Apache Release Notes

All Apache Release Notes (130)

• Apr 7, 2026

  • Date parsed from source:
    Apr 7, 2026
  • First seen by Releasebot:
    Apr 7, 2026
  

  Airflow by Apache

  Apache Airflow 3.2.0

  Airflow releases 3.2.0 with asset partitioning, multi-team deployments, and smarter deadline alerts, while expanding the UI with faster Grid performance, XCom editing, and richer task history. It also adds Python 3.14 support, new API and CLI options, and many stability fixes.

  📦 PyPI: https://pypi.org/project/apache-airflow/3.2.0/

  📚 Docs: https://airflow.apache.org/docs/apache-airflow/3.2.0/

  🛠 Release Notes: https://airflow.apache.org/docs/apache-airflow/3.2.0/release_notes.html

  🐳 Docker Image: "docker pull apache/airflow:3.2.0"

  🚏 Constraints: https://github.com/apache/airflow/tree/constraints-3.2.0

  Significant Changes

  Asset Partitioning

  The headline feature of Airflow 3.2.0 is asset partitioning — a major evolution of data-aware scheduling. Instead of triggering Dags based on an entire asset, you can now schedule downstream processing based on specific partitions of data. Only the relevant slice of data triggers downstream work, making pipeline orchestration far more efficient and precise.

  This matters when working with partitioned data lakes — date-partitioned S3 paths, Hive table partitions, BigQuery table partitions, or any other partitioned data store. Previously, any update to an asset triggered all downstream Dags regardless of which partition changed. Now only the right work gets triggered at the right time.

  For detailed usage instructions, see :doc:/authoring-and-scheduling/assets.

  Multi-Team Deployments

  Airflow 3.2 introduces multi-team support, allowing organizations to run multiple isolated teams within a single Airflow deployment.

  Each team can have its own Dags, connections, variables, pools, and executors— enabling true resource and permission isolation without requiring separate Airflow instances per team.

  This is particularly valuable for platform teams that serve multiple data engineering or data science teams from shared infrastructure, while maintaining strong boundaries between teams' resources and access.

  For detailed usage instructions, see :doc:/core-concepts/multi-team.

  .. warning::

  Multi-Team Deployments are experimental in 3.2.0 and may change in future versions based on user feedback.

  Synchronous callback support for Deadline Alerts

  Deadline Alerts now support synchronous callbacks via SyncCallback in addition to the existing asynchronous AsyncCallback. Synchronous callbacks are executed by the executor (rather than the triggerer), and can optionally target a specific executor via the executor parameter.

  A Dag can also define multiple Deadline Alerts by passing a list to the deadline parameter, and each alert can use either callback type.

  .. warning::

  Deadline Alerts are experimental in 3.2.0 and may change in future versions based on user feedback. Synchronous deadline callbacks (SyncCallback) do not currently support Connections stored in the Airflow metadata database.

  For detailed usage instructions, see :doc:/howto/deadline-alerts.

  UI Enhancements & Performance

  • Grid View Virtualization: The Grid view now uses virtualization -- only visible rows are rendered to the DOM. This dramatically improves performance when viewing Dags with large numbers of task runs, reducing render time and memory usage for complex Dags. (#60241)
  • XCom Management in the UI: You can now add, edit, and delete XCom values directly from the Airflow UI. This makes it much easier to debug and manage XCom state during development and day-to-day operations without needing CLI commands. (#58921)
  • HITL Detail History: The Human-in-the-Loop approval interface now includes a full history view, letting operators and reviewers see the complete audit trail of approvals and rejections for any task. (#56760, #55952)
  • Gantt Chart Improvements:
    • All task tries displayed: Gantt chart now shows every attempt, not just the latest
    • Task display names in Gantt: task_display_name shown for better readability (#61438)
    • ISO dates in Gantt: Cross-browser consistent date format (#61250)
    • Fixed null datetime crash: Gantt chart no longer crashes on tasks with null datetime fields

  New --only-idle flag for the scheduler CLI

  The airflow scheduler command has a new --only-idle flag that only counts runs when the scheduler is idle. This helps users run the scheduler once and process all triggered Dags and queued tasks. It requires and complements the --num-runs flag so one can set a small value instead of guessing how many iterations the scheduler needs.

  Replace per-run TI summary requests with a single NDJSON stream

  The grid, graph, gantt, and task-detail views now fetch task-instance summaries through a single streaming HTTP request (GET /ui/grid/ti_summaries/{dag_id}?run_ids=...) instead of one request per run. The server emits one JSON line per run as soon as that run's task instances are ready, so columns appear progressively rather than all at once.

  What changed:

  • GET /ui/grid/ti_summaries/{dag_id}?run_ids=... is now the sole endpoint for TI summaries, returning an application/x-ndjson stream where each line is a serialized GridTISummaries object for one run.
  • The old single-run endpoint GET /ui/grid/ti_summaries/{dag_id}/{run_id} has been removed.
  • The serialized Dag structure is loaded once and shared across all runs that share the same dag_version_id, avoiding redundant deserialization.
  • All UI views (grid, graph, gantt, task instance, mapped task instance, group task instance) use the stream endpoint, passing one or more run_ids.

  Structured JSON logging for all API server output

  The new json_logs option under the [logging] section makes Airflow produce all its output as newline-delimited JSON (structured logs) instead of human-readable formatted logs. This covers the API server (gunicorn/uvicorn), including access logs, warnings, and unhandled exceptions.

  Not all components support this yet — notably airflow celery worker but any non-JSON output when json_logs is enabled will be treated as a bug. (#63365)

  Remove legacy OTel Trace metaclass and shared tracer wrappers

  The interfaces and functions located in airflow.traces were internal code that provided a standard way to manage spans in internal Airflow code. They were not intended as user-facing code and were never documented. They are no longer needed so we remove them in 3.2. (#63452)

  Move task-level exception imports into the Task SDK

  Airflow now sources task-facing exceptions (AirflowSkipException, TaskDeferred, etc.) from airflow.sdk.exceptions. airflow.exceptions still exposes the same exceptions, but they are proxies that emit DeprecatedImportWarning so Dag authors can migrate before the shim is removed.

