30909:9090
• Do not change the container-internal port 9090
• Use the new host port when accessing, for example http://localhost:30909

Step 6: Optional - Manually Start Grafana

If you have already used docker compose -f examples/grafana/docker-compose.yml up -d, you can skip this section.

Similarly, 3000 on many machines is also often occupied. It is recommended to map Grafana to host port 13000:

docker run -d \
  --name grafana \
  --network openviking-observability \
  -p 127.0.0.1:13000:3000 \
  grafana/grafana

After startup, open:

http://localhost:13000

The default initial Grafana credentials are usually:

• Username: admin
• Password: admin

If your environment has changed the default credentials, use the actual values.

Step 7: Optional - Manually Add the Prometheus Data Source in Grafana

If you are using the repository's built-in compose files, you can usually skip this step as well, because the data source is automatically provisioned.

In the Grafana UI:

1. Open Connections or Data sources in the left sidebar
2. Click Add data source
3. Select Prometheus
4. In the URL field, enter: http://prometheus:9090
5. Click Save & test

The reason for entering http://prometheus:9090 here is:

• Grafana and Prometheus run in the same Docker network openviking-observability
• The two containers can communicate directly via the container name

If Save & test fails, first run:

docker ps

Confirm that both the prometheus and grafana containers are running.

Step 8: First Query Directly in Grafana Explore

After adding the data source, verify these queries in Explore:

Requests per second:

rate(openviking_http_requests_total[5m])

View request volume and status codes by route:

sum by (route, status) (rate(openviking_http_requests_total[5m]))

P95 latency:

histogram_quantile(0.95, sum by (le, route) (rate(openviking_http_request_duration_seconds_bucket[5m])))

Queue backlog:

openviking_queue_pending

Model call volume:

rate(openviking_model_calls_total[5m])

Tokens per second:

rate(openviking_operation_tokens_total[5m])

If you are not yet sure which metric names exist, you can first query:

{__name__=~"openviking_.*"}

rate() needs multiple samples in the selected window. Feedback snapshot gauges, even those named _total, should be queried as current values; see Vikingbot metrics validation.

Step 9: Import the OpenViking Built-in Dashboards

If you are using the repository's built-in compose files, these two dashboards will be automatically loaded into the OpenViking folder after Grafana starts.

If you want to import them manually, just follow the steps below.

The repository already provides Grafana dashboards that can be imported directly:

• examples/grafana/openviking_demo_dashboard.json
• examples/grafana/openviking_token_demo_dashboard.json

Import steps:

1. Go to Dashboards in the left sidebar of Grafana
2. Click New or Import in the top right corner
3. Upload examples/grafana/openviking_demo_dashboard.json
4. On the import page, select the Prometheus data source you just created
5. Click Import

Notes:

• openviking_demo_dashboard.json is suitable as a basic overview dashboard
• openviking_token_demo_dashboard.json depends on the tim012432-calendarheatmap-panel plugin; before it is installed, some panels may not display properly

Step 10: How to Verify the Entire Pipeline Is Working

You can verify in the following order:

1. curl http://localhost:30300/metrics returns metric text
2. Open http://localhost:30909 and you can find openviking_http_requests_total in Prometheus
3. Open http://localhost:13000 and see that the Prometheus data source already exists, or that a manual Save & test succeeds
4. Running rate(openviking_http_requests_total[5m]) in Grafana Explore produces a graph
5. After importing the demo dashboard, the panels begin to display data

As long as all five steps pass, the entire pipeline is working.

FAQ

1. /metrics is accessible, but Prometheus cannot find any data

First check:

• Whether targets in prometheus.yml is written correctly
• Whether Prometheus has actually reloaded the new configuration
• Whether the Docker container can access port 30300 on the host

If you are using the repository's built-in compose files, first check:

docker compose -f examples/grafana/docker-compose.yml logs prometheus

If you suspect a container-to-host access issue, you can change host.docker.internal to the actual host IP.

2. The Prometheus Host Port Is Occupied

Example error:

Bind for 0.0.0.0:9090 failed: port is already allocated

How to handle: change to a different host port, for example:

  -p 30909:9090

3. The Grafana Host Port Is Occupied

How to handle: change to a different host port, for example:

-p 13000:3000

4. There Are No OpenViking Metrics in Grafana

First check:

• Whether the Grafana data source is actually connected to Prometheus
• Whether openviking_* metrics already exist in Prometheus
• Whether the time range is too short, resulting in no recent samples

If you are using the compose auto-import approach, you can also first confirm whether the dashboard has been loaded:

• Go to Dashboards in the left sidebar
• Check whether the OpenViking folder exists

5. The Dashboard Imports Successfully but the Panels Are Empty

Check these causes before changing the dashboard:

• The corresponding metric samples do not yet exist in Prometheus
• The filter conditions do not match the current environment
• The wrong data source was selected

It is recommended to first go back to Explore and manually run PromQL to confirm that the basic queries do have data.

Related Documents

• Observability and Troubleshooting
• Metrics
• Metrics API
• Server Deployment
• Quick Start