Service health score, impact score, and metrics
Service health score
The service health score is computed for the selected time range using the impacted events associated with each of the service entities and the significance derived from service topology. The higher the health score, the healthier the service. The service health score ranges from 0 to 100.
The service health score is displayed on the service details page as shown in the following image:
The service health is represented using the color-coded severity values as shown in the following image:
If the service severity is Ok, the service is healthy. Any other severity value such as Critical, Major, Minor indicates that the service is impacted.
Impacted entities and Impacted CIs
Impacted Entities on the service details page displays the top 3 impacted business services that are part of the main impacted service. In the following example, BMC Banking Application and Banking Core Servers are the top impacted business services that are part of the BMC Financial Service business service. Impacting Events shows the number of open events impacting the services.
Impacted CIs on the Services page displays the total count of impacted CIs associated with a service. In the following example, there are 5 impacted CIs that are associated with the cattle_namespace and 2 impacted CIs with manual_bs_service services.
Service health timeline
The service health score for the selected time range is represented by using the health timeline on the service details page. Here is an annotated screenshot of the service health timeline:
Time range selector. Click the arrow to change the time range. You can select a relative time range such as 3,6,12, and 24 hours. By default, Last3 hours time range is selected. Depending on the time range selected, the timeline is divided into equal-length time slots as shown in the following table:
Time range
Length of each time slot
3 hours
5 minutes
6 hours
5 minutes
12 hours
15 minutes
24 hours
20 minutes
Service health score for a specific time slot on the health timeline. Hover over a time slot to view the health score.
Legends to indicate incidents, events, and change requests on the health timeline. Hover over a legend on the health timeline to view event, incident, or change request details. For more information, see:
- Event-noise-reduction-indicator-for-prioritized-triage-and-remediation
The health timeline does not display the INFO and OK events. - Total-incident-count-and-mean-time-to-resolve-MTTR-indicators-for-a-reliable-incidence-response-process
How do I derive insights using the event, incident, and change request legends?
When you hover over a legend on the health timeline, the corresponding details are displayed along with the timestamp. If you find unusual occurrences of events, incidents, or change requests, hover over the legends, collate the details, and analyze them to resolve the issues.
Example
In the preceding example:
The event count is 1 on 15/02/2021 at 12:37, and the event count is 10 on 15/02/2021 at 13:32. You can check the details of the events that occurred during this time slot and analyze the associated information to determine and resolve the error condition. Click the time slot to view the event details and to perform root cause isolation. For more information, see Performing-ML-based-root-cause-isolation-of-an-impacted-service.- Event-noise-reduction-indicator-for-prioritized-triage-and-remediation
Service impact score
The service impact score indicates how the service is impacted because of its entities. The service impact score is inversely proportional to its health score. The higher the service impact score, the lower is its health.
Impact score = 100 - service health score
In BMC Helix AIOps, the service impact score is displayed on the service details page as shown in the following image:
The service health score is 64in the example and hence the impact score is 36.
Health Indicator
The health indicator is a measure that provides relevant insight into the behavior of one or more essential CIs that are part of the Service. For example, Hourly average capacity of the File System, Kubernetes configuration status at different time intervals, and so on.
As a service administrator, you can define a health indicator as part of a service model definition. Each health indicator is a single or collection of metrics from CIs. Each metric contains an alarm trigger condition to generate events when a threshold value is violated. For more information on setting alarm policies, see Alarm Policies, on adding health indicator to a service model, see Modeling-services, and for viewing the health indicators as part of service details, see Performing-ML-based-root-cause-isolation-of-an-impacted-service. You can view the heath indicator metrics chart associated with the impacted service as shown in the following image:
Metrics
Metric is an important performance indicator in your environment. For example, if you have a Linux monitoring solution and CPU monitor type, the following section lists a few example metrics that can be monitored:
- Utilization
- Load
- Idle time
- Context Switches
You can view the metrics associated with the top three events associated with the top 3 impacted nodes for a service. An example metrics chart is shown in the following image:
Service health insights
The following video (1:53) shows a high-level overview of the Service Insights feature in BMC Helix AIOps:
https://youtu.be/NAy2pEMzjF8View and analyze the summary of service health behavior and its severity pattern for a pre-defined period of 15 days, derive insights, and take corrective measures to ensure service continuity. The following section lists use case examples for understanding the health behavior and severity patterns:
- Service health behavior: For a service, the text summary shows the highest percentage degradation and the graph represents the daily average health score trend, for the predefined period. For example, see the following behavior pattern for consecutive four days period.
Let's consider an example of a Financial Service, for which the daily average health score and their percentage changes are described in the following table.
Date | Daily Avg. Health Score | % change in Daily Avg. Health Score, compared to previous day Formula: [(H2 - H1)/(H1)] x 100 where, H1 = Average Health Score of Previous Date H2 = Average Health Score of Current Date
| |
|---|---|---|---|
06/13/2022 | 62.50 | - | - |
06/14/2022 | 61.25 | [(61.25 - 62.5)/62.5] x 100 | - 2 % |
06/15/2022 | 60 | [(60-61.25)/61.25] x 100 | - 2.04 % |
06/16/2022 | 60.79 | [(60.79-60)/60] x 100 | + 1.31 % |
06/17/2022 | 59.86 | [(59.86-60.79)/60.79] x 100 | - 1.53 % |
06/18/2022 | 60 | [(60-59.86)/59.86] x 100 | + 0.23 % |
BMC Helix AIOps displays only the highest percentage degradation of average service health (e.g., 2.04%) in the summary text with the respective comparison dates. From the corresponding daily average health score trend, you can identify the zone of highest percentage degradation.
- Service severity pattern: For a service, the summary text shows the daily occurrence time of Critical or Major severity, and the corresponding graph shows the severity occurrence pattern highlighted for the predefined period. For example, see following severity pattern with two repetitive durations on three consecutive days.
Consider the table below, showing the daily occurrences of Major and Critical severities of a Financial Service. Let's try to derive a pattern considering the periodical repetition of severities. We can see only the Major severity is occurring daily between 21:30 and 05:30 hours. However, based on the occurrences of Critical severity we can't derive any pattern.
Date | Severity | Duration |
|---|---|---|
06/14/2022 | Major | 21:30 to 5:30 hrs |
Critical | 07:00 to 10:00 hrs | |
06/15/2022 | Major | 21:30 to 5:30 hrs |
Critical | 09:00 to 11:00 hrs | |
06/16/2022 | Major | 21:30 to 5:30 hrs |
Critical | 07:00 to 10:00 hrs |
BMC Helix AIOps displays the pattern for the occurrences of Major severity during the period. From the graph, viewing the highlighted sections you can identify the pattern. As per the example, we see the graph only for the Major severity, since it repeats regularly at a fixed time daily. However, there will be no graph for the Critical severity as the regularity pattern is broken on 06/15/2022.
Where to go from here