  What changed:

  • Runtime code now consistently raises the SDK versions of task-level exceptions.
  • The Task SDK redefines these classes so workers no longer depend on airflow-core at runtime.
  • airflow.providers.common.compat.sdk centralizes compatibility imports for providers.

  Behaviour changes:

  • Sensors and other helpers that validate user input now raise ValueError (instead of AirflowException) when poke_interval/ timeout arguments are invalid.
  • Importing deprecated exception names from airflow.exceptions logs a warning directing users to the SDK import path.

  Exceptions now provided by airflow.sdk.exceptions:

  • AirflowException and AirflowNotFoundException
  • AirflowRescheduleException and AirflowSensorTimeout
  • AirflowSkipException, AirflowFailException, AirflowTaskTimeout, AirflowTaskTerminated
  • TaskDeferred, TaskDeferralTimeout, TaskDeferralError
  • DagRunTriggerException and DownstreamTasksSkipped
  • AirflowDagCycleException and AirflowInactiveAssetInInletOrOutletException
  • ParamValidationError, DuplicateTaskIdFound, TaskAlreadyInTaskGroup, TaskNotFound, XComNotFound
  • AirflowOptionalProviderFeatureException

  Backward compatibility:

  • Existing Dags/operators that still import from airflow.exceptions continue to work, though they log warnings.
  • Providers can rely on airflow.providers.common.compat.sdk to keep one import path that works across supported Airflow versions.

  Migration:

  • Update custom operators, sensors, and extensions to import exception classes from airflow.sdk.exceptions (or from the provider compat shim).
  • Adjust custom validation code to expect ValueError for invalid sensor arguments if it previously caught AirflowException.

  Support numeric multiplier values for retry_exponential_backoff parameter

  The retry_exponential_backoff parameter now accepts numeric values to specify custom exponential backoff multipliers for task retries. Previously, this parameter only accepted boolean values (True or False), with True using a hardcoded multiplier of 2.0.

  New behavior:

  • Numeric values (e.g., 2.0, 3.5) directly specify the exponential backoff multiplier
  • retry_exponential_backoff=2.0 doubles the delay between each retry attempt
  • retry_exponential_backoff=0 or False disables exponential backoff (uses fixed retry_delay)

  Backwards compatibility:

  • Existing Dags using boolean values continue to work:
  • retry_exponential_backoff=True → converted to 2.0 (maintains original behavior)
  • retry_exponential_backoff=False → converted to 0.0 (no exponential backoff)

  API changes:

  The REST API schema for retry_exponential_backoff has changed from type: boolean to type: number. API clients must use numeric values (boolean values will be rejected).

  Migration:

  While boolean values in Python Dags are automatically converted for backwards compatibility, we recommend updating to explicit numeric values for clarity:

  • Change retry_exponential_backoff=True → retry_exponential_backoff=2.0
  • Change retry_exponential_backoff=False → retry_exponential_backoff=0

  Move serialization/deserialization (serde) logic into Task SDK

  Airflow now sources serde logic from airflow.sdk.serde instead of airflow.serialization.serde. Serializer modules have moved from airflow.serialization.serializers.* to airflow.sdk.serde.serializers.*. The old import paths still work but emit DeprecatedImportWarning to guide migration. The backward compatibility layer will be removed in Airflow 4.

  What changed:

  • Serialization/deserialization code moved from airflow-core to task-sdk package
  • Serializer modules moved from airflow.serialization.serializers.* to airflow.sdk.serde.serializers.*
  • New serializers should be added to airflow.sdk.serde.serializers.* namespace

  Code interface changes:

  • Import serializers from airflow.sdk.serde.serializers.* instead of airflow.serialization.serializers.*
  • Import serialization functions from airflow.sdk.serde instead of airflow.serialization.serde

  Backward compatibility:

  • Existing serializers importing from airflow.serialization.serializers.* continue to work with deprecation warnings
  • All existing serializers (builtin, datetime, pandas, numpy, etc.) are available at the new location

  Migration:

  • For existing custom serializers: Update imports to use airflow.sdk.serde.serializers.*
  • For new serializers: Add them to airflow.sdk.serde.serializers.* namespace (e.g., create task-sdk/src/airflow/sdk/serde/serializers/your_serializer.py)

  Methods removed from PriorityWeightStrategy

  On (experimental) class PriorityWeightStrategy, functions serialize() and deserialize() were never used anywhere, and have been removed. They should not be relied on in user code. (#59780)

  Methods removed from TaskInstance

  On class TaskInstance, functions run(), render_templates(), get_template_context(), and private members related to them have been removed. The class has been considered internal since 3.0, and should not be relied on in user code. (#59780, #59835)

  Modify the information returned by DagBag

  New behavior:

  • DagBag now uses Path.relative_to for consistent cross-platform behavior.
  • FileLoadStat now has two additional nullable fields: bundle_path and bundle_name.

  Backward compatibility:

  • FileLoadStat will no longer produce paths beginning with / with the meaning of "relative to the dags folder".
  • This is a breaking change for any custom code that performs string-based path manipulations relying on this behavior.
  • Users are advised to update such code to use pathlib.Path. (#59785)

  Remove --conn-id option from airflow connections list

  The redundant --conn-id option has been removed from the airflow connections list CLI command.

  Use airflow connections get instead. (#59855)

  Add operator-level render_template_as_native_obj override

  Operators can now override the Dag-level render_template_as_native_obj setting, enabling fine-grained control over whether templates are rendered as native Python types or strings on a per-task basis. Set render_template_as_native_obj=True or False on any operator to override the Dag setting, or leave as None (default) to inherit from the Dag.

  Add gunicorn support for API server with zero-downtime worker recycling

  The API server now supports gunicorn as an alternative server with rolling worker restarts to prevent memory accumulation in long-running processes.

  Key Benefits:

  • Rolling worker restarts: New workers spawn and pass health checks before old workers are killed, ensuring zero downtime during worker recycling.
  • Memory sharing: Gunicorn uses preload + fork, so workers share memory via copy-on-write. This significantly reduces total memory usage compared to uvicorn's multiprocess mode where each worker loads everything independently.
  • Correct FIFO signal handling: Gunicorn's SIGTTOU kills the oldest worker (FIFO), not the newest (LIFO), which is correct for rolling restarts.

