75 lines
3.6 KiB
Markdown
75 lines
3.6 KiB
Markdown
# Prometheus metrics showcase
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This is an example application that showcases how Watermill may be monitored with Prometheus metrics.
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The docker-compose bundle contains the following services:
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#### Golang
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A [Golang](https://hub.docker.com/_/golang) image which runs the [example code](https://github.com/ThreeDotsLabs/watermill/blob/master/_examples/basic/4-metrics/main.go). It consists of a router with a single handler.
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The handler consumes messages from a [Gochannel PubSub](https://github.com/ThreeDotsLabs/watermill/tree/master/message/infrastructure/gochannel), and publishes 0-4 copies of the message with a preconfigured random delay.
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Additionally, there is one goroutine which produces messages incoming to the handler with a gochannel publisher, and another goroutine which consumes the messages outgoing from the handler.
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The router, the standalone publisher and the standalone subscriber are all decorated with the metrics code and their statistics will appear in the dashboard.
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#### Prometheus
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[Prometheus](https://hub.docker.com/r/prom/prometheus/), to scrape the metrics which the golang application exposes at `:8081/metrics` by default. It is configured by a [prometheus.yml](https://github.com/ThreeDotsLabs/watermill/blob/master/_examples/basic/4-metrics/prometheus.yml) file, which declares the endpoints that Prometheus will scrape.
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#### Grafana
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[Grafana](https://hub.docker.com/r/grafana/grafana), to visualize the metrics in a dashboard.
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#### Running the example
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To run the docker-compose bundle, go to `_examples/metrics` and execute:
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```
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docker-compose up
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```
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The golang app will start running, producing messages, passing them through the handler, and consuming the copies.
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With default settings, the raw Prometheus metrics should appear at your http://localhost:8081/metrics.
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The Prometheus image should expose a more advanced UI at http://localhost:9090/graph, where you can investigate all the scraped metrics.
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However, what is the most useful way to monitor is through the use of Grafana, which you can access at http://localhost:3000.
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#### Adding the Prometheus data source to Grafana
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The fresh Grafana image should greet you with a login screen:
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Just use the default `admin:admin` credentials. You can skip changing the password, if you wish.
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The next thing that we need to do is to add the Prometheus data source. Click on `Add data source`.
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In the following screen:
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1. Enter a name for the Prometheus data source. Let's name this data source `prometheus`.
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1. Choose `Prometheus` from the `Type` dropdown.
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1. Enter the `http://localhost:9090` value in the HTTP/URL section.
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1. You can leave the remaining settings at default and click `Save & Test`.
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The Prometheus data source is now ready to use in Grafana.
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#### Importing the Grafana dashboard
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We have prepared a Grafana dashboard that visualizes the metrics exported by this example.
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To import the Grafana dashboard, select Dashboard/Manage from the left menu, and then click on `+Import` (or go to http://localhost:3000/dashboard/import).
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Enter the dashboard URL https://grafana.com/dashboards/9777 (or just the ID, 9777), and click on Load.
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Then select the Prometheus data source created in the previous step. Click on `Import`, and you're done!
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### Find out more
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To find out more, about metrics be sure to check out the [Watermill docs](https://watermill.io/docs/metrics).
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