Yandex Monitoring metric reference

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Updated at October 1, 2024

This section describes Managed Service for Apache Airflow™ metrics delivered to Monitoring.

The metric name is written to the name label.

Common labels for all Managed Service for Apache Airflow™ metrics:

Label	Value
service	Service ID: `managed-airflow`
cluster_id	Cluster ID

Service metrics:

Name Type, units	Description Labels
`airflow.dag_processing.file_path_queue_size_value` `GAUGE,` number	Number of DAG files that will be considered in the next scan.
`airflow.dag_processing.file_path_queue_update_count.value` `COUNTER,` number	Number of times the file system was scanned and all existing DAGs were added to the queue.
`airflow.dag_processing.import_errors.value` `GAUGE,` number	Number of errors when trying to parse DAG files.
`airflow.dag_processing.total_parse_time.value` `GAUGE,` seconds	The time it took to scan and import all DAG files that will be included in the next scan.
`airflow.dagbag_size.value` `GAUGE,` number	Number of DAG files found in the last DAGBag scan by scheduler configuration.
`airflow.dataset.orphaned.value` `GAUGE,` number	Number of datasets that were marked as orphans because they no longer link to DAG schedule parameters or task outputs.
`airflow.job_start.value` `COUNTER`, number	Number of runs of different types of tasks such as `SchedulerJob`, `LocalTaskJob`, etc.
`airflow.pool.deferred_slots.default_pool.value` `GAUGE,` number	Number of deferred slots in default pools.
`airflow.pool.deferred_slots.value` `GAUGE,` number	Number of deferred slots in all pools. `pool_name` label: Pool name.
`airflow.pool.open_slots.default_pool.value` `GAUGE,` number	Number of open slots in default pools.
`airflow.pool.open_slots.value` `GAUGE,` number	Number of open slots in all pools. `pool_name` label: Pool name.
`airflow.pool.queued_slots.default_pool.value` `GAUGE,` number	Number of queued slots in default pools.
`airflow.pool.queued_slots.value` `GAUGE,` number	Number of queued slots in all pools. `pool_name` label: Pool name.
`airflow.pool.running_slots.default_pool.value` `GAUGE,` number	Number of running slots in default pools.
`airflow.pool.running_slots.value` `GAUGE,` number	Number of running slots in all pools. `pool_name` label: Pool name.
`airflow.scheduler.critical_section_duration.50_percentile` `TIMING,` milliseconds	Time spent on the critical section of the scheduler loop¹. 0.5 percentile.
`airflow.scheduler.critical_section_duration.95_percentile` `TIMING,` milliseconds	Time spent on the critical section of the scheduler loop¹. 0.95 percentile.
`airflow.scheduler.critical_section_duration.99_percentile` `TIMING,` milliseconds	Time spent on the critical section of the scheduler loop¹. 0.99 percentile.
`airflow.scheduler.critical_section_duration.count` `TIMING,` number	Number of measurements of time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_duration.lower` `TIMING,` milliseconds	Minimum time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_duration.mean` `TIMING,` milliseconds	Average time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_duration.median` `TIMING,` milliseconds	Median time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_duration.stddev` `TIMING,` milliseconds	Standard deviation of time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_duration.sum` `TIMING,` milliseconds	Total time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_duration.upper` `TIMING,` milliseconds	Maximum time spent on the critical section of the scheduler loop¹.
`airflow.scheduler.critical_section_query_duration.50_percentile` `TIMING,` milliseconds	Time spent to execute a query in the critical section¹. 0.5 percentile.
`airflow.scheduler.critical_section_query_duration.95_percentile` `TIMING,` milliseconds	Time spent to execute a query in the critical section¹. 0.95 percentile.
`airflow.scheduler.critical_section_query_duration.99_percentile` `TIMING,` milliseconds	Time spent to execute a query in the critical section¹. 0.99 percentile.
`airflow.scheduler.critical_section_query_duration.count` `TIMING,` number	Number of measurements of the time spent to execute a query in the critical section¹.
`airflow.scheduler.critical_section_query_duration.lower` `TIMING,` milliseconds	Minimum time spent to execute a query in the critical section¹.
`airflow.scheduler.critical_section_query_duration.mean` `TIMING,` milliseconds	Average time spent to execute a query in the critical section¹.