  Configuration:

  [api]
  # Use gunicorn instead of uvicorn
  server_type = gunicorn
  # Enable rolling worker restarts every 12 hours
  worker_refresh_interval = 43200
  # Restart workers one at a time
  worker_refresh_batch_size = 1
  

  Or via environment variables:

  export AIRFLOW__API__SERVER_TYPE=gunicorn
  export AIRFLOW__API__WORKER_REFRESH_INTERVAL=43200
  

  Requirements:

  Install the gunicorn extra: pip install 'apache-airflow-core[gunicorn]'

  Note on uvicorn (default):

  The default uvicorn mode does not support rolling worker restarts because:

  • With workers=1, there is no master process to send signals to
  • uvicorn's SIGTTOU kills the newest worker (LIFO), defeating rolling restart purposes
  • Each uvicorn worker loads everything independently with no memory sharing

  If you need worker recycling or memory-efficient multi-worker deployment, use gunicorn. (#60921)

  Improved performance of rendered task instance fields cleanup for Dags with many mapped tasks (~42x faster)

  The config max_num_rendered_ti_fields_per_task is renamed to num_dag_runs_to_retain_rendered_fields (old name still works with deprecation warning).

  Retention is now based on the N most recent dag runs rather than N most recent task executions, which may result in fewer records retained for conditional/sparse tasks. (#60951)

  AuthManager Backfill permissions are now handled by the requires_access_dag on the DagAccessEntity.Run

  is_authorized_backfill of the BaseAuthManager interface has been removed. Core will no longer call this method and their provider counterpart implementation will be marked as deprecated.

  Permissions for backfill operations are now checked against the DagAccessEntity.Run permission using the existing requires_access_dag decorator. In other words, if a user has permission to run a Dag, they can perform backfill operations on it.

  Please update your security policies to ensure that users who need to perform backfill operations have the appropriate DagAccessEntity.Run permissions. (Users having the Backfill permissions without having the DagRun ones will no longer be able to perform backfill operations without any update)

  Python 3.14 support added

  Airflow 3.2.0 adds support for Python 3.14. (#63787)

  Reduce API server memory by eliminating SerializedDAG loads on task start

  The API server no longer loads the full SerializedDAG when starting tasks, significantly reducing memory usage. (#60803)

  Remove MySQL client from container images

  MySQL client support has been removed from official Airflow container images. MySQL users building on official images must install the client themselves. (#57146)

  Add support for async callables in PythonOperator

  The PythonOperator parameter python_callable now also supports async callables in Airflow 3.2, allowing users to run async def functions without manually managing an event loop. (#60268)

  Make start_date optional for @continuous schedule

  The schedule="@continuous" parameter now works without requiring a start_date, and any Dags with this schedule will begin running immediately when unpaused. (#61405)

  New Features

  • Add FIPS support by making Python LTO configurable via PYTHON_LTO build argument (#58337)
  • Add support for task queue-based Trigger assignment to specific Triggerer hosts via the new --queues CLI option for the trigger command (#59239)
  • Add --show-values and --hide-sensitive flags to CLI connections list and variables list to hide sensitive values by default (#62344)
  • Add support for setting individual secrets backend kwargs via AIRFLOW__SECRETS__BACKEND_KWARG__<KEY> environment variables (#63312)
  • Add only_new parameter to Dag clear to only clear newly added task instances (#59764)
  • Add log_timestamp_format config option for customizing component log timestamps (#63321)
  • Add --action-on-existing-key option to pools import and connections import CLI commands (#62702)
  • Add back --use-migration-files flag for airflow db init (#62234)
  • Add AllowedKeyMapper for partition key validation in asset partitioning (#61931)
  • Add ChainMapper for chaining multiple partition mappers (#64094)
  • Add cryptographic signature verification for Python source packages in Docker builds (#63345)
  • Add Human-to-the-Loop (HITL) Review system for AgenticOperator (#63081)
  • Add @task.stub decorator to allow tasks in other languages to be defined in Dags (#56055)
  • Add support for creating connections using URI in SDK (#62211)
  • Add note support to TriggerDagRunOperator (#60810)
  • Add allowed_run_types to whitelist specific Dag run types (#61833)
  • Add OR operator support in API search parameters (#60008)
  • Add API filtering for Dags by timetable type (#58852)
  • Add wildcard support for dag_id and dag_run_id in bulk task instance endpoint (#57441)
  • Add operator_name_pattern, pool_pattern, queue_pattern as task instance search filters (#57571)
  • Add update_mask support for bulk PATCH APIs (#54597)
  • Add asset event emission listener event (#61718)
  • Add source parameter to Param (#58615)
  • Add lazy filtering for inlet events by time range, ordering, and limit (#54891)
  • Add ability to get previous TaskInstance on RuntimeTaskInstance (#59712)
  • Add required context messages to all DagRun state change notifications (#56272)
  • Add max_trigger_to_select_per_loop config for Triggerer HA setup (#58803)
  • Add uvicorn_logging_level config option to control API server access logs (#56062)
  • Add correlation-id support to Execution API for request tracing (#57458)
  • Add executor.running_dags gauge metric to expose count of running Dags (#52815)
  • Add submodules support to GitDagBundle (#59911)
  • Add HTTP URL authentication support to GitHook for Dag bundles (#58194)
  • Add stream method to RemoteIO for ObjectStorage (#54813)
  • Add CLI hot-reload support via --dev flag (#57741)
  • Add auth list-envs command to list CLI environments and auth status (#61426)
  • Add Dag bundles to airflow info command output (#59124)
  • Add new arguments to db_clean to explicitly include or exclude Dags (#56663)
  • UI: Add Jobs page to the Airflow UI (#61512)
  • UI: Add version change indicators for Dag and bundle versions in Grid view (#53216)
  • UI: Add segmented state bar for collapsed task groups and mapped tasks (#61854)
  • UI: Add date range filter for Dag executions (#60772)
  • UI: Add "Select Recent Configurations" to trigger form, restoring Airflow 2 functionality (#56406)
  • UI: Add copy button to logs (#61185)
  • UI: Add filename display to Dag Code tab for easier file identification (#60759)
  • UI: Add Dag run state filter to grid view options (#55898)
  • UI: Add task upstream/downstream filter to Graph and Grid views (#57237)
  • UI: Add filters to Task Instances tab (#56920)
  • UI: Add display of active Dag runs count in header with auto-refresh (#58332)
  • UI: Add Dag ID pattern search to Dag Runs and Task Instances pages (#55691)
  • UI: Add delete button for Dag runs in more options menu (#55696)
  • UI: Add depth filter to TaskStreamFilter (#60549)
  • UI: Add theme config support (#58411)
  • UI: Add support for globalCss in custom themes (#61161)
  • UI: Add display of logged-in user in settings button (#58981)
  • UI: Add tooltip for explaining task filter traversal (#61401)
  • UI: Add self-service JWT token generation for API and CLI access (#63195)
  • UI: Add bulk operations for edge workers page (#64033)
  • UI: Add real-time concurrency control for edge workers (#63142)
  • UI: Add run_after date filter on Dag runs page (#62797)
  • UI: Add bundle version filter on Dag runs page (#62810)
  • UI: Add icon support for theme customization (#62172)
  • UI: Add Monaco editor for all JSON editing fields (#62708)
  • UI: Add run type legend tooltip to grid view (#62946)
  • UI: Allow customizing gray, black, and white color tokens in AIRFLOW__API__THEME in addition to brand (#64232)

