Use this skill when converting Airflow code that references credentials via Airflow's connection system: any operator/hook kwarg ending in `_conn_id` (conn_id=, aws_conn_id=, snowflake_conn_id=, ssh_conn_id=, slack_conn_id=, gcp_conn_id=, http_conn_id=), any `BaseHook.get_connection(...)` or `Connection` class usage, any `AIRFLOW_CONN_<NAME>` environment variable, or a Secrets Backend (AWS Secrets Manager / Hashicorp Vault) configured for connections. Also covers distinguishing these from `Variable.get()` / `AIRFLOW_VAR_*`, which are non-secret config, not connections. Must be read before finalising any Orchestra YAML with a connection: field converted from an Airflow source.
Airflow never puts credentials directly in DAG code. Instead, every operator or hook takes a conn_id (or a provider-specific variant like snowflake_conn_id, aws_conn_id, ssh_conn_id, slack_conn_id, gcp_conn_id) that is a pointer to a Connection record — stored in the metadata DB, an AIRFLOW_CONN_* env var, or an external Secrets Backend. The DAG source almost never contains the real host/user/password; it only contains the conn_id string. This skill teaches how to recognize each of Airflow's idioms for expressing that pointer and map it to an Orchestra connection — including the full connection-type table, naming rules, and secrets handling in one place, the way dagster-connections-to-orchestra and prefect-connections-to-orchestra do for their own orchestrators.
connection: my_snowflake_12345 # format: descriptive-name_XXXXX (5-digit suffix from UI)The 5-digit suffix is assigned by Orchestra when the connection is created — copy it from the UI; never invent it.
No conn_id referenced? If the task doesn't actually take a _conn_id=/conn_id= kwarg or call BaseHook.get_connection(...) — pure computation, no external client, no secrets — don't invent a connection name or a fake env var placeholder just to fill the field:
connection: null # no distinct conn_id in the source; Orchestra uses the workspace default for this integrationThis extends to task parameters that duplicate connection-level scope, too — e.g. Power BI's workspace_id (from group_id), or any other parameter whose value is also stored on the Orchestra connection itself. If the source code just reads the same single value everywhere rather than genuinely varying it per task, leave that parameter null/omitted and let the connection's own configured value apply.
For environment-specific connections:
connection: ${{ ENV.SNOWFLAKE_CONNECTION_NAME }}Set SNOWFLAKE_CONNECTION_NAME=my_snowflake_12345 in Orchestra's environment settings.
| Airflow pattern | What it is | Where the real value lives |
|---|---|---|
conn_id="powerbi_default" / aws_conn_id= / snowflake_conn_id= / ssh_conn_id= / slack_conn_id= / gcp_conn_id= / http_conn_id= kwarg on an operator or hook | A pointer to a named Connection | Airflow metadata DB (Admin → Connections UI), OR an AIRFLOW_CONN_* env var, OR a Secrets Backend |
BaseHook.get_connection("my_conn").password (or .host, .login, .extra_dejson) inside a PythonOperator/@task | Same pointer, resolved manually in code instead of via a provider hook | Same three sources as above |
Connection(conn_id=..., conn_type=..., host=..., login=..., password=...) constructed and .add()'d in code (rare, usually in a setup/bootstrap script, not the DAG itself) | Programmatic connection creation | Whatever this code writes to — still ends up in the metadata DB |
AIRFLOW_CONN_MY_DB='postgres://user:pass@host:5432/db' env var (uppercased conn_id, URI-encoded value) | Connection defined entirely via environment, bypassing the metadata DB | The env var itself — if you can see this in a .env/deployment manifest, the real credential IS visible in source and needs care not to leak it into any file you write |
A Secrets Backend is configured (AwsSecretsManagerBackend, HashicorpVaultBackend, etc., set in airflow.cfg / secrets.backend) | Connection lookups resolve through the backend first, falling back to the metadata DB | Entirely outside Airflow — DAG code shows only the conn_id, nothing else to extract |
In every one of these cases, the Orchestra-side answer is the same: create one Orchestra connection per distinct conn_id and reference it by name in the YAML connection: field. The only thing that differs is how much information you can recover from source to help a human set up that connection correctly.
When conn_id= is generic (no provider-specific kwarg name), the operator class itself tells you the integration — e.g. conn_id="powerbi_default" on a Power BI refresh operator still maps to Orchestra's Power BI connection type, not a generic HTTP connection.
