How to query usage data from Image Processor

The workloadConsumptionMetrics dataset lets you get real-time aggregated data related to consumption and usage of Azion products, including Image Processor.

The information can be accessed through the GraphQL API, allowing you to transfer this data to a third-party platform, and enabling you to further analyze and review. Additionally, the data is available for up to 24 months.

This guide explains how to query images processed by Image Processor using the GraphiQL Playground.

Querying Image Processor’s usage data

To query the total number of images processed by Image Processor, proceed as follows:

Access the GraphiQL Playground by going to the following link: https://api.azion.com/v4/consumption/graphql.
- You must be logged in to your Azion account. Otherwise, you’ll receive an error message.
Send a query following this format:

query {
  workloadConsumptionMetrics(
    filter: {
      tsRange: {
        begin: "2025-02-01T00:00:00",
        end: "2025-03-01T00:00:00",
      }
      productId: 1441110021
      metricName: "images_processed"
    }
    aggregate: {
      sum: accounted
    }
    limit: 10000
    groupBy: [clientId, workloadId, productId, metricName]
  ) {
    clientId
    workloadId
    productId
    metricName
    total: sum
  }
}

Where:

Field	Description
`filter`	Defines the criteria used to filter the data returned by the query.
`tsRange`	A subfield of `filter`. Specifies a time range for filtering data. It includes `begin` and `end` fields to define the start and end timestamps. Format: `"YYYY-MM-DDTHH:mm:ss"`; example: `"2024-04-11T00:00:00"`.
`sum: accounted`	As a subfield of `aggregate`, calculates the total accounted usage for events matching the query’s filters and groups.
`limit`	Specifies the maximum number of results to return. System maximum: `10000`.
`groupBy`	Specifies the fields by which the query results should be grouped. Example: `[clientId, metricName]`.
`productId`	Unique identifier of the product being used. In this case, `1441110021` for Image Processor.
`metricName`	Name of the calculated metric for analytics. In this case, `images_processed`.

You’ll receive a JSON response similar to this:

{
  "data": {
    "workloadConsumptionMetrics": [
      {
        "clientId": "0000z",
        "workloadId": 4829103746,
        "productId": 1441110021,
        "metricName": "images_processed",
        "total": 32
      },
      {
        "clientId": "0000z",
        "workloadId": 1938475620,
        "productId": 1441110021,
        "metricName": "images_processed",
        "total": 19478
      },
      {
        "clientId": "0000z",
        "workloadId": 7584931026,
        "productId": 1441110021,
        "metricName": "images_processed",
        "total": 299612
      },
      {
        "clientId": "0000z",
        "workloadId": 6203849175,
        "productId": 1441110021,
        "metricName": "images_processed",
        "total": 1432
      },
      {
        "clientId": "0000z",
        "workloadId": 3948571023,
        "productId": 1441110021,
        "metricName": "images_processed",
        "total": 268675
      }
    ]
  }
}

Where:

Field	Description
`clientId`	Client unique identifier on Azion. Example: `8437r`.
`workloadId`	Identifier for the workload associated with the usage. Example: `4829301746`.
`productId`	Unique identifier of the product being used. In this case, `1441110021` for Image Processor.
`metricName`	Name of the measured metric for analytics. Example: `images_processed`.
`total`	Total number of images processed by Image Processor. This field is the result of a sum. Example: `268675`.