  Bug Fixes

  • Fix sensitive configuration values not being masked in public config APIs; treat the deprecated non-sensitive-only value as True (#59880)
  • Fix InvalidStatsNameException for pool names with invalid characters by auto-normalizing them when emitting metrics (#59938)
  • Fix JWT tokens appearing in task logs by excluding the token field from workload object representations (#62964)
  • Fix security iframe navigation when AIRFLOW__API__BASE_URL basename is configured (#63141)
  • Fix grid view URL for dynamic task groups producing 404 by not appending /mapped to group URLs (#63205)
  • Fix ti_skip_downstream overwriting RUNNING tasks to SKIPPED in HA deployments (#63266)
  • Fix duplicate task execution when running multiple schedulers (#60330)
  • Fix callback starvation across Dag bundles (#63795)
  • Fix @task decorator failing for tasks that return falsy values like 0 or empty string (#63788)
  • Fix LatestOnlyOperator not working when direct upstream of a dynamically mapped task (#62287)
  • Fix inconsistent XCom return type in mapped task groups with dynamic mapping (#59104)
  • Fix task group lookup using wrong Dag version for historical runs, causing 404 errors in grid view (#63360)
  • Fix import errors when updating Dags in other bundles (#63615)
  • Fix DagRun span emission crash when context_carrier is None (#64087)
  • Fix false error logs for partitioned timetables when next_dagrun fields are None (#63962)
  • Fix timetable serialization error when decoding relativedelta (#61671)
  • Fix task_instance_mutation_hook receiving run_id=None during TaskInstance creation (#63049)
  • Fix scheduler crash on None dag_version access (#62225)
  • Fix MetastoreBackend.expunge_all() corrupting shared session state (#63080)
  • Fix triggerer logger file descriptor closed prematurely when trigger is removed (#62103)
  • Fix airflowignore negation pattern handling for directory-only patterns (#62860)
  • Fix false warnings for TYPE_CHECKING-only forward references in TaskFlow decorators (#63053)
  • Fix structlog JSON serialization crash on non-serializable objects (#62656)
  • Fix backward compatibility for deadline alert serialization (#63701)
  • Fix queued_tasks type mismatch in hybrid executors (CeleryKubernetesExecutor, LocalKubernetesExecutor) (#63744)
  • Fix Celery tasks not being registered at worker startup (#63110)
  • Fix asset partition detection incorrectly identifying Dags as partitioned (#62864)
  • Fix pathlib.Path objects incorrectly resolved by Jinja templater in Task SDK (#63306)
  • Fix state mismatch in Kubernetes executor after pod completion (#63061)
  • Fix make_partial_model for API Pydantic models (#63716)
  • Fix WTForms validator compatibility in connection form (#63823)
  • Fix _execution_api_server_url() ignoring configured value and falling back to edge config (#63192)
  • Fix DetachedInstanceError for airflow tasks render command (#63916)
  • Fix scheduler isolating per-dag-run failures to prevent a single DagRun crashing all scheduling (#62893)
  • Fix task argument order in @task definition causing Dag parsing errors (#62174)
  • Fix limit parameter not sent in execute_list server requests (#63048)
  • Fix circular import from airflow.configuration causing ImportError on Python 3.14 (#63787)
  • Fix map_index range validation in CLI commands (#62626)
  • Fix nullable ORM fields by restoring correct defaults and dropping unreleased corrective migration (#63899)
  • Fix race condition in auth manager initialization on concurrent requests (#62431)
  • Fix FabAuthManager race condition on startup with multiple workers (#62737)
  • Fix FabAuthManager race condition when workers concurrently create permissions, roles, and resources (#63842)
  • Fix JWTValidator not handling GUESS algorithm with JWKS (#63115)
  • Fix FabAuthManager first idle MySQL disconnect in token auth (#62919)
  • Fix JWTBearerTIPathDep import errors in Human-In-The-Loop routes (#63277)
  • Fix 403 from roles endpoint despite admin rights in FAB provider (#64097)
  • Fix task log filters not working in full-screen mode (#62747)
  • Fix duplicate log reads when resuming from log_pos (#63531)
  • Fix 404 errors from worker log server for historical retry attempts now handled gracefully (#62475)
  • Fix Elasticsearch/OpenSearch logging exception details missing in task log tab (#63739)
  • Fix task-level audit logs missing success/running events (#61932)
  • Fix null dag_run_conf causing serialization error in BackfillResponse (#63259)
  • Fix CLI asset materialization using wrong Dag run type (#63815)
  • Fix migration 0094 performance: use SQL instead of Python deserialization (#63628)
  • Fix migration reliability: replace savepoints with per-Dag transactions (#63591)
  • Fix slow downgrade performance by adding index to deadline.callback_id (#61236)
  • Fix MySQL reserved keyword interval causing query failures in deadline_alert (#63494)
