Skip to content
Back to skills

Data Connectivity

ASecurity

Connect Domino workloads to external data sources including AWS S3 (via Mountpoint CSI driver), credential propagation with AWS IRSA and Azure Entra ID, and External Data Volumes. Use when configuring S3 access, setting up credential propagation, or connecting to cloud data sources from Domino.

  • 3 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added October 9, 2026
ai-agentspythonrailskubernetesawsazuregitdatabasedocumentation

Works with

  • cli

Security analysis

A100/100

Pro scans all 4 files and shows the line behind each finding

Scanned October 9, 2026

npx -y skills add dominodatalab/domino-ai-plugin --skill data-connectivity --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Data Connectivity?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Data Connectivity
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/dominodatalab-data-connectivity/badge)](https://www.skillsdirectory.com/skills/dominodatalab-data-connectivity)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: domino-data-connectivity
description: Connect Domino workloads to external data sources including AWS S3 (via Mountpoint CSI driver), credential propagation with AWS IRSA and Azure Entra ID, and External Data Volumes. Use when configuring S3 access, setting up credential propagation, or connecting to cloud data sources from Domino.
---

# 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.

## Safety Rules

The setup guides in this skill are platform-administrator procedures that change cloud IAM and
Kubernetes cluster state. When using them:

- **Explain, don't execute.** Show `aws iam`, `eksctl`, `helm`, `kubectl`, `az` commands and
  IAM/RBAC policies for the user to review and run. Do not run them yourself unless the user
  explicitly asks you to run that specific command.
- **Least privilege.** Scope every policy to named buckets, endpoints, or resources. Never
  propose `"Resource": "*"` or wildcard actions such as `s3:*`.
- **No secrets in output.** Never print, log, or echo access keys, tokens, or client secrets, and
  never ask the user to paste one into the chat.
- **Read-only troubleshooting.** Prefer `get`/`describe` commands over `exec` into running pods.

## Key Concepts

### Data Access Options in Domino

| Option | Use Case |
|--------|----------|
| **Datasets** | Project-level data storage |
| **Data Sources** | External database connections |
| **External Data Volumes (EDV)** | Mount external storage as volumes |
| **S3 Mountpoint** | Direct S3 access as file system |
| **Credential Propagation** | Pass user identity to cloud services |

### Credential Propagation Methods

| Method | Cloud | Description |
|--------|-------|-------------|
| **IRSA** | AWS | IAM Role for Service Accounts via OIDC |
| **Azure Entra ID** | Azure | User-based credential propagation |

## Related Documentation

- [S3-MOUNTPOINT.md](./S3-MOUNTPOINT.md) - AWS S3 as local file system
- [AWS-IRSA.md](./AWS-IRSA.md) - AWS IAM Role for Service Accounts
- [AZURE-CREDENTIALS.md](./AZURE-CREDENTIALS.md) - Azure Entra ID integration

## Quick Start

### Accessing S3 Data

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

```python
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:

```python
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:

```python
# 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](https://domino.ai/resources/blueprints/transforming-s3-into-local-storage)
- [AWS IRSA Blueprint](https://domino.ai/resources/blueprints/aws-irsa)
- [Azure Credential Propagation Blueprint](https://domino.ai/resources/blueprints/domino-azure-credential-propagation)

## GitHub Repository

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

Files in this skill

  • AWS-IRSA.md7.9 KB
  • AZURE-CREDENTIALS.md7.7 KB
  • S3-MOUNTPOINT.md7 KB
  • SKILL.md3.8 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.