Overview

The Amazon S3 integration in Netcore enables users to import contact data from an Amazon S3 bucket. This feature allows you to automate data ingestion, ensuring that contact information remains up-to-date.

This document provides step-by-step instructions for setting up the Amazon S3 import, configuring AWS permissions, and ensuring successful data transfer.

Types of Imports

Netcore can import the following from your S3 buckets:

• Registered Users: These are users who are already registered on Netcore.
• Anonymous Users: These are users who are not yet registered on Netcore.

Prerequisites

Before configuring the integration, ensure that:

• You have an Amazon S3 bucket created in your AWS account.
• You have the necessary AWS IAM permissions to allow Netcore to fetch data.
• The files follow the naming convention required for import.

Activate Amazon S3 Integration

Follow the steps below to activate Amazon S3 on the Netcore CE dashboard.

1. Log in to the Netcore CE dashboard and navigate to Integrations.
2. Locate Amazon S3 under the Connected section.
3. Select Integration type as Import and click ADD INTEGRATION.
4. Provide theConnection Name and enter the Bucket Name as specified in your AWS S3 setup.
5. Specify the Bucket Path using the following naming convention, "folder_name/subfolder_name/". Ensure that Bucket Path ends with a "/" and do not include bucket name in the bucket path.
6. Select the Region from the dropdown menu, such as us-west-2, in-2, in-1, and so on.
7. Select the email addresses from the dropdown menu in the Alert Email field. These email addresses receive notifications if issues arise during the ongoing export process.
8. Select your preferred Configuration method. The options are IAM (recommended) and Access key.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::sample-bucket"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::sample-bucket/*"
            ]
        }
    ]
}

Lambda Function

To automate data import, follow these steps to configure an AWS Lambda trigger:

1. Navigate to the AWS Console> Lambda, and click Create Function.
2. Enter a Function Name and select Python 3.11 as the runtime.
3. Click Create Function to complete the setup.
4. Under the function's settings, click Add Trigger and select S3 as the source.
5. In the Bucket field, enter the same bucket name used in the CE dashboard.
6. Set the Event Type to All object create events.
7. In the Prefix field, specify the folder path defined in the CE panel (Suffix is optional).
8. Check the acknowledgment box and click Add to finalize the trigger.
9. To add the Lambda function code, navigate to Lambda > Functions.
10. Select the created function, paste the provided code (from Netcore documentation) into Code Source, and click Deploy.

📘

Increasing Lambda Function Timeout for Better Performance

We recommend increasing the timeout of your Lambda function to at least 1 minute.
Recommended: 5 minutes for optimal performance.

Steps to Increase Timeout:

1. Navigate to the Configuration tab.
2. Click Edit under the Timeout section.
3. Set the Timeout to 5 minutes.
4. Click Save to apply the changes.

This ensures your function has enough time to execute without interruptions.

This trigger ensures that Netcore automatically fetches the data whenever a new file is added to the specified S3 folder.

Activate the Integration

1. Click Activate on the Netcore CE dashboard.
2. If successful, the integration status will show Connected.

A successful connection ensures any file uploaded to the S3 bucket will be automatically imported into Netcore.

File Naming Conventions

Each file uploaded in the S3 bucket must follow a structured naming convention to be processed correctly. Files that do not follow this convention will be rejected. Here is the structure how to name a file: [Type]~[List Name]~[Timestamp]~[Anonymous/Identified].csv

Example File Names:

L~CustomerList~20240210~Identified.csv → Adds contacts to the "CustomerList".
CM~Users~20240209~Anonymous.csv → Updates Contact Master with anonymous users.

Key Components

• L → List | CM → Contact Master.
• CustomerList → The target list name.
• 202503111530 → Timestamp format: yyyymmddhhMM (to prevent duplication).
• Identified or Anonymous → Specifies user type.

Check the import status of uploaded files under Logs.