![]() The minimum time range for data requests is one minute (60 seconds). high priority tasks get longer timeslice (up to 200ms) than low priority tasks (as little as 10 ms) but all processes get a chance to run their timeslice. These attributes are available in addition to the metric-specific attributes listed in the APM metrics table above. Time slice averages, data aggregation policy, and non-existent data considerations. To understand more about the general structure of metric timeslice data, including some common examples, see Metric timeslice data. Learn how to see all metrics available to you. KeyTransactionName, transactionName, transactionTypeĪpm.Įxternal call response time by transaction type returns a long result representing the number of elapsed seconds since. Response time for external calls broken out by external host name The timeslicer increments the long variable named TIMESLICECOUNT each timeslice. Response time for database calls broken out by table operations other time-displacement functions such as timeShift and timeSlice. Here are how the original APM metric timeslice metrics are converted into dimensional metrics: This function can be used with aggregation functions average (or avg ), avgzero. If you don't see a metric you're looking for in this section, see Generic queries. The conversion of original APM metric timeslice metrics into dimensional metrics that are available for querying is an ongoing process and isn't complete. This optional clause displays the results in a time-based chart.įor general information on NRQL syntax, including FROM, FACET, and TIMESERIES, see Intro to NRQL.įor more queries, see Query examples. Sets the transaction type to web, meaning that background/non-web transactions won't be counted. Group data into time-sliced buckets for time. ![]() Timeslice also supports creating a fixed-target number of buckets, for example, 150 buckets over the last 60 minutes. This query uses entity.guid, but you can also use appId or appName. The timeslice operator aggregates data by time period, so you can create bucketed results based on a fixed interval (for example, five-minute buckets). You can select a single entity's GUID, as shown here, or you can select multiple sources. You must specify at least one data source. The timeslice operator is currently supported in the Metric Explorers advanced mode, not in basic mode. Note that you can use other aggregator functions. This query uses the converted metric names. This math generates a count of errors out of a total count of transaction metrics. For general tips on querying Metric data, see Metric query examples. Metric is one of our core data types, and metric timeslice data is stored as this data type.
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