[Yandex Cloud documentation](../../index.md) > [Monium](../index.md) > [Metrics](../metrics/overview.md) > [Metric reference](index.md) > Managed Service for Apache Airflow™ # Yandex Managed Service for Apache Airflow™ metrics This section describes [Managed Service for Apache Airflow™](../../managed-airflow/index.md) metrics delivered to Monium.Metrics. The `name` label contains the metric name. Labels shared by all Managed Service for Apache Airflow™ metrics: Label | Value ----|---- service | Service ID: `managed-airflow` cluster_id | [Cluster](../../managed-airflow/concepts/index.md#cluster) ID Service metrics: Name
Type, units | Description
Labels ----|---- `airflow.dag_processing.file_path_queue_size_value`
`GAUGE`, count | Number of DAG files to include in the next scan `airflow.dag_processing.file_path_queue_update_count.value`
`COUNTER`, count | Number of file system scans that resulted in all existing DAGs being enqueued. `airflow.dag_processing.import_errors.value`
`GAUGE`, count | Number of DAG file parsing errors `airflow.dag_processing.total_parse_time.value`
`GAUGE`, seconds | Time taken to scan and import all DAG files to include the next scan `airflow.dagbag_size.value`
`GAUGE`, count | Number of DAG files found in the latest DAGBag scan based on scheduler configuration `airflow.dataset.orphaned.value`
`GAUGE`, count | Number of datasets labeled as orphans since they are no longer linked to DAG schedule parameters or task outputs. `airflow.job_start.value`
`COUNTER`, count | Number of runs of different types of tasks, such as `SchedulerJob`, `LocalTaskJob`, etc. `airflow.pool.deferred_slots.default_pool.value`
`GAUGE`, count | Number of deferred slots in default pools `airflow.pool.deferred_slots.value`
`GAUGE`, count | Number of deferred slots in all pools.
This metric features the `pool_name` label containing the pool name. `airflow.pool.open_slots.default_pool.value`
`GAUGE`, count | Number of open slots in default pools `airflow.pool.open_slots.value`
`GAUGE`, count | Number of open slots in all pools.
This metric features the `pool_name` label containing the pool name. `airflow.pool.queued_slots.default_pool.value`
`GAUGE`, count | Number of queued slots in default pools `airflow.pool.queued_slots.value`
`GAUGE`, count | Number of queued slots in all pools.
This metric features the `pool_name` label containing the pool name. `airflow.pool.running_slots.default_pool.value`
`GAUGE`, count | Number of running slots in default pools `airflow.pool.running_slots.value`
`GAUGE`, count | Number of running slots in all pools.
This metric features the `pool_name` label containing the pool name. `airflow.scheduler.critical_section_duration.50_percentile`
`TIMING`, milliseconds | Time spent on the critical section of the scheduler loop^1^, 50th percentile `airflow.scheduler.critical_section_duration.95_percentile`
`TIMING`, milliseconds | Time spent on the critical section of the scheduler loop^1^, 95th percentile `airflow.scheduler.critical_section_duration.99_percentile`
`TIMING`, milliseconds | Time spent on the critical section of the scheduler loop^1^, 99th percentile `airflow.scheduler.critical_section_duration.count`
`TIMING`, count | Number of time measurements for the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_duration.lower`
`TIMING`, milliseconds | Minimum time spent on the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_duration.mean`
`TIMING`, milliseconds | Average time spent on the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_duration.median`
`TIMING`, milliseconds | Median time spent on the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_duration.stddev`
`TIMING`, milliseconds | Standard deviation of the time spent on the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_duration.sum`
`TIMING`, milliseconds | Total time spent on the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_duration.upper`
`TIMING`, milliseconds | Maximum time spent on the critical section of the scheduler loop^1^ `airflow.scheduler.critical_section_query_duration.50_percentile`
`TIMING`, milliseconds | Time spent running a query in the critical section^1^, 50th percentile `airflow.scheduler.critical_section_query_duration.95_percentile`
`TIMING`, milliseconds | Time spent running a query in the critical section^1^, 95th percentile `airflow.scheduler.critical_section_query_duration.99_percentile`
`TIMING`, milliseconds | Time spent running a query in the critical section^1^, 99th percentile `airflow.scheduler.critical_section_query_duration.count`
