fix: improve monitoring guide

content/docs/15.how-to-guides/monitoring.md

@@ -43,10 +43,16 @@ scrape_configs:
       - targets: ["<kestra-host-ip-address>:8081"]
 ```
 
-Be sure to put the appropriate `<kestra-host-ip-address>` in the last line. Now, we will start the Prometheus server using the following docker command:
+Be sure to put the appropriate `<kestra-host-ip-address>` in the last line, e.g. `localhost:8081` or `host.docker.internal:8081`.
+
+::alert{type="info"}
+If you're running everything in Docker on the same machine, you will need to change your host address to `host.docker.internal` rather than localhost.
+::
+
+We can start the Prometheus server using the following docker command:
 
 ```sh
-docker run -d -p 9090:9090 -v ~/Documents/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus
+docker run -d -p 9090:9090 -v ./prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus
 ```
 
 You can now go to `http://localhost:9090/graph` and try out visualizing some metrics using the PromQL. Here is one of the graphs for `kestra_executor_execution_started_count_total` metric:
@@ -61,20 +67,41 @@ Let us now move on to setting up Grafana. You start by installing Grafana using
  docker run -d -p 3000:3000 --name=grafana grafana/grafana-enterprise
 ```
 
-You can open the Grafana server at `http://localhost:3000`. The default credentials are `admin` as both username and passowrd. Once logged into Grafana, click on the hamburger menu on the top left and go to Connections -> Data Sources.
+You can open the Grafana server at `http://localhost:3000`. The default credentials are `admin` as both username and password. Once logged into Grafana, click on the hamburger menu on the top left and go to **Connections -> Data Sources**.
 
 ![grafana_data_sources](/docs/how-to-guides/setup-monitoring/grafana_data_sources.png)
 
-Click on `Add new Data Source` button present on the top right, and select `Prometheus` from the time series databases list. In the `Prometheus server URL` text box, put in the following URL: `http://<host-ip-address>:9090`. All the other confoguration can be left as default. You can click on `Save and Test` button at the bottom, and confirm that the connection to Prometheus database is successful.
+### Add Data Source
+
+Click on **Add new Data Source** button present on the top right, and select **Prometheus** from the time series databases list. In the **Prometheus server URL** text box, put in the following URL: `http://<host-ip-address>:9090`. All the other configuration can be left as default. You can click on **Save and Test** button at the bottom, and confirm that the connection to Prometheus database is successful.
+
+## Add Dashboard
+
+We are now all set to create the Grafana dashboard. For this, click on the **+** button on the top of the page to add a **New Dashboard** to Grafana. Save the dashboard with an appropriate name. Then, click on **Add visualization**, and select **prometheus** as the data source.
+
+We will create a Gauge that shows the number of tasks that are presently running. For this, select **Gauge** as the Visualization in the top right corner. In the PromQL metrics explorer text box, you can write `sum(kestra_worker_running_count)`. Click on **Run queries** button to ensure the Gauge shows up the number. 
+
+Head back to Kestra and create a number of tasks that will execute for a long time. The example below will sleep for 60 seconds:
+
+```yaml
+id: sleep
+namespace: company.team
+
+tasks:
+  - id: sleep_task
+    type: io.kestra.plugin.scripts.shell.Commands
+    commands:
+      - sleep 60
+```
 
-We are now all set to create the Grafana dashboard. For this, click on the `+` button on the top of the page to add a `New Dashboard` to Grafana. Save the dashboard with an appropriate name. Then, click on `Add visualization`, and select `prometheus` as the data source.
+Now we have some long-running tasks in progress, we can check that the Gauge correctly reflects the count. You can now put an appropriate title in the Panel options that says **Tasks running**. 
 
-We will create a Gauge that shows the number of tasks that are presently running. For this, select `Guage` as the Visualization in the top right corner. In the PromQL metrics explorer text box, you can write `sum(kestra_worker_running_count)`. Click on `Run queries` button to ensure the Guage shows up the number. You can now run some long-running task, and check that the Guage correctly reflects the count. You can now put an appropriate title in the Panel options, say `Tasks running`. This is how your Grafana should look like:
+This is how your Grafana should look like:
 
-![grafana_tasks_running_guage](/docs/how-to-guides/setup-monitoring/grafana_tasks_running_guage.png)
+![grafana_tasks_running_gauge](/docs/how-to-guides/setup-monitoring/grafana_tasks_running_gauge.png)
 
-Click on `Save` and `Apply` to add this guage to the dashboard.
+Click on **Save** and **Apply** to add this gauge to the dashboard.
 
-Similarly, you can now keep on adding more graphs to your dashboard. Here is one of the sample dashboards for Kestra metrics.
+Similarly, you can now keep on adding more graphs to your dashboard. Here is one of the example dashboards for Kestra metrics.
 
 ![kestra_metrics_dashboard](/docs/how-to-guides/setup-monitoring/kestra_metrics_dashboard.png)