  • Fix MySQL serialize_dag query failure during deadline migration (#63804)
  • Fix SQLite downgrade failures caused by FK constraints during batch table recreation (#63437)
  • Fix migration 0096 downgrade failing when team table has existing rows (#63449)
  • Fix missing warning about hardcoded 24h visibility_timeout that kills long-running Celery tasks (#62869)
  • Fix scheduler memory issue by removing eager loading of all task instances (#60956)
  • Fix MySQL sort buffer overflow in deadline alert migration (#61806)
  • Fix failing to manually trigger a Dag with CronPartitionedTimetable (#62441)
  • Fix race condition in AssetModel when updating asset partition DagRun — adds mutex lock (#59183)
  • Fix FAB auth_manager load_user causing PendingRollbackError (#61943)
  • Fix N+1 query: add joinedload for asset in dags_needing_dagruns() (#60957)
  • Fix Dag Processor health check threshold matching SchedulerJob/TriggererJob pattern (#58704)
  • Fix NotMapped exception when clearing task instances with downstream/upstream (#58922)
  • Fix missing asset events for partitioned DagRun (#61433)
  • Fix missing partition_key filter in PALK when creating DagRun (#61831)
  • Fix Dag params API contract broken by earlier change (#56831)
  • Fix OAuth session race condition causing false 401 errors during login (#61287)
  • Fix ObjectStoragePath to exclude conn_id from storage options passed to fsspec (#62701)
  • Fix unable to import list value for Variable (#61508)
  • Fix plugin registration returning early on duplicate names (#60498)
  • Fix circular import when using XComObjectStorageBackend (#55805)
  • Fix deadline alert hashing bug (#61702)
  • Fix task SDK to read default_email_on_failure/default_email_on_retry from config (#59912)
  • Fix Celery worker crash on macOS due to non-serializable local function (#62655)
  • Fix Redis import race condition in Celery executor (#61362)
  • Fix incorrect state query parameter for task instances in Dashboard (#59086)
  • Fix TaskInstance.get_dagrun returning None in task_instance_mutation_hook (#60726)
  • Fix Simple Auth Manager login showing cryptic error on failed authentication (#64303)
  • Fix dag_display_name property bypass for DagStats query (#64256)
  • Fix TaskAlreadyRunningError not raised when starting an already-running task instance (#60855)
  • Fix Teardown tasks not waiting for all in-scope tasks to complete (#64181)
  • Fix enable_swagger_ui config not respected in API server (#64376)
  • Fix: add check for xcom permission when result is specified for DagRun wait endpoint (#64415)
  • Fix conf.has_option not respects default provider metadata (#64209)
  • Fix teardown scope causing unnecessary database writes during task scheduling (#64558)
  • Fix live task log output not visible in stdout when using Elasticsearch log forwarding (#64067)
  • Fix TaskInstance crash when refreshing task weight for non-serialized operators (#64557)
  • Fix Variables secrets backend conflict check exiting early when multiple backends are configured (#64062)
  • UI: Fix Dag run accessor key on clear task instance page (#64072)
  • UI: Fix searchable dropdown not working for Dag params enum fields (#63895)
  • UI: Fix newline rendering in Dag warning alert (#63588)
  • UI: Fix XCom edit modal value not repopulating on reopen (#62798)
  • UI: Fix task duration tooltip not displaying correctly (#63639)
  • UI: Fix elapsed time not showing for running tasks (#63619)
  • UI: Fix RenderedJsonField collapse behavior (#63831)
  • UI: Fix RenderedJsonField not displaying in table cells (#63245)
  • UI: Fix full-screen log dropdown z-index after Chakra upgrade (#63816)
  • UI: Fix asset materialization run type display (#63819)
  • UI: Fix pools with unlimited (-1) slots not rendering correctly (#62831)
  • UI: Fix DurationChart labels and disable animation flicker during auto-refresh (#62835)
  • UI: Fix 403 error not shown when unauthorized user re-parses Dag (#61560)
  • UI: Fix logical date filter on /dagruns page not working (#62848)
  • UI: Fix inflated total_received count in partitioned Dag runs view (#62786)
  • UI: Fix edge executor navigation when behind reverse proxy with subpath (#63777)
  • UI: Fix queries not invalidated on Dag run add/delete (#64269)
  • UI: Fix RenderedJsonField flickering when collapsed (#64261)
  • UI: Fix Docs menu REST API link visibility when API docs are disabled (#64359)
  • UI: Fix TISummaries not refreshing when gridRuns are invalidated (#64113)
  • UI: Fix guard against null/undefined dates in Gantt chart to prevent RangeError (#64031)
  • UI: Block polling requests to endpoints that returned 403 Forbidden (#64333)
  • UI: Fix Gantt view still visible when time range is outside DagRun window (#64179)
  • UI: Fix Human-in-the-Loop (HITL) operator options not displaying when exactly 4 choices are configured (#64453)