`TIMING`, count | Number of query run time measurements in the critical section^1^ `airflow.scheduler.critical_section_query_duration.lower`
`TIMING`, milliseconds | Minimum time spent running a query in the critical section^1^ `airflow.scheduler.critical_section_query_duration.mean`
`TIMING`, milliseconds | Average time spent running a query in the critical section^1^ `airflow.scheduler.critical_section_query_duration.median`
`TIMING`, milliseconds | Median time spent running a query in the critical section^1^ `airflow.scheduler.critical_section_query_duration.stddev`
`TIMING`, milliseconds | Standard deviation of the time spent running a query in the critical section^1^ `airflow.scheduler.critical_section_query_duration.sum`
`TIMING`, milliseconds | Total time spent running a query in the critical section^1^ `airflow.scheduler.critical_section_query_duration.upper`
`TIMING`, milliseconds | Maximum time spent running a query in the critical section^1^ `airflow.scheduler.heartbeat.value`
`COUNTER`, count | Number of heartbeat messages from the scheduler indicating its active state `airflow.scheduler.load_serializers.50_percentile`
`TIMING`, milliseconds | Time spent serializing data in the scheduler^2^, 50th percentile `airflow.scheduler.load_serializers.95_percentile`
`TIMING`, milliseconds | Time spent serializing data in the scheduler^2^, 95th percentile `airflow.scheduler.load_serializers.99_percentile`
`TIMING`, milliseconds | Time spent serializing data in the scheduler^2^, 99th percentile `airflow.scheduler.load_serializers.count`
`TIMING`, count | Number of time measurements for data serialization in the scheduler^2^ `airflow.scheduler.load_serializers.lower`
`TIMING`, milliseconds | Minimum time spent serializing data in the scheduler^2^ `airflow.scheduler.load_serializers.mean`
`TIMING`, milliseconds | Average time spent serializing data in the scheduler^2^ `airflow.scheduler.load_serializers.median`
`TIMING`, milliseconds | Median time spent serializing data in the scheduler^2^ `airflow.scheduler.load_serializers.stddev`
`TIMING`, milliseconds | Standard deviation of the time spent serializing data in the scheduler^2^ `airflow.scheduler.load_serializers.sum`
`TIMING`, milliseconds | Total time spent serializing data in the scheduler^2^ `airflow.scheduler.load_serializers.upper`
`TIMING`, milliseconds | Maximum time spent serializing data in the scheduler^2^ `airflow.scheduler.orphaned_tasks.adopted.value`
`COUNTER`, count | Number of tasks adopted by the scheduler that were marked as orphans. `airflow.scheduler.orphaned_tasks.cleared.value`
`COUNTER`, count | Number of tasks cleared by the scheduler that were marked as orphans. `airflow.scheduler.scheduler_loop_duration.50_percentile`
`TIMING`, milliseconds | Time spent running one scheduler loop, 50th percentile `airflow.scheduler.scheduler_loop_duration.95_percentile`
`TIMING`, milliseconds | Time spent running one scheduler loop, 95th percentile `airflow.scheduler.scheduler_loop_duration.99_percentile`
`TIMING`, milliseconds | Time spent running one scheduler loop, 99th percentile `airflow.scheduler.scheduler_loop_duration.count`
`TIMING`, count | Number of time measurements for one scheduler loop `airflow.scheduler.scheduler_loop_duration.lower`
`TIMING`, milliseconds | Minimum time spent running one scheduler loop `airflow.scheduler.scheduler_loop_duration.mean`
`TIMING`, milliseconds | Average time spent running one scheduler loop `airflow.scheduler.scheduler_loop_duration.median`
`TIMING`, milliseconds | Median time spent running one scheduler loop `airflow.scheduler.scheduler_loop_duration.stddev`
`TIMING`, milliseconds | Standard deviation of time spent running one scheduler loop `airflow.scheduler.scheduler_loop_duration.sum`
`TIMING`, milliseconds | Total time spent running one scheduler loop `airflow.scheduler.scheduler_loop_duration.upper`
`TIMING`, milliseconds | Maximum time spent running one scheduler loop `airflow.scheduler.tasks.executable.value`
`GAUGE`, count | Number of tasks that are ready to run based on pool limitations, DAG concurrency, worker status, and priority levels. `airflow.scheduler.tasks.starving.value`
`GAUGE`, count | Number of tasks that cannot be scheduled due to no free slots in the pool. `CeleryExecutor`
`GAUGE`, count | Number of [Celery](https://docs.celeryq.dev/en/main/index.html) workers at different task running stages.
The `status` label value means the number of workers with the following statuses: ^1^ Only a single scheduler can enter this loop at a time. ^2^ Data serialization for exchange between tasks and for web server and scheduler security.