`airflow.scheduler.critical_section_query_duration.median` `TIMING,` milliseconds	Median time spent to execute a query in the critical section¹.
`airflow.scheduler.critical_section_query_duration.stddev` `TIMING,` milliseconds	Standard deviation of the time spent to execute a query in the critical section¹.
`airflow.scheduler.critical_section_query_duration.sum` `TIMING,` milliseconds	Total time spent to execute a query in the critical section¹.
`airflow.scheduler.critical_section_query_duration.upper` `TIMING,` milliseconds	Maximum time spent to execute a query in the critical section¹.
`airflow.scheduler.heartbeat.value` `COUNTER,` number	Number of heartbeat messages from the scheduler indicating its activity.
`airflow.scheduler.load_serializers.50_percentile` `TIMING,` milliseconds	Time spent serializing data in the scheduler². 0.5 percentile.
`airflow.scheduler.load_serializers.95_percentile` `TIMING,` milliseconds	Time spent serializing data in the scheduler². 0.95 percentile.
`airflow.scheduler.load_serializers.99_percentile` `TIMING,` milliseconds	Time spent serializing data in the scheduler². 0.99 percentile.
`airflow.scheduler.load_serializers.count` `TIMING,` number	Number of measurements of time spent serializing data in the scheduler².
`airflow.scheduler.load_serializers.lower` `TIMING,` milliseconds	Minimum time spent serializing data in the scheduler².
`airflow.scheduler.load_serializers.mean` `TIMING,` milliseconds	Average time spent serializing data in the scheduler².
`airflow.scheduler.load_serializers.median` `TIMING,` milliseconds	Median time spent serializing data in the scheduler².
`airflow.scheduler.load_serializers.stddev` `TIMING,` milliseconds	Standard deviation of time spent serializing data in the scheduler².
`airflow.scheduler.load_serializers.sum` `TIMING,` milliseconds	Total time spent serializing data in the scheduler².
`airflow.scheduler.load_serializers.upper` `TIMING,` milliseconds	Maximum time spent serializing data in the scheduler².
`airflow.scheduler.orphaned_tasks.adopted.value` `COUNTER,` number	Number of tasks adopted by the scheduler that were marked as orphans.
`airflow.scheduler.orphaned_tasks.cleared.value` `COUNTER,` number	Number of tasks cleared by the scheduler that were marked as orphans.
`airflow.scheduler.scheduler_loop_duration.50_percentile` `TIMING,` milliseconds	Time spent to execute one scheduler loop. 0.5 percentile.
`airflow.scheduler.scheduler_loop_duration.95_percentile` `TIMING,` milliseconds	Time spent to execute one scheduler loop. 0.95 percentile.
`airflow.scheduler.scheduler_loop_duration.99_percentile` `TIMING,` milliseconds	Time spent to execute one scheduler loop. 0.99 percentile.
`airflow.scheduler.scheduler_loop_duration.count` `TIMING,` number	Number of measurements of time spent to execute one scheduler loop.
`airflow.scheduler.scheduler_loop_duration.lower` `TIMING,` milliseconds	Minimum time spent to execute one scheduler loop.
`airflow.scheduler.scheduler_loop_duration.mean` `TIMING,` milliseconds	Average time spent to execute one scheduler loop.
`airflow.scheduler.scheduler_loop_duration.median` `TIMING,` milliseconds	Median time spent to execute one scheduler loop.
`airflow.scheduler.scheduler_loop_duration.stddev` `TIMING,` milliseconds	Standard deviation of time spent to execute one scheduler loop.
`airflow.scheduler.scheduler_loop_duration.sum` `TIMING,` milliseconds	Total time spent to execute one scheduler loop.
`airflow.scheduler.scheduler_loop_duration.upper` `TIMING,` milliseconds	Total time spent to execute one scheduler loop.
`airflow.scheduler.tasks.executable.value` `GAUGE,` number	Number of tasks ready to run according to pool limitations, DAG competitiveness, executor state, and priorities.
`airflow.scheduler.tasks.starving.value` `GAUGE,` number	Number of tasks that cannot be scheduled because there is no free slot in the pool.
`CeleryExecutor` `GAUGE,` number	Number of Celery workers at different stages of task execution. The `status` label value means the number of workers that: `open`: Are ready to receive a task. `queued`: Have received tasks but have not yet started executing them. `running`: Are executing tasks.

¹ Only one scheduler can enter this loop at a time.
² Data serialization process for exchange between tasks and for web server and scheduler security.

Yandex Monitoring metric reference

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