Load AlloyDB API data to DuckDB

AlloyDB API provides management and administrative operations for Google Cloud AlloyDB for PostgreSQL clusters, instances, and backups. Everything needed to build a working AlloyDB API → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your AlloyDB API to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from AlloyDB API to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the AlloyDB API API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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AlloyDB API API at a glance

These values come from the AlloyDB API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the AlloyDB API API?

The AlloyDB REST API uses OAuth 2.0 authentication. Requests must include an 'Authorization: Bearer ' header, where the token is a valid OAuth 2.0 access token with sufficient scopes (typically https://www.googleapis.com/auth/cloud-platform).

1. Get your credentials

The AlloyDB API uses Google Cloud IAM and OAuth 2.0 for authentication rather than static API keys. To obtain credentials for programmatic access: 1. Go to the Google Cloud Console and navigate to IAM & Admin > Service Accounts. 2. Create a new service account or select an existing one. 3. Grant the service account the necessary IAM roles (e.g., roles/alloydb.admin or roles/alloydb.client). 4. Click on the service account, go to the Keys tab, and click Add Key > Create new key. 5. Select JSON as the key type and download the file. This file contains the credentials for service-to-service authentication. Alternatively, use Application Default Credentials (ADC) by running 'gcloud auth application-default login' in your local environment.

2. Add them to .dlt/secrets.toml

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[sources.alloydb_api_source]
google_application_credentials_path = "/path/to/your/service-account-key.json"
project_id = "your-gcp-project-id"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What AlloyDB API data can I load into DuckDB?

These are the AlloyDB API endpoints dlt can load into DuckDB:

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How do I load only new AlloyDB API records?

AlloyDB API exposes nextPageToken on v1/projects/*/locations/*/clusters, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "clusters", "endpoint": {
    "path": "v1/projects/*/locations/*/clusters",
    "data_selector": "clusters",
    "incremental": {"cursor_path": "nextPageToken", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated AlloyDB API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading projects.locations.clusters and projects.locations.clusters.instances from the AlloyDB API API into DuckDB:

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

@dlt.source
def alloydb_api_source(credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://alloydb.googleapis.com",
            "auth": {"type": "bearer", "token": credentials},
        },
        "resources": [
            {"name": "clusters", "endpoint": {"path": "v1/projects/*/locations/*/clusters", "data_selector": "clusters"}},
            {"name": "backups", "endpoint": {"path": "v1/projects/*/locations/*/backups", "data_selector": "backups"}}
        ],
    }
    yield from rest_api_resources(config)


def load_alloydb_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="alloydb_api_pipeline",
        destination="duckdb",
        dataset_name="alloydb_api_data",
    )
    load_info = pipeline.run(alloydb_api_source())
    print(load_info)


if __name__ == "__main__":
    load_alloydb_api_to_duckdb()

Run it with python alloydb_api_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query AlloyDB API data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("alloydb_api_pipeline").dataset()
df = data.clusters.df()
print(df.head())

SQL:

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SELECT * FROM alloydb_api_data.clusters LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the AlloyDB API to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw AlloyDB API loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load AlloyDB API data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack