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metrics-tutorial
Get Started With Metrics
Get Started With Metrics

Deploy a PayID server with Docker, and pull PayID metrics into Prometheus

In this tutorial, you will deploy a PayID server and run Prometheus locally using Docker, and you will create a configuration file for the PayID server so that PayID metrics are pulled into Prometheus.

Prerequisites

Install the following software on your machine, if not already present.

Build a Docker container for setting up a PayID server

Run these commands to build a Docker container for a PayID server.

git clone https://github.com/payid-org/payid.git
cd payid
docker build -t payid-server .

Create Docker network for PayID

You will run several containers in Docker that must talk to each other. To set up these containers, create a docker network called payid-network.

docker network create payid-network

Start a Postgres Database

To have a PayID server, you require a Postgres database to store PayID accounts and address mappings. To do this, run the postgres database in docker with a default password of password, and tell the database to use the payid-network that you previously created. Name this docker container payid-postgres, so that you can reference the container by name when you connect your PayID server. Note that both the default database and the user are named postgres, as described at Postgres Docker Official Images.

docker run -d --rm --name payid-postgres --network payid-network -e POSTGRES_PASSWORD=password postgres

Start and test the PayID server

To start the PayID server, run the PayID server in docker using the image you created. You must also use the docker network payid-network so that it can connect to the payid-postgres container.

docker run -it -p 8080:8080 -p 8081:8081 --name payid-server --network payid-network -e DB_PASSWORD=password -e
    DB_NAME=postgres -e DB_HOSTNAME=payid-postgres payid-server

Test whether the PayID server is running by creating a PayID with this cURL command.

 curl --location --request POST 'http://127.0.0.1:8081/users' --header 'PayID-API-Version: 2020-06-16' --header 'Content-Type: application/json' --data-raw '{
     "payId": "charlie$127.0.0.1",
     "addresses": [
         {
             "paymentNetwork": "XRPL",
             "environment": "TESTNET",
             "details": {
                 "address": "rDk7FQvkQxQQNGTtfM2Fr66s7Nm3k87vdS"
             }
         }
     ]
 }'

You should get a Created response.

Query the PayID server to make sure it resolves, using this cURL command.

curl http://127.0.0.1:8080/charlie -H "PayID-Version: 1.0" -H "Accept: application/xrpl-testnet+json"`

Start Prometheus

In this step, you will run prometheus in docker and configure it to scrape the PayID server’s metrics. To do this, you need to create a prometheus.yml file on the host machine and mount it in the docker container.

Create a file named prometheus.yml with these contents.

global:
  scrape_interval: 15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
  evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.

scrape_configs:
  - job_name: 'payid-metric'
    honor_labels: true
    static_configs:
      - targets: ['payid-server:8081']

Start the docker container:

docker run -d --network payid-network -p 9090:9090 -v $PWD/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus`

You can verify Prometheus is running by opening http://localhost:9090/graph in a browser.

You can verify metrics collection metrics are being collected by entering the following expression into the form:

sum(payid_count)

Click Execute. If successful, the results look like this:

PayID Metrics setup and configuration

Click the Graph tab to display the results in graph format.

Here are some other example expressions:

  • sum(payid_count) by (paymentNetwork) - Sum of payid count by payment network, such as XRPL, BTC, and so forth.
  • sum(payid_lookup_request) - Total number of payid lookup requests.
  • rate(payid_lookup_request[5m]) - Rate of payid lookup requests per second.