  Miscellaneous

  • Deprecate api.page_size config in favor of api.fallback_page_limit (#61067)
  • Improve Dag callback relevancy by passing a context-relevant task instance based on the Dag's final state instead of an arbitrary lexicographical selection (#61274)
  • Optimize get_dag_runs API endpoint performance (#63940)
  • Improve historical metrics endpoint performance (#63526)
  • Add TTL cache with single-flight deduplication to Keycloak filter_authorized_dag_ids (#63184)
  • Reduce Celery worker memory usage with gc.freeze (#62212)
  • Eliminate duplicate JOINs in get_task_instances endpoint (#62910)
  • Replace large IN clause in asset queries with CTE and JOIN for better SQL performance (#62114)
  • Add row lock to prevent race conditions during asset-triggered DagRun creation (#60773)
  • Add ConnectionResponse serializer safeguard to prevent accidental sensitive field exposure (#63883)
  • Add missing dag_id filter on DagRun task instances API query (#62750)
  • Add missing HTTP timeout to FAB JWKS fetching (#63058)
  • Add additional permission check in asset materialization endpoint (#63338)
  • Filter backfills list by readable Dags (authorization enforcement) (#63003)
  • Hide SQL statements in exception details when expose_stacktrace is disabled (#63028)
  • Use default max depth to redact Variable values in API responses (#63480)
  • Validate update_mask fields in PATCH API endpoints against Pydantic models (#62657)
  • Align key/id path validation for variables and connections in Execution API (#63897)
  • Add order_by parameter to GET /permissions endpoint for pagination consistency (#63418)
  • Implement truncation logic for rendered template values (#61878)
  • Add BaseXcom to airflow.sdk public exports (#63116)
  • Make TaskSDK conf respect default config from provider metadata (#62696)
  • Add OTel trace import shim via airflow.sdk.observability.trace (#63554)
  • Improve 3.2.0 deadline migration performance (#63920)
  • Improve 3.2.0 downgrade migration for external_executor_id on PostgreSQL (#63625)
  • Skip backfilling old DagRun.created_at during migration for faster upgrades (#63825)
  • Add INFO-level logging to asset scheduling path (#63958)
  • Improve log file template for ExecuteCallback by including dag_id and run_id (#62616)
  • Improve Dag processor timeout logging clarity (#62328)
  • Deprecate get_connection_form_widgets and get_ui_field_behaviour hook methods (#63711)
  • Add missing deprecation warnings for [workers] config section (#63659)
  • Expose TaskInstance API for external task management (#61568)
  • Remove deprecated airflow.datasets, airflow.timetables.datasets, and airflow.utils.dag_parsing_context modules (#62927)
  • Remove PyOpenSSL from core dependencies (#63869)
  • Optimize fail-fast check to avoid loading SerializedDAG (#56694)
  • Improve performance of task queue processing by switching from pop(0) to popleft() (#61376)
  • Optimize K8s API usage for watching pod events, fixing hanging communication (#59080)
  • Remove N+1 database queries for team names (#61471)
  • Improve XCom value handling in extra links API (#61641)
  • Remove .git folder from versions in GitDagBundle to reduce storage size (#57069)
  • Deprecate subprocess exec utils from airflow.utils.process_utils (#57193)
  • Improve error handling in edge worker on 405 responses (#60425)
  • Improve deferrable KubernetesPodOperator handling of deleted pods between polls (#56976)
  • Improve event log entries when a pod fails for K8s executor (#60800)
  • Refactor XCom API to use shared serialization constants (#64148)
  • Improve temporal mapper to be timezone aware for asset partitioning (#62709)
  • Improve dag version inflation checker logic and fix false-positive detection (#61345)
  • Rename ToXXXMapper to StartOfXXXMapper in partition-mapper for clarity (#64160)
  • Run DB check only for core components in prod entrypoint (#63413)
  • Fix partitioned asset events incorrectly triggering non-partition-aware Dags (#63848)
  • Improve partitioned DagRun sorting by partition_date (#62866)
  • Allow gray, black, and white color tokens in AIRFLOW__API__THEME config (#64232)
  • Add parent task spans and nest worker/trigger spans for improved observability (#63839)
  • UI: Enhance code view to support search and diff (#55467)
  • UI: Improve UX for adding custom DeadlineReferences (#57222)
  • UI: Enhance FilterBar with DateRangeFilter for compact UI (#56173)
  • UI: Move deadline alerts into their own table for UI integration (#58248)
  • UI: Persist tag filter selection in Dag grid view (#63273)
  • UI: Show HITL review tab only for review-enabled task instances (#63477)
  • UI: Updated button styles for adding Connections, Variables, and Pools (#62607)
  • UI: Add clear permission toast for 403 errors on user actions (#61588)

  Doc Only Changes

  • Add documentation marking pre/post-execute task hooks as GA (no longer experimental) (#59656)
  • Add RedisTaskHandler configuration example (#63898)
  • Add documentation explaining difference between deferred vs async operators (#63500)
  • Add auth manager section in multi-team documentation (#63208)
  • Add documentation about shared libraries in _shared folders (#63468)
  • Clarify plugin folder module registration in modules_management docs (#63634)
  • Clarify max_active_tasks Dag parameter documentation (#63217)
  • Clarify HLL in extraction precedence docs (#63723)
  • Clarify Ubuntu/Debian venv requirement in quick start guide (#63244)
  • Fix Git connection docs to match actual GitHook parameters (#63265)
  • Mention Python 3.14 support in docs (#63950)
  • Add Dag documentation for example_bash_decorator (#62948)
  • Add Russian translation for UI (#63450)
  • Add Hungarian translation (#62925)
  • Complete Traditional Chinese translations (#62652)
  • Add asset partition documentation (#63262)
  • Add guide for dag version inflation and its checker (#64100)

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• Apr 7, 2026

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  Airflow by Apache

  task-sdk/1.2.0

  Airflow releases Task SDK 1.2.0.

  Airflow Task SDK 1.2.0

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• Apr 7, 2026

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  Airflow by Apache

  Apache Airflow 3.2.0: Data-Aware Workflows at Scale

  Airflow releases 3.2.0 with Asset partitioning for granular pipeline orchestration, experimental multi-team deployments, synchronous deadline alert callbacks, UI and performance improvements, and continued Task SDK separation.

  Apache Airflow 3.2.0 introduces Asset partitioning for granular pipeline orchestration, multi-team deployments for enterprise scale, synchronous deadline alert callbacks, and continued progress toward full Task SDK separation.

  We’re proud to announce the release of Apache Airflow 3.2.0! Airflow 3.1 puts humans at the center of automated workflows. 3.2 brings that same precision to data: Asset partitioning for granular pipeline orchestration, multi-team deployments for enterprise scale, synchronous deadline alert callbacks, and continued progress toward full Task SDK separation.

