Configuring Export Pipeline Destinations & Permissions

Before you can schedule exports, you need to create a Destination — a configured cloud storage bucket where Clarisights will upload your exported files. This article covers how to set up Amazon S3 and Google Cloud Storage destinations.

Amazon S3

Configuration Fields

Authentication Options

Choose one of the following:

Option A: Direct Credentials

• Access Key ID and Secret Access Key for an IAM user with write permissions to the bucket

Option B: Cross-Account IAM Role (Recommended)

• Role ARN — The ARN of an IAM role in your AWS account that Clarisights can assume (e.g., arn:aws:iam::123456789012:role/ClarisightsExportRole)

• External ID (optional) — An external ID for additional security when assuming the role

Required S3 Permissions

The IAM user or assumed role must have the following permission on the target bucket:

s3:PutObject

Example bucket policy for cross-account role:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::747179778889:role/ClarisightsExternalAccessRole"
      },
      "Action": "sts:AssumeRole",
      "Resource": "arn:aws:iam::YOUR_ACCOUNT:role/ClarisightsExportRole"
    }
  ]
}

Google Cloud Storage

Configuration Fields

Required GCS Permissions

Grant the following permission to the Clarisights service account on the target bucket:

storage.objects.create

The simplest way is to assign the Storage Object Creator role to the Clarisights service account on your bucket.

File Structure in Your Bucket

Exported files are organized as follows:

{path_prefix}/from_clarisights/{company_name}/{channel_name}/{extract_id}/{timestamp}_{start_date}_{end_date}.csv.gz
{path_prefix}/from_clarisights/{company_name}/{channel_name}/{extract_id}/{timestamp}_{start_date}_{end_date}.meta.json

Each export produces two files per extract:

• Data file (.csv.gz) — The exported data in CSV format, optionally gzip-compressed

• Metadata file (.meta.json) — Contains column mapping, date range, and compression info

Metadata File Structure

{
  "pipeline_name": "my_pipeline",
  "extract_id": "core_metrics",
  "date_range": {
    "start_date": "2026-04-10",
    "end_date": "2026-04-17"
  },
  "compression": "gzip",
  "column_mapping": [
    { "column_name": "campaign", "ui_name": "Campaign" },
    { "column_name": "impressions", "ui_name": "Impressions" }
  ]
}

If a single export exceeds 100,000 rows, it is automatically split into numbered chunks (e.g., .csv.gz.1, .csv.gz.2).

Managing Destinations

• Destination names must be unique within your company

• A destination cannot be deleted while it is referenced by an active schedule

• You can update destination credentials at any time without affecting existing schedules

In case of any queries, feel free to reach out to us from the messenger support on the platform.