Domino Data Connectivity Skill

This skill provides comprehensive knowledge for connecting Domino workloads to external data sources, including AWS S3, Azure storage, and credential propagation.

Key Concepts

Data Access Options in Domino

Credential Propagation Methods

Related Documentation

• S3-MOUNTPOINT.md - AWS S3 as local file system
• AWS-IRSA.md - AWS IAM Role for Service Accounts
• AZURE-CREDENTIALS.md - Azure Entra ID integration

Quick Start

Accessing S3 Data

With Mountpoint S3 configured, access S3 as a local file system:

import pandas as pd

# S3 data appears as local files
df = pd.read_parquet("/mnt/s3-data/datasets/sales.parquet")

Using IRSA for AWS Services

With IRSA configured, AWS SDK uses automatic credentials:

import boto3

# No explicit credentials needed - IRSA provides them
s3 = boto3.client('s3')
response = s3.list_objects_v2(Bucket='my-bucket')

Accessing External Data Volumes

EDVs are mounted at configured paths:

# Read from external volume
with open("/mnt/external-data/config.json") as f:
    config = json.load(f)

When to Use Each Option

Use S3 Mountpoint When:

• Working with large datasets stored in S3
• Need file system interface to S3
• Want to avoid EFS costs for large data
• Require multi-region data access

Use IRSA When:

• Need AWS service access from Domino workloads
• Policy prohibits long-lived credentials
• Require user-level audit trails
• Need cross-account role assumption

Use Azure Entra When:

• Working with Azure data services
• Need OAuth-based authentication
• Require user-level access control
• Need centralized RBAC

Blueprint References

• S3 Mountpoint Blueprint
• AWS IRSA Blueprint
• Azure Credential Propagation Blueprint

GitHub Repository

Implementation templates available at: https://github.com/dominodatalab/domino-blueprints