Load Avaya OneCloud CPaaS data to DuckDB

Avaya OneCloud CPaaS is a communications platform providing REST APIs for voice, SMS, and other business communications capabilities. Everything needed to build a working Avaya OneCloud CPaaS → 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 Avaya OneCloud CPaaS to DuckDB pipeline

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

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Run uvx dlthub-init@latest to build a pipeline from Avaya OneCloud CPaaS 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 Avaya OneCloud CPaaS 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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Avaya OneCloud CPaaS API at a glance

These values come from the Avaya OneCloud CPaaS API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Avaya OneCloud CPaaS API?

The API uses HTTP Basic authentication. The credentials consist of the Account SID and Auth Token, which must be combined as 'AccountSID:AuthToken', encoded in base64, and sent via the 'Authorization' header in the format 'Basic <base64_encoded_string>'.

1. Get your credentials

1. Log in to your account via the Avaya OneCloud CPaaS dashboard (typically at https://cloud.zang.io or the relevant regional portal). 2. Navigate to your account profile or dashboard summary page. 3. Locate the 'Account SID' and 'Auth Token' displayed in your account settings or credentials section. These two values serve as your primary authentication credentials for REST API requests.

2. Add them to .dlt/secrets.toml

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[sources.avaya_onecloud_cpaas_source]
api_key = "REPLACE_ME"

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 Avaya OneCloud CPaaS data can I load into DuckDB?

These are the Avaya OneCloud CPaaS endpoints dlt can load into DuckDB:

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How do I load only new Avaya OneCloud CPaaS records?

Avaya OneCloud CPaaS exposes nextPageToken on /analytics/v2/datasets/agent, 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": "analytics_historical", "endpoint": {
    "path": "/analytics/v2/datasets/agent",
    "data_selector": "data",
    "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 Avaya OneCloud CPaaS pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading SMS/Messages and Calls from the Avaya OneCloud CPaaS API into DuckDB:

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

@dlt.source
def avaya_onecloud_cpaas_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api-us.cpaas.avayacloud.com/v2 or https://api-eu.cpaas.avayacloud.com/v2",
            "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": api_key},
        },
        "resources": [
            {"name": "analytics_historical", "endpoint": {"path": "/analytics/v2/datasets/agent", "data_selector": "data"}},
            {"name": "available_numbers", "endpoint": {"path": "/AvailablePhoneNumbers/US/Local", "data_selector": "availablePhoneNumbers"}}
        ],
    }
    yield from rest_api_resources(config)


def load_avaya_onecloud_cpaas_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="avaya_onecloud_cpaas_pipeline",
        destination="duckdb",
        dataset_name="avaya_onecloud_cpaas_data",
    )
    load_info = pipeline.run(avaya_onecloud_cpaas_source())
    print(load_info)


if __name__ == "__main__":
    load_avaya_onecloud_cpaas_to_duckdb()

Run it with python avaya_onecloud_cpaas_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 Avaya OneCloud CPaaS 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("avaya_onecloud_cpaas_pipeline").dataset()
df = data.analytics_historical.df()
print(df.head())

SQL:

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SELECT * FROM avaya_onecloud_cpaas_data.analytics_historical LIMIT 10;

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

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How do I deploy the Avaya OneCloud CPaaS 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 Avaya OneCloud CPaaS 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 Avaya OneCloud CPaaS 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