  Details

  • 📦 PyPI: https://pypi.org/project/apache-airflow/3.2.0/
  • 📚 Docs: https://airflow.apache.org/docs/apache-airflow/3.2.0/
  • 🛠️ Release Notes: https://airflow.apache.org/docs/apache-airflow/3.2.0/release_notes.html
  • 🐳 Docker Image: docker pull apache/airflow:3.2.0
  • 🚏 Constraints: https://github.com/apache/airflow/tree/constraints-3.2.0

  🗂️ Asset Partitioning (AIP-76): Only the Right Work Gets Triggered

  Asset partitioning has been one of the most requested additions to data-aware scheduling. If you work with date-partitioned S3 paths, Hive table partitions, BigQuery partitions, or really any partitioned data store, you’ve dealt with this: An upstream task updates one partition, and every downstream Dag fires regardless of which slice actually changed. It’s wasteful, and for large deployments it creates real operational noise.

  Asset partitioning in 3.2 makes this granular. Downstream Dags trigger only when the specific partition they care about gets updated. It’s the biggest change to data-aware scheduling since Assets were introduced, and it turns partition-driven orchestration into something Airflow handles natively rather than something you work around.

  Key Capabilities

  • Partition-driven scheduling: Dags trigger on specific partition updates, not every asset change
  • CronPartitionTimetable: Schedule Dags against partitions using cron expressions. Also available in the Task SDK
  • Backfill for partitioned Dags: Backfill historical partitions without re-triggering everything downstream (#61464)
  • Multi-asset partitions: A single Dag can listen for partitions across multiple assets, which matters when your downstream work depends on several sources aligning (#60577)

  For more advanced use cases, there are temporal and range partition mappers (#61522, #55247) for mapping time ranges and value ranges to partition keys, a partition key field on Dag run references (#61725) so you can inspect exactly which partition triggered a run, and PartitionedAssetTimetable for full control over how partition events from multiple assets get resolved into a unified trigger.

  Example: Three upstream ingestion Dags each write to a separate asset on an hourly cadence. The downstream Dag only triggers when all three have updated the same hourly partition. Since the three assets don’t share a partition key natively, a mapper resolves them into a common key.

  🏢 Multi-Team Deployments (AIP-67): Airflow for the Enterprise

  ⚠️ Experimental: Multi-Team support is experimental in Airflow 3.2 and may change in future releases based on user feedback.

  Airflow 3.2 introduces multi-team support, allowing organizations to run multiple isolated teams within a single Airflow deployment. Each team can have its own Dags, connections, variables, pools, and executors— enabling true resource and permission isolation without requiring separate Airflow instances per team.

  This is particularly valuable for platform teams that serve multiple data engineering or data science teams from shared infrastructure, while maintaining strong boundaries between teams’ resources and access.

  Key Capabilities

  • Per-team resource isolation: Each team has its own Dags, connections, variables, and pools
  • Per-team executors: Different teams can use different executors (e.g. Celery, Kubernetes, Local, AWS ECS, etc.) and configure them separately — #57837, #57910
  • Team-scoped authorization: Keycloak and Simple auth managers support team-scoped access control (#61351, #61861)
  • Team-scoped secrets: Use AIRFLOW_VAR__{TEAM}{KEY} environment variable or AIRFLOW_CONN__ pattern for team-specific secrets (#62588)
  • CLI management: New CLI commands for managing teams (#55283)
  • UI team selector: Team selector in connection, variable, and pool create/edit forms (#60237, #60474, #61082)
  • Full API support: team_name field added to Connection, Variable, and Pool APIs (#59336, #57102, #60952)

  Enabling Multi-Team

  In airflow.cfg: [core] multi_team = True
  Or via environment variable: export AIRFLOW__CORE__MULTI_TEAM=True

  ⏰ Deadline Alerts: Now With Synchronous Callbacks (AIP-86)

  ⚠️ Experimental: Deadline Alerts are experimental in Airflow 3.2 and may change in future releases based on user feedback.

  Building on the Deadline Alerts system introduced in Airflow 3.1, this release adds synchronous callback support. In 3.1, callbacks ran through the triggerer (async only), which limited integration options. Synchronous callbacks execute directly via the executor, with optional targeting of a specific executor via the executor parameter.

  What’s New in 3.2

  • SyncCallback support: Unlike AsyncCallback which runs on the triggerer, SyncCallback executes directly on the worker via the executor, with optional targeting of a specific executor
  • Multiple Deadline Alerts per Dag: Pass a list to the deadline parameter to configure multiple thresholds on a single Dag
  • Missed-deadline metadata in Grid API: Dag run API now includes missed-deadline information for programmatic monitoring
  • Improved UX for custom DeadlineReferences: Cleaner developer experience when defining custom deadline reference points (#57222)

  🖥️ UI Enhancements

  • HITL Approval History: The Human-in-the-Loop approval interface now shows the complete audit trail of approvals and rejections for any task. (#56760, #55952)
  • XCom Management: You can now add, edit, and delete XCom values directly from the UI. (#58921)
  • Segmented state bar: Collapsed task groups and mapped tasks now show a segmented state bar for at-a-glance status (#61854)
  • Unified tooltips: Grid and Graph view tooltips now show dates, duration, and child states (#62119)
  • Filename in Dag Code tab: File identification now shown in the Code tab (#60759)
  • Copy button for logs: One-click log copying (#61185)
  • Date range filter: Filter Dag executions by date range (#60772)
  • Task upstream/downstream filter: Filter by upstream or downstream tasks in Graph and Grid views (#57237)
  • Data redaction: Sensitive fields are now redacted in the UI and Public API (#59873)
  • Custom theme support: globalCss and theme config for white-label/custom deployments (#61161, #58411)
  • Inherit core UI theme in React plugins: Plugin UIs now automatically match the core Airflow theme (#60256)
  • Task display names in Gantt: task_display_name shown for better readability (#61438)

  🚀 Performance Improvements

  Rendered Task Instance Fields Cleanup: ~42x Faster.

  The cleanup job for rendered task instance fields has been rewritten and is roughly 42 times faster for Dags with many mapped tasks. Retention is now based on the N most recent Dag runs rather than N most recent task executions, which is both more intuitive and dramatically more performant. Config renamed: max_num_rendered_ti_fields_per_task → num_dag_runs_to_retain_rendered_fields (old name still works with deprecation warning). (#60951)

  Scheduler Improvements.

