Merge pull request #97579 from rboucher/dynamthres

update article for github issue

Author: GitHubber17

articles/azure-monitor/platform/alerts-dynamic-thresholds.md

@@ -20,11 +20,11 @@ We would love to hear your feedback, keep it coming at <azurealertsfeedback@micr
 
 ## Why and when is using dynamic condition type recommended?
 
-1. **Scalable Alerting** – Dynamic Thresholds alerts rules can create tailored thresholds for hundreds of metric series at a time. Yet providing the same ease of defining an alert rule on a single metric. Using either the UI or the Azure Resource Manager API results in fewer alert rules to manage. The scalable approach is especially useful when dealing with metric dimensions or when applying to multiple resources, like all subscription resources. Which translates to a significant time saving on management and creation of alerts rules. [Learn more about how to configure Metric Alerts with Dynamic Thresholds using templates](alerts-metric-create-templates.md).
+1. **Scalable Alerting** – Dynamic threshold alert rules can create tailored thresholds for hundreds of metric series at a time, yet providing the same ease of defining an alert rule on a single metric. They give you fewer alert to create and  manage. You can use either Azure portal or the Azure Resource Manager API to create them. The scalable approach is especially useful when dealing with metric dimensions or when applying to multiple resources, such as to all subscription resources.  [Learn more about how to configure Metric Alerts with Dynamic Thresholds using templates](alerts-metric-create-templates.md).
 
-1. **Smart Metric Pattern Recognition** – Using our unique ML technology, we’re able to automatically detect metric patterns and adapt to metric changes over time, which may often include seasonality (Hourly / Daily / Weekly). Adapting to the metrics’ behavior over time and alerting based on deviations from its pattern relieves the burden of knowing the “right” threshold for each metric. The ML algorithm used in Dynamic Thresholds is designed to prevent noisy (low precision) or wide (low recall) thresholds that don’t have an expected pattern.
+1. **Smart Metric Pattern Recognition** – Using our ML technology, we’re able to automatically detect metric patterns and adapt to metric changes over time, which may often include seasonality (hourly / daily / weekly). Adapting to the metrics’ behavior over time and alerting based on deviations from its pattern relieves the burden of knowing the "right" threshold for each metric. The ML algorithm used in Dynamic Thresholds is designed to prevent noisy (low precision) or wide (low recall) thresholds that don’t have an expected pattern.
 
-1. **Intuitive Configuration** – Dynamic Thresholds allow setting up metric alerts using high-level concepts, alleviating the need to have extensive domain knowledge about the metric.
+1. **Intuitive Configuration** – Dynamic Thresholds allows setting up metric alerts using high-level concepts, alleviating the need to have extensive domain knowledge about the metric.
 
 ## How to configure alerts rules with Dynamic Thresholds?
 
@@ -59,7 +59,7 @@ You can choose the alert to be triggered on one of the following three condition
 
 ## What do the advanced settings in Dynamic Thresholds mean?
 
-**Failing Periods** - Dynamic Thresholds also allows you to configure “Number violations to trigger the alert”, a minimum number of deviations required within a certain time window for the system to raise an alert (the default time window is four deviations in 20 minutes). The user can configure failing periods and choose what to be alerted on by changing the failing periods and time window. This ability reduces alert noise generated by transient spikes. For example:
+**Failing Periods** - Dynamic Thresholds also allows you to configure "Number violations to trigger the alert", a minimum number of deviations required within a certain time window for the system to raise an alert (the default time window is four deviations in 20 minutes). The user can configure failing periods and choose what to be alerted on by changing the failing periods and time window. This ability reduces alert noise generated by transient spikes. For example:
 
 To trigger an alert when the issue is continuous for 20 minutes, 4 consecutive times in a given period grouping of 5 minutes, use the following settings:
 
@@ -81,13 +81,13 @@ The alert view displays:
 - A chart of the period in which the alert was triggered that includes the Dynamic Thresholds used at that point in time.
 - Ability to provide feedback on Dynamic Thresholds alert and the alerts view experience, which could improve future detections.
 
-## Will slow behavior change in the metric trigger an alert?
+## Will slow behavior changes in the metric trigger an alert?
 
 Probably not. Dynamic Thresholds are good for detecting significant deviations rather than slowly evolving issues.
 
 ## How much data is used to preview and then calculate thresholds?
 
-The thresholds appearing in the chart, before an alert rule is created on the metric, are calculated based on enough historical data to calculate hour or daily seasonal patterns (10 days). Once an alert rule is created, the Dynamic Thresholds will use all needed historical data that is available and will continuously learn and adapt based on new data to make the thresholds more accurate. This means that after this calculation, the chart will also display weekly patterns.
+When and alert is first creates, the thresholds appearing in the chart are calculated based on enough historical data to calculate hour or daily seasonal patterns (10 days). Once an alert rule is created, Dynamic Thresholds uses all needed historical data that is available and will continuously learn and adapt based on new data to make the thresholds more accurate. This means that after this calculation, the chart will also display weekly patterns.
 
 ## How much data is needed to trigger an alert?
 
@@ -169,3 +169,20 @@ The following items are best practices on how to configure alerts on some of the
 
 > [!NOTE]
 > Metric alert rules created through portal are created in the same resource group as the target resource.
+
+## Interpreting Dynamic Threshold charts
+
+Following is a chart showing a metric, its dynamic threshold limits, and some alerts fired when the value was outside of the allowed thresholds.
+
+![Learn more about how to configure Metric Alerts](media/alerts-dynamic-thresholds/threshold-picture-8bit.png)
+
+Use the following information to interpret the previous chart.
+
+- **Blue line** - The actual measured metric over time.
+- **Blue shaded area** - Shows the allowed range for the metric. As long as the metric values stay within this range, no alert will occur.
+- **Blue dots** - If you left click on part of the chart and then hover over the blue line, you see a blue dot appear under your cursor showing an individual aggregated metric value.
+- **Pop-up with blue dot** - Shows the measured metric value (the blue dot) and the upper and lower values of allowed range.  
+- **Red dot with a black circle** - Shows the first metric value out of the allowed range. This is the value that fires a metric alert and puts it in an active state.
+- **Red dots**- Indicate additional measured values outside of the allowed range. They will not fire additional metric alerts, but the alert stays in the active.
+- **Red area** - Shows the time when the metric value was outside of the allowed range. The alert remains in the active state as long as subsequent measured values are out of the allowed range, but no new alerts are fired.
+- **End of red area** - When the blue line is back inside the allowed values, the red area stops and the measured value line turns blue. The status of the metric alert fired at the time of the red dot with black outline is set to resolved.