gams87 · Aug 18, 2026 · Aug 18, 2026 · Oct 9, 2026
diff --git a/docs/how-tos/airflow/README.md b/docs/how-tos/airflow/README.md
@@ -2,7 +2,7 @@
 title: "Airflow in Datacoves: Key Things to Know First"
 sidebar_label: What to know
 description: "Important notes before writing Airflow DAGs in Datacoves: Ruff linting, Datacoves decorators, and My Airflow for faster personal DAG development."
-sidebar_position: 1
+sidebar_position: 10
 id: airflow-index
 ---
 # Airflow - What to know

diff --git a/docs/how-tos/airflow/airflow-3-migration-check.mdx b/docs/how-tos/airflow/airflow-3-migration-check.mdx
@@ -0,0 +1,83 @@
+---
+title: Check your DAGs for Airflow 3 migration issues
+sidebar_label: Airflow 3 migration check
+description: "Use the datacoves airflow3-check command to find and auto-fix Airflow 2 to 3 migration issues in your DAG code before upgrading your environment."
+sidebar_position: 20
+---
+# Check your DAGs for Airflow 3 migration issues
+
+:::info
+The `datacoves airflow3-check` command is available in Datacoves 6.1 and later. It works regardless of the Airflow version your environment runs, so you can (and should) use it while still on Airflow 2.
+:::
+
+When an environment is upgraded from Airflow 2 to Airflow 3, DAG code written for Airflow 2 may rely on imports, arguments, or behaviors that were removed or deprecated in Airflow 3, for example:
+
+| Airflow 2 pattern | Airflow 3 replacement |
+| --- | --- |
+| `from airflow.decorators import dag, task` | `from airflow.sdk import dag, task` |
+| `from airflow.operators.bash import BashOperator` | `from airflow.providers.standard.operators.bash import BashOperator` |
+| `schedule_interval="@daily"` | `schedule="@daily"` |
+| `email_on_failure` / `email_on_retry` in `default_args` | SMTP notifications (`SmtpNotifier`) |
+| Runtime-varying values in DAG definitions (e.g. `datetime.today()` in `start_date`) | Static values; Airflow 3 creates a new DAG version on every parse otherwise |
+
+Finding every occurrence across a repository by hand is tedious. The Datacoves code-server image ships the `datacoves airflow3-check` command, which scans your DAG code for all of these using [ruff's Airflow lint rules](https://docs.astral.sh/ruff/rules/#airflow-air), maintained alongside the Airflow project itself.
+
+## Run the check
+
+Open a terminal in your Datacoves workbench and run:
+
+```bash
+datacoves airflow3-check
+```
+
+By default it checks the DAGs folder configured for your environment. Each finding shows the file, line, offending pattern, and the suggested replacement:
+
+```
+airflow3-suggested-update: `airflow.decorators.dag` is removed in Airflow 3.0
+ --> orchestrate/dags/daily_run.py:13:2
+help: `dag` has been moved to `airflow.sdk` since Airflow 3.0
+```
+
+The command exits with code `0` when no issues are found and `1` when there are findings, so you can also use it in scripts or CI.
+
+To check a different directory (for example a scratch folder, or a repo with a non-standard layout), pass it explicitly:
+
+```bash
+datacoves airflow3-check path/to/dags
+```
+
+## Apply automatic fixes
+
+Some issues have unambiguous, safe fixes (for example `schedule_interval` -> `schedule`). Apply them with:
+
+```bash
+datacoves airflow3-check --fix
+```
+
+Changes that could alter behavior, such as rewriting imports to their new locations, are reported but not applied automatically; review each finding's `help:` line and update the code by hand.
+
+:::tip
+Commit or stash your work before running `--fix` so you can review the changes with `git diff`.
+:::
+
+## Recommended workflow
+
+1. Run `datacoves airflow3-check` on your repository while the environment is still on Airflow 2 and work through the findings. Fixes like `schedule_interval` -> `schedule` already work on recent Airflow 2 releases; for new-location imports such as `airflow.sdk` (Airflow 3 only), use a portable pattern while both versions are in play:
+
+   ```python
+   try:
+       # Airflow 3
+       from airflow.sdk import dag, task
+   except ImportError:
+       # Airflow 2
+       from airflow.decorators import dag, task
+   ```
+
+   The check recognizes this pattern and will not flag the Airflow 2 import inside the `except` branch.
+
+2. Re-run it until it reports no issues.
+3. Coordinate the environment upgrade with your Datacoves administrator.
+
+:::note
+The check covers Python DAG files. DAGs generated from YAML definitions (`dbt-coves generate airflow-dags`) are regenerated by the tooling and do not usually need manual migration.
+:::
diff --git a/docs/how-tos/airflow/api-triggered-dag.md b/docs/how-tos/airflow/api-triggered-dag.md
@@ -2,7 +2,7 @@
 title: How to Trigger an Airflow DAG Using Datasets
 sidebar_label: Trigger DAG via Datasets
 description: "Step-by-step guide to triggering Airflow DAGs via dataset events in Datacoves, enabling data-driven pipeline orchestration without time-based schedules."
-sidebar_position: 6
+sidebar_position: 140
 ---
 # How to Trigger a DAG using Datasets
 