| Airflow kwarg / hook | Typical operator(s) | Orchestra connection type |
|---|---|---|
snowflake_conn_id= | SnowflakeOperator, SnowflakeHook | Snowflake |
postgres_conn_id= | PostgresOperator, PostgresHook | Postgres |
databricks_conn_id= | DatabricksSubmitRunOperator, DatabricksSqlOperator | Databricks |
gcp_conn_id= / google_cloud_conn_id= / bigquery_conn_id= | BigQueryOperator, BigQueryHook | GCP Big Query |
aws_conn_id= (targeting S3) | S3Hook, S3KeySensor | AWS |
azure_data_lake_conn_id= | ADLSHook | Azure |
mssql_conn_id= | MsSqlOperator, MsSqlHook | SQL Server |
aws_conn_id= (targeting Redshift) | RedshiftSQLOperator, RedshiftDataOperator | AWS Redshift |
conn_id= against a MotherDuck DSN | custom SqlSensor/PythonOperator | MotherDuck |
| Airflow kwarg / hook | Typical operator(s) | Orchestra connection type |
|---|---|---|
airbyte_conn_id= pointed at api.airbyte.com | AirbyteTriggerSyncOperator | Airbyte Cloud (see airbyte-cloud-airflow-to-orchestra) |
airbyte_conn_id= pointed at a self-hosted host | AirbyteTriggerSyncOperator | Airbyte Server (see airbyte-server-airflow-to-orchestra) |
fivetran_conn_id= | FivetranOperator, FivetranSensor | Fivetran (see fivetran-airflow-to-orchestra) |
dbt_conn_id= / SSH+dbt combo / Git repo config on a Cosmos ProjectConfig | dbt CLI via BashOperator/SSHOperator/Cosmos | dbt Core (see dbt-core-airflow-to-orchestra) |
| Airflow kwarg / hook | Typical operator(s) | Orchestra connection type |
|---|---|---|
slack_conn_id= | SlackAPIPostOperator, SlackWebhookOperator | Slack (see slack-airflow-to-orchestra) |
conn_id= on a PagerDuty hook | PagerdutyEventsHook | PagerDuty |
http_conn_id= on a Teams webhook call | SimpleHttpOperator against a Teams incoming webhook | Microsoft Teams |
SMTP settings in airflow.cfg / EmailOperator | EmailOperator |
| Airflow kwarg / hook | Typical operator(s) | Orchestra connection type |
|---|---|---|
ssh_conn_id= | SSHOperator | Linux SSH (see airflow-bash-ssh-to-orchestra) |
winrm_conn_id= | WinRMOperator | Windows SSH |
sftp_conn_id= | SFTPOperator, SFTPSensor | SFTP |
http_conn_id= | SimpleHttpOperator, HttpSensor | HTTP |
conn_id= (generic, no dedicated Airflow operator for Tableau/Power BI dataflows) | PowerBIOperator/hooks, hand-rolled PythonOperator/SimpleHttpOperator calls | Look up the specific integration from the operator/REST call it wraps — e.g. Tableau → Tableau Cloud (see tableau-airflow-to-orchestra), Power BI → Power BI (see powerbi-airflow-to-orchestra) |
If the Airflow deployment configures a Secrets Backend (AWS Secrets Manager, Hashicorp Vault, GCP Secret Manager) for connections, the DAG code you're converting will show only the conn_id — there is no metadata-DB row, no AIRFLOW_CONN_* env var, nothing else in source to extract. This is expected and does not change the conversion:
conn_id.Variable / AIRFLOW_VAR_* vs Connection / AIRFLOW_CONN_*These look similar (AIRFLOW_VAR_ vs AIRFLOW_CONN_ env var prefixes) but map to opposite places in Orchestra:
| Airflow | Nature | Orchestra target |
|---|---|---|
Variable.get("target_table") | Non-secret config (table name, env flag, feature toggle) | inputs: |
AIRFLOW_VAR_TARGET_TABLE=orders | Same as above, set via env var instead of the UI | inputs: |
BaseHook.get_connection("my_conn") / conn_id= kwarg | Credential (host, login, password, token) | Orchestra connection, referenced via connection: |
AIRFLOW_CONN_MY_DB='postgres://user:pass@host/db' | Same credential, expressed as a URI env var | Orchestra connection |
# Airflow — Variable is config, not a secret
target_table = Variable.get("target_table", default_var="orders")
# Airflow — Connection is a credential
hook = SnowflakeHook(snowflake_conn_id="snowflake_prod")# Orchestra
inputs:
target_table:
type: string
default: orders
pipeline:
stage-load:
tasks:
load-data:
integration: SNOWFLAKE
integration_job: SNOWFLAKE_RUN_QUERY
connection: snowflake_prod_12345 # from snowflake_conn_id="snowflake_prod"
parameters:
statement: 'INSERT INTO ${{ inputs.target_table }} SELECT * FROM staging'If a Variable value happens to look secret-shaped (an API key someone stashed as a Variable instead of a Connection), flag it — Airflow Variables are not encrypted by default unless the key name matches a configured "sensitive" pattern, so treat it with the same caution as a Prefect Variable.get() (see prefect-secrets-to-orchestra for the parallel case in another orchestrator).
_conn_id= kwarg, BaseHook.get_connection(, and Connection( usageAIRFLOW_CONN_* (connections) separately from AIRFLOW_VAR_* (config)conn_id, identify the operator/hook it's passed to and look up the Orchestra connection type (table above)airflow.cfg [secrets] backend) — if so, note that no further credential detail can be extracted from sourcename_XXXXX suffixconn_id="..." reference with the matching Orchestra connection: name_XXXXX in the YAMLVariable.get() / AIRFLOW_VAR_* values to inputs:, never to a connectionAIRFLOW_CONN_* URI or anywhere else) into the Orchestra YAML or any file — connections hold secrets in the Orchestra UI onlyconn_id can be reused across many tasks/DAGs — map it to a single Orchestra connection, don't create a duplicate per task.conn_id= is generic; the operator class disambiguates the type — the same generic kwarg name is used by Power BI, HTTP, and many community-provider operators, so identify the type from the operator/hook class, not the kwarg name alone.AIRFLOW_CONN_* URIs are real credentials in plain sight — if a deployment manifest or .env file has one, treat the value as sensitive; don't echo it back into any generated file, only use it to identify what fields the new Orchestra connection needs.Variable is not a secret store — even though it's fetched with a .get() call that superficially resembles Secret.load() in other orchestrators, Airflow Variables map to inputs:, not to a connection.LINUX_SSH — if a conn_id/ssh_conn_id is feeding a dbt CLI invocation, defer to dbt-core-airflow-to-orchestra, not this skill's SSH mapping.3a29fe4
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.