DRAFT
On the Anomaly Impact Details page, users gain insight into why & how AGILITY triggered each anomaly notification by delineating the anomaly’s unique information we received. The Anomaly Impact Details page allows you to drill down further into an anomaly's causes & impacts to expedite network resolution processes and gather knowledge to prevent similar anomalies from reoccurring.
How to Access the Anomaly Impact Details Page (RAN Domain)
The Anomlay Impact Details page is accessible through each domain dashboard. To get to the Anomlay Impact Details page, users need to expand the anomaly’s information row & select View Details
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On the Anomaly Details page, go to the Imapcted KQIS chart.
Select the graph line icon from the SEE See Trends column.
The Service KQIS TREND data Trend graph for the selected KQI will load.
Normal network behaviour The KQI is plotted on the y-axis.
The time is plotted on the x-axis.
The legend provides the context for the colors used on the graph.
Normal network behavior (no anomalies) is plotted in green
Auxillary data togle adds secondary data the secondary axix added on the right hand side adds data that lets you visualize the cause
Performance Management:
key performance indicators are network level performance level - second two tables PM KPIS
names are standard they all know what those names mean
kpi value mathematical value the result of the anomaly on performance
Imapct Level means the severity of the anomaly and the percentage deviation level how much it deviates from the normal network
Importance : the inidcagti=or that was decided to trigger the anomaly numbers greater than zero indicate that this KPI was degraded and therefor triggered an anomaly . You will see dgredation in the chart if it is higher than 0
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, the selected anomaly is plotted in red, and historical anomalies are plotted in yellow.
The Performance Management KPIS (Key Performance Indicators) Chart
The PM KPIS chart provides network-level key performance indicators to help users identify the severity of the anomaly.
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The KPI Name column lists industry-standard network performance KPIs.
The KPI Value column quantifies the mathematical value of the impact that the anomaly had on network performance.
The Impact Level column qualifies the impact that the anomaly had on performance. The impact levels include Low, Medium, High, No & N/A. “No” means that there was no impact. “N/A” means that there is no data available.
The Importance Level column lists the numerical value that determines whether or not an anomaly is triggered. If the value is greater than zero, network degradation has occurred and will be reflected in the RAN Metrics Trend chart.
The See Trends column allows users to visualize the service impact on a graph that plots the impacted PM KPI for the selected anomaly amongst normal network behavior to highlight deviations and demonstrate their severity.
RAN Metrics Trend
The RAN Metrics Trends graph plots the impacted PM KPI for the selected anomaly amongst normal network behavior to highlight deviations and demonstrate their severity.
How to View the RAN Metrics Trend Graph
To view the impacted RAN Metrics Trends graph:
On the Anomaly Details page, go to the PM KPIs chart.
2. Select the graph line icon from the See Trends column.
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The Service KQIS Trend graph for the selected KQI will load.
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The KQI is plotted on the y-axis.
The time is plotted on the x-axis.
The legend provides the context for the colors used on the graph.
Normal network behavior (no anomalies) is plotted in green, the selected anomaly is plotted in red, and historical anomalies are plotted in yellow.
Show Auxiliary Data on the RAN Metrics Trend Graph
To display Auxiliary Data on the RAN Metrics Trend graph:
Toggle Show Auxiliary Data to the right.
The auxiliary data will load
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FM Alarms
if we have an alarm on site it will trigger an anomaly based on the alarms right now we don't have an alarm . In some cases we do have an alarm. Example of cases with an alarm: https://oci-ad-dev.b-yond.com/ran/anomaly/c3818f35-a987-d578-aa66-58f7bcb3569c?restoreFilters=4bdbf827-75e0-4620-99d1-4b55ce3ebcba
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