  For large-scale deployments, 3.2 addresses several known bottlenecks:

  • The scheduler no longer loads all TaskInstances into memory, preventing memory spikes on large deployments (#60956)
  • Faster task dequeuing loop (#61376)
  • Queue query now enforces max_active_tasks directly, preventing over-queueing (#54103)

  API Server Improvements:

  • Eliminated SerializedDag loads on task start, reducing memory usage (#60803)
  • serialized_dag data column now uses JSONB on PostgreSQL (#55979)

  🔧 Task SDK Evolution & Developer Experience

  Task SDK Decoupling Continues

  Airflow 3.2 continues moving components from airflow-core into the Task SDK, progressing toward full client-server separation. This enables Dag authors to independently upgrade the Task SDK without requiring Airflow Core upgrades, reducing coordination overhead between Dag authors and Ops teams.

  Modules moved to Task SDK in this release (old import paths still work with deprecation warnings):

  • Exceptions: AirflowSkipException, TaskDeferred, etc. → airflow.sdk.exceptions (#59780)
  • Serde: airflow.serialization.serde → airflow.sdk.serde; serializers → airflow.sdk.serde.serializers.* (#58900)
  • SkipMixin / BranchMixIn: Moved to Task SDK; existing imports work via common-compat (#62749, #62776)
  • Lineage module: Moved to Task SDK for client-server separation (#60968, #61157)
  • Listeners module: Moved to shared library (#59883)
  • XCom API: Decoupled from XComEncoder (#58900)

  PythonOperator Async Support

  PythonOperator now supports async callables. You can pass an async function as the python_callable and the operator will correctly await it, enabling async I/O patterns without needing a custom operator. (#60268)

  Updated securiy model

  We are working on improving isolation and improving security of Airflow deployments and in order to make our users better informed of what expectations they should have for Airflow security, we updated the security model to reflect changes implemented in Airflow 3.2.0 and explain future improvements that we work on in this area. See more: Airflow Security Model.

  🙏 Community Appreciation

  This release represents the collaborative effort of hundreds of contributors from around the world. Special thanks to our release manager and all the developers, documentarians, testers, and community members who made Airflow 3.2.0 possible.

  Thanks to contributors like you, the Airflow project continues to thrive. Whether you’re filing issues, submitting PRs, improving documentation, or helping others in the community, every contribution matters.

  🔗 Get Involved

  • Try the Release: Upgrade your development environment and explore the new features
  • Join the Conversation: Connect with us on Slack and the dev mailing list
  • Contribute: Check out our contribution guide
  • Provide Feedback: Share your experiences and suggestions on GitHub

  Apache Airflow 3.2.0 marks a new chapter in data-aware, partition-driven workflow orchestration. We can’t wait to see what you build with it!

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  Airflow by Apache

  constraints-latest

  Airflow updates the latest constraints set to Apache Airflow 3.2.0.

  Latest constraints set to Apache Airflow 3.2.0

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• Apr 3, 2026

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  Airflow by Apache

  3.2.0rc2

  Airflow ships Apache Airflow 3.2.0rc2 release candidate.

  Apache Airflow 3.2.0rc2

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• Apr 3, 2026

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  Airflow by Apache

  task-sdk/1.2.0rc2

  Airflow ships Task SDK 1.2.0rc2.

  Airflow Task SDK 1.2.0rc2

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• Apr 3, 2026

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    Apr 3, 2026
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    Mar 31, 2026
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  Airflow by Apache

  constraints-3.2.0rc2

  Airflow adds constraints for Apache Airflow 3.2.0rc2.

  Constraints for Apache Airflow 3.2.0rc2

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• Mar 30, 2026

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  Airflow by Apache

  3.2.0rc1

  Airflow ships 3.2.0rc1 release candidate.

  Apache Airflow 3.2.0rc1

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• Mar 29, 2026

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  Superset by Apache

  Mobile agents, SOC 2 pen test passed, and theme marketplace

  Superset releases a mobile-first agents experience, a new theme marketplace, and security hardening after passing its independent penetration test and SOC 2 requirements. It also adds usability upgrades and fixes across workspaces, chat, terminals, and editing.

  Mobile Agents Experience (WIP) #2595

  Mobile Agents Experience (WIP)

  We're building out a mobile-first agents experience in the web app. This is still a work in progress, but you can already browse, start, and monitor agents from your phone with an interface designed for smaller screens. More to come here.

  SOC 2 Compliance & Pen Test Passed

  The big news this week: Superset now passes its independent penetration test and meets SOC 2 compliance requirements. We shipped a round of security hardening based on findings from the pen test. This is a major milestone for teams that need enterprise-grade security assurances.

  Theme Marketplace #2966

  Theme Marketplace

  Browse and install themes from the new theme marketplace. When your system is set to auto mode, you can now independently configure which theme is used for light and dark #2557.

  Improvements

  • Open in editor from worktrees - Jump straight from a worktree into your external editor #2999
  • Cmd-click file paths - File paths in chat or output can be Cmd-clicked to open in your editor #2903
  • New workspace modal UX - Cleaner layout with icon buttons and server-side PR search #2980 #2909
  • Close workspace hotkey - Cmd+W to close a workspace #2907
  • Settings search indicator - Visual indicator when a search filter is active in settings #2997
  • Terminal flow control - Hardened backlog and flow control to prevent output drops under heavy load #3006

  Bug fixes

  • Fixed PTY spawn failure leaving zombie sessions that blocked new terminals #2963
  • Batched PTY output to prevent bun dev crashes in terminal #3001
  • Preserved chat cursor position #2993
  • Restored Codex loading state #2998
  • Fixed workspace search regressions #2979
  • Honored linked PR push targets #2977
  • Fixed worktree deletion #2929
  • Removed spurious terminal backpressure warning #2996
  • Restored native text editing shortcuts in chat #2676

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• Mar 28, 2026

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  Airflow by Apache

  python-client/3.1.8

  Airflow ships Python Client 3.1.8.

  Airflow Python Client 3.1.8

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