Limits and rules pertaining to New Relic :
Limited condition | Minimum value | Maximum value |
---|---|---|
Alert policies: | ||
1 character | 128 characters | |
n/a | 10000 policies | |
Alert conditions: | ||
Matched data points per minute, per account (learn more) | N/A | 300M |
1 character | 128 characters | |
0 conditions | 500 conditions | |
0 conditions | 3700 conditions | |
OR Web app response percentiles per account | 0 conditions | 4000 conditions |
Targets (product entities) per condition | 1 target | 5000 targets for NRQL conditions 1000 targets for non-NRQL conditions |
Thresholds per condition | 1 Warning or 1 Critical | 1 Warning and 1 Critical |
Alert incidents: | ||
4000 characters | ||
30 seconds | 2 hours | |
Incidents per issue | 1 incident | 10,000 incidents Incidents beyond this limit will not be persisted. |
Incident search API: page size | 1 page (less than or equal to 25 incidents) | 1000 pages (25K incidents) TipOnly use the |
Workflows: | ||
n/a | Initial limit 1000 | |
Workflow filter size | 1 character | 4096 characters per workflow |
Notification channels (Legacy): | ||
Channel limitations |
NRDB alert query matched data points per minute
The alert condition Matched data points per minute
limit applies to the total rate of matched data points for the alerting queries in a New Relic account.
If this limit is exceeded, you won't be able to create or update conditions for the impacted account until the rate goes below the limit. Existing alert conditions are not affected.
You can see your matched data points and any limit incidents in the limits UI.
To understand what conditions are leading to the most throughput, you can perform a query like:
FROM NrAiSignal SELECT sum(aggregatedDataPointsCount) AS 'alert matched data points' FACET conditionId
Some tips on optimizing your matched data points:
- If you're using sliding windows, note that this can significantly increase the number of data points. To lower the number of data points, you can use a longer aggregation duration.
- Use
WHERE
clauses to scope down the amount of data being alerted on. UsingWHERE
instead ofFACET
can produce more efficient alerts in some cases. - Combine similar alerts. If you have several alert conditions that are similar, consider grouping them together with combined filters.
To request a limit increase, talk to your New Relic account representative.
Note that using sliding windows can significantly increase the number of data points. Consider using a longer duration of Sliding window aggregation to reduce the number of data points produced.