diff --git a/docs/how-tos/airflow/customize-worker-environment.md b/docs/how-tos/airflow/customize-worker-environment.md
@@ -2,7 +2,7 @@
 title: Set Up a Custom Environment for Airflow Workers
 sidebar_label: Worker - Custom Environment
 description: "Configure a custom Docker image for Airflow workers in Datacoves to include specific Python packages, libraries, or dependencies your DAGs require."
-sidebar_position: 39
+sidebar_position: 150
 ---
 # How to set up a custom environment for your Airflow workers
 

diff --git a/docs/how-tos/airflow/dags/_category_.yaml b/docs/how-tos/airflow/dags/_category_.yaml
@@ -1,5 +1,5 @@
 label: DAGs
-position: 11
+position: 40
 link:
   type: generated-index
   title: DAGs

diff --git a/docs/how-tos/airflow/initial-setup.mdx b/docs/how-tos/airflow/initial-setup.mdx
@@ -2,7 +2,7 @@
 title: Airflow Configuration Guide for Datacoves Admins
 sidebar_label: Initial Setup
 description: "Configure Airflow in Datacoves: set DAG paths, git sync branch, Kubernetes executor settings, and environment-level service connections for dbt jobs."
-sidebar_position: 1
+sidebar_position: 50
 ---
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';

diff --git a/docs/how-tos/airflow/request-resources-on-workers.md b/docs/how-tos/airflow/request-resources-on-workers.md
@@ -2,7 +2,7 @@
 title: Request Custom CPU & Memory for Airflow Workers
 sidebar_label: Worker - Request CPU & Memory
 description: "Configure Kubernetes resource requests for individual Airflow tasks in Datacoves to allocate specific CPU and memory limits per DAG task."
-sidebar_position: 40
+sidebar_position: 160
 ---
 # How to request more memory or cpu resources on a particular DAG task
 

diff --git a/docs/how-tos/airflow/send-emails.md b/docs/how-tos/airflow/send-emails.md
@@ -2,7 +2,7 @@
 title: Send Email Notifications on Airflow DAG Failure
 sidebar_label: Notifications - Email
 description: "Configure email alerts for Airflow DAG failures in Datacoves: set up SMTP integration, define recipient lists, and handle task-level notifications."
-sidebar_position: 34
+sidebar_position: 70
 ---
 # How to send email notifications on DAG's failure
 

diff --git a/docs/how-tos/airflow/send-ms-teams-notifications.md b/docs/how-tos/airflow/send-ms-teams-notifications.md
@@ -2,7 +2,7 @@
 title: Send MS Teams Alerts on Airflow DAG Failure
 sidebar_label: Notifications - MS Teams
 description: "Configure Microsoft Teams notifications for Airflow DAGs in Datacoves to receive alerts when pipeline tasks succeed, fail, or are retried."
-sidebar_position: 35
+sidebar_position: 80
 ---
 # How to send Microsoft Teams notifications on DAG's status
 

