--- sourceDocument: Brazil Impact sourceDocumentLink: https://www.servicenow.com/docs/r/impact Release : - brazil ft:locale : - en-US ft:publication_title : - Brazil Impact ft:clusterId : - ipact bundleId : - ipact --- # Scheduler performance metrics # Scheduler performance metrics {#ariaid-title1} Release version: Brazil Updated September 10, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read The metrics provide the Schedulers performance snapshot within the ServiceNow AI Platform®. ## Completed Scheduled Jobs {#io-schedulers-perf-metrics__section_a5c_5lx_hjc} The number of scheduled jobs completed per node. There are many types of scheduled jobs. They could be scheduled reports, scheduled script executions, one-time jobs like SLA or Workflow Timers, or repeating jobs like Email Sender or Event Processor. In addition to what you might think of as traditional scheduled "jobs" there is also a couple special case of operations that run on the scheduled job queue called, Asynchronous business rules. These can be work that was triggered from the UI or an integration but runs as a scheduled job to achieve asynchronous behavior. Typical examples of Asynchronous business rules are Discovery Sensors or perhaps a job that iterates over a large number of child records, making so many updates that it would not be a good user experience to have to wait for them all to complete. Note: * When scheduled job counts suddenly shoot up this can be concerning as it may overwhelm processing and cause lag. * This should be considered together with other job metrics like the scheduler age, scheduler queue length, and pending jobs counts. {#io-schedulers-perf-metrics__ul_ov1_xlx_hjc} ## Scheduler mean queue age {#io-schedulers-perf-metrics__section_uwn_zlx_hjc} The average age of all unprocessed jobs in an application node in memory scheduler queue (i.e., the delta between the job being claimed by the node or placed in the queue and the point at which metrics were collected). Note that this does not include time the job spent pending in the sys_trigger table between its 'Next Action' time (that is, when it should have run) and when it was claimed. A large scheduler mean queue age can indicate that an application node is struggling to process claimed jobs (that is, those in its in memory queue) in a timely manner. Note: Check to see if the majority of worker threads on the corresponding node are busy executing long running scheduled jobs --- in this scenario long running jobs should be investigated to reduce frequency/improve performance/stagger execution. In New York and later a node which is unable to process claimed jobs can send these jobs back to the sys_trigger table to be claimed by other nodes. Check whether this functionality is working as expected ## Scheduler queue length {#io-schedulers-perf-metrics__section_xg4_kmx_hjc} The number of claimed scheduled jobs in each application nodes in memory scheduler queue. Note that this does not include scheduled jobs which are currently executing on a worker thread on the application node. It is common for application nodes to claim multiple jobs at once and therefore have a significant scheduler queue length at any point in time. If a single node has significant queue length for a sustained period (that is, more than 60 minutes), where queue length does not drop down to 0 and scheduler age is increasing, this may indicate the node has an issue processing scheduled jobs. If multiple nodes see similar issues it may indicate either all nodes are having issues processing scheduled jobs or the instance is simply overwhelmed by scheduled jobs. Note: * Check scheduled jobs executing on application nodes to determine type or source. * Address performance or scheduling of jobs as necessary to prevent them overloading worker threads. {#io-schedulers-perf-metrics__ul_yhq_44x_hjc} **Related reference** * [Anomaly insights](https://www.servicenow.com/docs/9eMZNrCJaJtg~3aFIFet1A "The reference topic gives additional information for anomaly charts.") * [Feature availability based on package](https://www.servicenow.com/docs/M3A1LJNB8V4JVxJd7sbWsA "The table outlines the access permissions for Performance Analytics features across production and sub production instances.") * [Auriga Intelligent Alert report](https://www.servicenow.com/docs/V1ruTiVtM2A3MbeTcDpeYQ "Auriga Intelligent Alert is an advanced multivariate machine learning (ML) model that learns from historical issues on your instance to provide real-time insight. Auriga monitors your performance metrics to deliver notifications of noteworthy events or deviations from anticipated data patterns.") * [Transaction or response metrics](https://www.servicenow.com/docs/OqtPTCLgCEFebynXPu5FUA "The metrics provide a performance snapshot of classic UI transactions within the ServiceNow AI Platform.") * [Database performance metrics](https://www.servicenow.com/docs/_cccPZVYR~lyZyDQd9i1rg "The metrics provide the database performance snapshot within the ServiceNow AI Platform.") * [Semaphores performance metrics](https://www.servicenow.com/docs/VPNjbLl2b_wmgHTCQLSISg "The metrics provide the key performance indicators calculated at the instance level for the selected duration.") * [Event queues performance metrics](https://www.servicenow.com/docs/FzQ~auFuRBp08BnxEI7RRQ "The metrics provide the event performance snapshot within the ServiceNow AI Platform.") * [ECC Queue performance metrics](https://www.servicenow.com/docs/_O_6TR7e9CzFqyACutE4AA "The metrics provide the ECC Queue performance snapshot within the ServiceNow AI Platform.") * [Email performance metrics](https://www.servicenow.com/docs/GBdK4QuaJS5f89Z0DzLCYw "The metrics provide the Email performance snapshot within the ServiceNow AI Platform.") * [Job details performance metrics](https://www.servicenow.com/docs/s_D18FA~3ZZvqGb5gp_K0g "The metrics provide the job details performance snapshot within the ServiceNow AI Platform.") * [Node health performance metrics](https://www.servicenow.com/docs/nQjkyl1AcdIzwWbTM63MHw "The metrics provide the node health performance snapshot within the ServiceNow AI Platform.") * [Host health performance metrics](https://www.servicenow.com/docs/Yez46paUCAk0Na7ewZ82hQ "The metrics provide the host health performance snapshot within the ServiceNow AI Platform.") * [Standby replication Lag](https://www.servicenow.com/docs/B9CtYGvUn9MVs9J0Mgmt8w "A read replica is a copy of the primary DB that reflects changes to the primary in almost real time, in normal circumstances. The lag represents the database server of the instance that is behind in seconds.") * [Pool Replication Lag](https://www.servicenow.com/docs/YSPXFJIoJR_vf8BzPPjQew "Pool replication lag is the number of seconds that a Standby database or a read replica database lags behind the primary database.") * [Chat details performance metrics](https://www.servicenow.com/docs/~EfYHOVKr6RLUqarKf6dGw "For the operations team to get the insights of current load across main components of AWA channel infrastructure like queues and agents, and to monitor load during events of chat spikes.") * [Cluster details performance metrics](https://www.servicenow.com/docs/n1cNOtxAWYwNE5sjOFJmoA "The metrics provide the cluster details and Encryption status snapshot within the ServiceNow AI Platform.") * [Load balancer performance metrics](https://www.servicenow.com/docs/nxr5K~NVw8540hEh5TqvOQ "The metrics provide the load balancer performance snapshot within the ServiceNow AI Platform.") * [User information metrics](https://www.servicenow.com/docs/_Ly6DopUwh4OA_SaAk6Kyg "The metrics provide the user information performance snapshot within the ServiceNow AI Platform.") * [Instance Data Replication](https://www.servicenow.com/docs/0j2ckH2pLj3hbtk4zpouHQ "The Instance Data Replication (IDR) copies data updates from one instance, called the producer instance, to one or more other instances called the consumer instances.")