Skills Development Deploy Clari Data Pipelines To Cloud

Deploy Clari Data Pipelines To Cloud

v20260423
clari-deploy-integration
This skill provides blueprints for deploying Clari data export pipelines into robust, production-grade cloud environments. It guides users on setting up reliable, scheduled, and serverless data syncs using major platforms like Airflow DAGs, AWS Lambda, and Google Cloud Functions. Ideal for automating revenue forecasting and business intelligence data extraction.
Get Skill
380 downloads
Overview

Clari Deploy Integration

Overview

Deploy Clari export pipelines to production environments: Airflow DAGs, AWS Lambda, or Google Cloud Functions for scheduled, serverless execution.

Instructions

Airflow DAG

# dags/clari_export_dag.py
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.models import Variable
from datetime import datetime, timedelta

def export_clari_forecast(**context):
    from clari_client import ClariClient, ClariConfig

    client = ClariClient(ClariConfig(
        api_key=Variable.get("clari_api_key"),
    ))

    period = context["params"].get("period", "2026_Q1")
    data = client.export_and_download("company_forecast", period)

    entries = data.get("entries", [])
    context["ti"].xcom_push(key="entry_count", value=len(entries))
    # Load to warehouse here

dag = DAG(
    "clari_daily_export",
    schedule_interval="0 6 * * *",
    start_date=datetime(2026, 1, 1),
    catchup=False,
    default_args={"retries": 2, "retry_delay": timedelta(minutes=5)},
)

export_task = PythonOperator(
    task_id="export_forecast",
    python_callable=export_clari_forecast,
    dag=dag,
)

AWS Lambda

# lambda_handler.py
import json
import boto3
from clari_client import ClariClient, ClariConfig

def handler(event, context):
    ssm = boto3.client("ssm")
    api_key = ssm.get_parameter(
        Name="/clari/api-key", WithDecryption=True
    )["Parameter"]["Value"]

    client = ClariClient(ClariConfig(api_key=api_key))
    data = client.export_and_download(
        event.get("forecast_name", "company_forecast"),
        event.get("period", "2026_Q1"),
    )

    return {
        "statusCode": 200,
        "body": json.dumps({"entries": len(data.get("entries", []))}),
    }

Google Cloud Function

# main.py
import functions_framework
from google.cloud import secretmanager
from clari_client import ClariClient, ClariConfig

@functions_framework.http
def clari_export(request):
    sm = secretmanager.SecretManagerServiceClient()
    secret = sm.access_secret_version(name="projects/my-proj/secrets/clari-api-key/versions/latest")
    api_key = secret.payload.data.decode()

    client = ClariClient(ClariConfig(api_key=api_key))
    data = client.export_and_download("company_forecast", "2026_Q1")

    return {"entries": len(data.get("entries", []))}

Error Handling

IssueCauseSolution
Lambda timeoutExport takes > 15minUse Step Functions for long jobs
Secret not foundWrong parameter pathVerify SSM/Secret Manager path
Airflow task failsRate limitedAdd retries with backoff

Resources

Next Steps

For webhook setup, see clari-webhooks-events.

Info
Category Development
Name clari-deploy-integration
Version v20260423
Size 3.41KB
Updated At 2026-04-27
Language