Metrics

note

PayString was previously known as PayID.

Deploy a PayString server with Docker, and pull PayString metrics into Prometheus#

In this tutorial, you will deploy a PayString server and run Prometheus locally using Docker, and you will create a configuration file for the PayString server so that PayString 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 PayString server#

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

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

Create Docker network for PayString#

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

docker network create paystring-network

Start a Postgres Database#

To have a PayString server, you require a Postgres database to store PayString 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 paystring-network that you previously created. Name this docker container paystring-postgres, so that you can reference the container by name when you connect your PayString 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 paystring-postgres --network paystring-network -e POSTGRES_PASSWORD=password postgres

Start and test the PayString server#

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

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

Test whether the PayString server is running by creating a PayString 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 PayString 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 PayString 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: 'paystring-metric'
    honor_labels: true
    static_configs:
      - targets: ['paystring-server:8081']

Start the docker container:

docker run -d --network paystrings-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:

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