Technologies/Celery/celery.task.runtime
CeleryCeleryMetric

celery.task.runtime

Total task runtime sum
Dimensions:None
Available on:OpenTelemetryOpenTelemetry (1)PrometheusPrometheus (1)
Interface Metrics (2)
OpenTelemetryOpenTelemetry
Total runtime of tasks (sum of durations)
Dimensions:None
PrometheusPrometheus
Total runtime of successful tasks in seconds (deprecated, use celery_task_runtime_seconds)
Dimensions:None
Sources
celery.task.runtimedocs.celeryq.dev
celery_tasks_runtime_secondsgithub.com

Technical Annotations (14)

Configuration Parameters (3)
task_time_limitrecommended: 600
Hard limit in seconds before task is forcefully terminated
task_soft_time_limitrecommended: 300
Soft limit allowing graceful cleanup before hard termination
CE_BUCKETSrecommended: 1,2.5,5,10,30,60,300,600,900,1800
histogram buckets for async tasks ranging from 1 second to 30 minutes
Technical References (11)
CDNcomponentmicroservice architectureconceptlatencyconcepthigh-frequency tasksconceptconnection poolcomponentPicklecomponentJSONcomponentpyinstrumentcomponenthistogram bucketsconceptCeleryHighQueueLengthconceptworker pool sizecomponent
Related Insights (11)
High network latency causes up to 30% increase in task completion timewarning
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Inefficient task design causes latency from external service dependencieswarning
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Task time limits prevent runaway tasks from blocking workers indefinitelyinfo
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High-frequency tasks exceeding 100ms latency degrade user satisfactionwarning
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Connection pooling reduces broker latency by 27%warning
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Task serialization with Pickle doubles time vs JSONwarning
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Pyinstrument production profiling adds significant performance overheadwarning
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Task latency spikes identified as primary bottleneck in 65% of deploymentswarning
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Task execution time degradation impacts user experiencewarning
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Default Prometheus histogram buckets unsuitable for Celery async task runtimewarning
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High Celery queue length indicates worker processing bottleneckwarning
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