diff --git a/docs/how-tos/airflow/send-slack-notifications.md b/docs/how-tos/airflow/send-slack-notifications.md
@@ -2,7 +2,7 @@
 title: Send Slack Notifications on Airflow DAG Status
 sidebar_label: Notifications - Slack
 description: "Set up Slack alerts for Airflow DAG events in Datacoves: connect a workspace, configure channel routing, and receive success or failure messages."
-sidebar_position: 36
+sidebar_position: 90
 ---
 # How to send Slack notifications on DAG's status
 

diff --git a/docs/how-tos/airflow/sync-database.mdx b/docs/how-tos/airflow/sync-database.mdx
@@ -2,7 +2,7 @@
 title: Sync the Internal Airflow Database in Datacoves
 sidebar_label: Sync Internal Database
 description: "How to sync the internal Airflow metadata database in Datacoves to apply configuration changes, reset state, or recover from database inconsistencies."
-sidebar_position: 3
+sidebar_position: 130
 ---
 
 # Sync Airflow database

diff --git a/docs/how-tos/airflow/use-airflow-api.md b/docs/how-tos/airflow/use-airflow-api.md
@@ -2,7 +2,7 @@
 title: Access the Airflow REST API in Datacoves
 sidebar_label: Airflow REST API
 description: "Authenticate with and call the Airflow REST API in Datacoves: generate API tokens, trigger DAGs, check run status, and query task instances programmatically."
-sidebar_position: 2
+sidebar_position: 30
 ---
 # How to use the Airflow API
 

diff --git a/docs/how-tos/airflow/use-aws-secrets-manager.mdx b/docs/how-tos/airflow/use-aws-secrets-manager.mdx
@@ -2,7 +2,7 @@
 title: Use AWS Secrets Manager for Airflow in Datacoves
 sidebar_label: Secrets - AWS Secrets Manager
 description: "Configure AWS Secrets Manager as the secrets backend for Apache Airflow in Datacoves to securely store and retrieve connections and variables."
-sidebar_position: 36
+sidebar_position: 100
 ---
 # How to use AWS Secrets Manager in Airflow
 

diff --git a/docs/how-tos/airflow/use-azure-key-vault.mdx b/docs/how-tos/airflow/use-azure-key-vault.mdx
@@ -2,7 +2,7 @@
 title: Use Azure Key Vault for Airflow in Datacoves
 sidebar_label: Secrets - Azure Key Vault
 description: "Configure Azure Key Vault as the secrets backend for Apache Airflow in Datacoves to securely store and retrieve connections and variables using Managed Identity."
-sidebar_position: 37
+sidebar_position: 110
 ---
 # How to use Azure Key Vault in Airflow
 

diff --git a/docs/how-tos/airflow/use-datacoves-secrets-manager.mdx b/docs/how-tos/airflow/use-datacoves-secrets-manager.mdx
@@ -2,7 +2,7 @@
 title: Use the Datacoves Secrets Manager in Airflow
 sidebar_label: Secrets - Datacoves Manager
 description: "How to use the built-in Datacoves Secrets Manager to store and inject secrets into Airflow connections and variables without exposing credentials in code."
-sidebar_position: 38
+sidebar_position: 120
 ---
 
 # How to use Datacoves Secrets Manager in Airflow

diff --git a/docs/how-tos/airflow/use-key-pair-authentication.md b/docs/how-tos/airflow/use-key-pair-authentication.md
@@ -2,7 +2,7 @@
 title: Use Key-Pair Authentication in Airflow
 sidebar_label: Key-Pair Authentication
 description: "Configure Snowflake key-pair authentication for Airflow connections in Datacoves instead of password-based credentials for improved security."
-sidebar_position: 10
+sidebar_position: 60
 ---
 # Using Key-Pair Authentication in Airflow