Create baseline alert conditions

Use baseline alert conditions to define thresholds that adjust to your data's behavior. This feature is available for New Relic Alerts users who have apps monitored by New Relic APM or New Relic Browser, and also available for NRQL queries.

Baseline alerting is useful for creating alert conditions that:

  • Dynamically adjust to changing data and trends, including daily or weekly trends.
  • Establish adjustable values for new applications with as-yet-unknown patterns.
  • Offer more hands-off thresholds that only notify you when data is identified as abnormal.

Access to baseline alerting is only available with Pro-level subscriptions. If all of your subscriptions are at the Essentials level, upgrade your subscription level to Pro on at least one New Relic product to gain baseline alerting access.

Workflow

Understanding how baseline alerting works will help you create effective conditions for them.

  1. You choose the metric data or NRQL query for which you want to create an alert condition.
  2. New Relic Alerts uses the past values of that data to dynamically predict the data's upcoming behavior. This ongoing prediction is called a baseline and appears as a dotted black line in the UI.
  3. Use the slider bar to adjust the alert thresholds (the gray bands around the baseline in the chart). Making the threshold smaller makes the condition more sensitive and will trigger more alert violations.
  4. You can set both a Critical threshold (the outer, light gray band in the chart) and an optional Warning threshold (the inner, dark gray band).
  5. When your data escapes the predicted "normal" behavior based on the options you have chosen, you will receive an alert notification.

Create baseline alert condition

All entities in a single alert condition share the same threshold settings. If you want to set different threshold settings for your APM or Browser entities, create multiple conditions for your policy.

To assign a baseline alert condition to a policy and one or more entities in New Relic Alerts:

  1. Follow the basic workflow process to set up an alert policy.
  2. When creating a condition, select APM > Application metric baseline or Browser > Metric baseline

    OR

    Select NRQL > Define thresholds and then select a Threshold type of Baseline.

  3. Adjust and set the baseline thresholds.
  4. Follow the UI prompts to complete and save the alert condition.

Adjust baseline alert thresholds

Creating an effective baseline condition threshold is a back-and-forth process of:

  • Adjusting threshold settings
  • Reviewing the violations those settings would theoretically create in your data

Here's an example of how to create baseline alert thresholds:

  1. Select the metric or input the NRQL query you want to monitor.
  2. For non-NRQL conditions: Select the time range (2 days or 7 days) for the preview chart using the dropdown selector above the chart.
  3. Set the Critical (red) threshold, which appears as a light gray band in the preview chart. Use the time settings to select what will trigger a violation. Use the slider to adjust the bands around the baseline.
  4. Optional: Follow the same procedure to set the Warning (yellow) threshold, which is the darker gray band in the chart.
  5. For non-NRQL conditions: If the alert condition applies to multiple apps, you can select a choice from the dropdown above the chart to see the metrics for different applications.
  6. When finished setting your thresholds, save your baseline alert condition.

The 2-day and 7-day preview charts are not the time period used to compute the baseline. They are simply a time range for the displayed data. The baseline is computed from up to several weeks of data, if available.

Baseline calculation

The algorithm for baseline conditions in New Relic Alerts is mathematically complex. Some of the major rules governing its predictive abilities include:

Data trait Baseline rules
Consistency of data

For metric values that remain in a consistent range or that trend slowly and steadily, their more predictable behavior means that their thresholds will become tighter around the baseline. Data that is more varied and unpredictable will have looser (wider) thresholds.

Regular fluctuations

For shorter-than-one-week cyclical fluctuations (such as weekly Wednesday 1 pm deployments or nightly reports), the baseline algorithm looks for these cyclical fluctuations and attempts to adjust to them.

Age of data

For data that has only existed for a short time, the baseline will likely fluctuate a good deal and not be very accurate. This is because there is not yet enough data to determine its usual values and behavior. The more history the data has, the more accurate the baseline and thresholds will become.

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