Apigee · Arazzo Workflow

Apigee Set Up Analytics Export and Read Stats

Version 1.0.0

Create an analytics datastore for export, then query environment statistics for a dimension.

1 workflow 1 source API 1 provider
View Spec View on GitHub Advanced API SecurityAgentic AIAnalyticsAPI GatewayAPI GovernanceAPI HubAPI ManagementDeveloper PortalEnterpriseGenerative AIHybridIntegrationMicroservicesMCPMonetizationArazzoWorkflows

Provider

apigee

Workflows

setup-analytics-datastore
Create an analytics datastore and query environment statistics.
Creates a datastore for analytics export and then reads environment statistics for a dimension to confirm analytics availability.
2 steps inputs: bucketName, datastoreDisplayName, dimensionName, environmentId, organizationId, select, targetType, timeRange outputs: datastoreSelf, environments
1
createDatastore
Create a datastore describing the Cloud Storage target Apigee will export analytics data to.
2
getStats
Query environment statistics for the chosen dimension to confirm analytics data is available.

Source API Descriptions

Arazzo Workflow Specification

Raw ↑
arazzo: 1.0.1
info:
  title: Apigee Set Up Analytics Export and Read Stats
  summary: Create an analytics datastore for export, then query environment statistics for a dimension.
  description: >-
    The analytics enablement flow. The workflow creates a datastore that defines
    where Apigee exports analytics data, then queries environment statistics for
    a chosen dimension so the operator can confirm analytics data is flowing.
    Every step spells out its request inline so the flow can be read and executed
    without opening the underlying OpenAPI description.
  version: 1.0.0
sourceDescriptions:
- name: analyticsApi
  url: ../openapi/apigee-analytics-api-openapi.yml
  type: openapi
workflows:
- workflowId: setup-analytics-datastore
  summary: Create an analytics datastore and query environment statistics.
  description: >-
    Creates a datastore for analytics export and then reads environment
    statistics for a dimension to confirm analytics availability.
  inputs:
    type: object
    required:
    - organizationId
    - environmentId
    - datastoreDisplayName
    - targetType
    - bucketName
    - dimensionName
    - select
    - timeRange
    properties:
      organizationId:
        type: string
        description: The Apigee organization to configure analytics for.
      environmentId:
        type: string
        description: The environment to query statistics from.
      datastoreDisplayName:
        type: string
        description: Display name for the analytics datastore.
      targetType:
        type: string
        description: Type of target for the data export (e.g. gcs or bigquery).
      bucketName:
        type: string
        description: Cloud Storage bucket name for the export target.
      dimensionName:
        type: string
        description: The analytics dimension to query statistics for (e.g. apiproxy).
      select:
        type: string
        description: Comma-separated metrics to select (e.g. sum(message_count)).
      timeRange:
        type: string
        description: Time range for the query (MM/DD/YYYY HH:MM~MM/DD/YYYY HH:MM).
  steps:
  - stepId: createDatastore
    description: >-
      Create a datastore describing the Cloud Storage target Apigee will export
      analytics data to.
    operationId: createDatastore
    parameters:
    - name: organizationId
      in: path
      value: $inputs.organizationId
    requestBody:
      contentType: application/json
      payload:
        displayName: $inputs.datastoreDisplayName
        targetType: $inputs.targetType
        datastoreConfig:
          bucketName: $inputs.bucketName
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      datastoreSelf: $response.body#/self
  - stepId: getStats
    description: >-
      Query environment statistics for the chosen dimension to confirm analytics
      data is available.
    operationId: getEnvironmentStats
    parameters:
    - name: organizationId
      in: path
      value: $inputs.organizationId
    - name: environmentId
      in: path
      value: $inputs.environmentId
    - name: dimensionName
      in: path
      value: $inputs.dimensionName
    - name: select
      in: query
      value: $inputs.select
    - name: timeRange
      in: query
      value: $inputs.timeRange
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      environments: $response.body#/environments
  outputs:
    datastoreSelf: $steps.createDatastore.outputs.datastoreSelf
    environments: $steps.getStats.outputs.environments

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Call it yourself

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curl "https://apis.io/api/v1/arazzo/apigee-analytics-datastore-setup-workflow"
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curl "https://apis.io/api/v1/arazzo?limit=25"

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