Load Camunda Operate API data to DuckDB
Build a Camunda Operate API to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Camunda Operate API API base URL, auth, endpoints, and incremental loading.
Camunda Operate is a tool for monitoring and troubleshooting process instances in Camunda 8, providing a REST API for programmatic access to workflow data. Everything needed to build a working Camunda Operate 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.
Build your Camunda Operate API to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Camunda Operate 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 Camunda Operate 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.
Camunda Operate API API at a glance
| Base URL | https://${REGION}.operate.camunda.io/${CLUSTER_ID}/v1/ (SaaS) or http://localhost:8080/v1/ (Self-Managed) |
| Example endpoint | POST v1/process-instances/search |
| Records found at | items |
| Authentication | all requests require a Bearer token obtained via OAuth 2.0 client credentials flow — sent in the Authorization header, prefixed Bearer |
| Pagination | Not paginated |
| API reference | https://docs.camunda.io/docs/8.8/apis-tools/operate-api/operate-api-authentication/ |
These values come from the Camunda Operate API API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Camunda Operate API API?
Requests require an Authorization header with a Bearer token (OAuth 2.0). The token is obtained via an OAuth 2.0 client credentials flow from an authorization server.
1. Get your credentials
- Navigate to the Camunda Console dashboard.
- Select the specific cluster you wish to access.
- Open the API tab within the cluster configuration.
- Click to create a new API client.
- Provide a descriptive name and define the necessary scopes (ensure Operate access is included).
- Save the Client ID and Client Secret immediately, as the secret is only displayed once.
- Use these credentials to request an OAuth 2.0 access token from the Authorization Server URL (typically https://login.cloud.camunda.io/oauth/token).
2. Add them to .dlt/secrets.toml
[sources.camunda_operate_api_source] camunda_client_id = "your_client_id_here" camunda_client_secret = "your_client_secret_here" camunda_oauth_url = "https://login.cloud.camunda.io/oauth/token" camunda_operate_base_url = "https://your-region.operate.camunda.io/your-cluster-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.
What Camunda Operate API data can I load into DuckDB?
These are the Camunda Operate API endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| process_instances | /v1/process-instances/search | POST | items | Search for process instances |
| process_definitions | /v1/process-definitions/search | POST | items | Search for process definitions |
| incidents | /v1/incidents/search | POST | items | Search for incidents |
| variable | /v1/variables/search | POST | items | Search for variables |
| flownode_instances | /v1/flownode-instances/search | POST | items | Search for flownode instances |
How do I load only new Camunda Operate API records?
The Camunda Operate API API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.
{"name": "process_instances", "endpoint": { "path": "v1/process-instances/search", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "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.
What does the generated Camunda Operate API pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /v1/process-instances/search and /v1/process-definitions/search from the Camunda Operate API API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def camunda_operate_api_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://${REGION}.operate.camunda.io/${CLUSTER_ID}/v1/ (SaaS) or http://localhost:8080/v1/ (Self-Managed)", "auth": {"type": "bearer", "token": access_token}, }, "resources": [ {"name": "process_instances", "endpoint": {"path": "v1/process-instances/search", "data_selector": "items"}}, {"name": "incidents", "endpoint": {"path": "v1/incidents/search", "data_selector": "items"}} ], } yield from rest_api_resources(config) def load_camunda_operate_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="camunda_operate_api_pipeline", destination="duckdb", dataset_name="camunda_operate_api_data", ) load_info = pipeline.run(camunda_operate_api_source()) print(load_info) if __name__ == "__main__": load_camunda_operate_api_to_duckdb()
Run it with python camunda_operate_api_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query Camunda Operate 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):
import dlt data = dlt.pipeline("camunda_operate_api_pipeline").dataset() df = data.process_instances.df() print(df.head())
SQL:
SELECT * FROM camunda_operate_api_data.process_instances LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Camunda Operate 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 Camunda Operate API loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load Camunda Operate API data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
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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