Broadcom VMware Cloud Foundation Python API Docs | dltHub

Broadcom VMware Cloud Foundation API is a REST interface for managing SDDC resources such as domains, network pools, roles, and users. The REST API base URL is https://<SDDC_MANAGER_HOST>/v1 and All requests require a Bearer access token passed in the Authorization header..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Broadcom VMware Cloud Foundation data in under 10 minutes.

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What data can I load from Broadcom VMware Cloud Foundation?

Here are some of the endpoints you can load from Broadcom VMware Cloud Foundation:

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How do I authenticate with the Broadcom VMware Cloud Foundation API?

Obtain an access token by POSTing credentials to /v1/tokens, then include Authorization: Bearer <accessToken> header in every request.

1. Get your credentials

1. Log in to the Broadcom Developer Portal.
2. Open the "My Account" or "API Keys" section.
3. Click “Create New API Key” (or “Create Service Account”).
4. Copy the generated API key or service‑account credentials.
5. Use the API key in the token request payload as "apiKey": "<your_api_key>" to obtain an access token.

2. Add them to .dlt/secrets.toml

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[sources.broadcom_vmware_cloud_foundation_source]
access_token = "your_access_token_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Broadcom VMware Cloud Foundation API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python broadcom_vmware_cloud_foundation_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline broadcom_vmware_cloud_foundation_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset broadcom_vmware_cloud_foundation_data
The duckdb destination used duckdb:/broadcom_vmware_cloud_foundation.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline broadcom_vmware_cloud_foundation_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads domains and tokens from the Broadcom VMware Cloud Foundation API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def broadcom_vmware_cloud_foundation_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<SDDC_MANAGER_HOST>/v1",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "domains", "endpoint": {"path": "v1/domains", "data_selector": "elements"}},
            {"name": "users", "endpoint": {"path": "v1/users", "data_selector": "elements"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="broadcom_vmware_cloud_foundation_pipeline",
        destination="duckdb",
        dataset_name="broadcom_vmware_cloud_foundation_data",
    )
    load_info = pipeline.run(broadcom_vmware_cloud_foundation_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("broadcom_vmware_cloud_foundation_pipeline").dataset()
sessions_df = data.domains.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM broadcom_vmware_cloud_foundation_data.domains LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("broadcom_vmware_cloud_foundation_pipeline").dataset()
data.domains.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Broadcom VMware Cloud Foundation data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

• 401 Unauthorized – Occurs when the Authorization header is missing, the token is expired, or the token is invalid. Obtain a fresh access token via /v1/tokens.

Insufficient privileges

• 403 Forbidden – The token is valid but does not have the required role or permission for the requested operation. Verify that the user or service account has the appropriate role.

Token errors

• 404 Not Found – Returned when a refresh token is invalid or expired. Generate a new access token using the token endpoint.

Rate limiting

• 429 Too Many Requests – The API rate limit has been exceeded. Implement back‑off and retry after the period indicated in the Retry-After header.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack