Service-centric predictions
The AI-based service-centric prediction in BMC Helix AIOpsconsumes service health indicators and metrics from multicloud and hybrid IT environments. It has the capability to predict service outages and helps in identifying and fixing issues before they happen. As a result, it helps reduce an organization's overall mean time to resolve (MTTR).
The Service Predictions page lists the services that might degrade in the next 24 hours. The predictions are calculated periodically based on the contributing metrics. For example, CPU Utilization or Disk I/O (disk read and write data) are some of the metrics used in the calculations. The service health indicators and metrics are related; for example, a high CPU Utilization slows down the response of applications. The prediction algorithm is capable of learning from past events to predict failures in the future.
Based on the calculations, services can be categorized by status as will be available (marked in green) or not available (other colors) in the next 24 hours. As time progresses, the algorithm continuously keeps learning and recalculates the status. Based on the recalculations, the availability status can change. This overriding of the previous status occurs at a pre-configured interval set within the algorithm.
Consider the following scenarios where you can use service predictions.
Jordan is a tenant administrator with APEX Global Finance, a financial services provider. The organization provides API services to multiple business consumers. APEX Global has an SLA of 99.9%, and if any of its API services goes down, it costs them a lot. Jordan thinks that if he can get predictive information about an API outage at least 30 minutes before it happens, he might be able to prevent, which in turn, will help his organization to meet the SLA.
Jordan is using BMC Helix AIOps service and situation monitoring features. Now Jordan can use the service prediction feature to list the services that might degrade in the near future. This information helps him maintain the system health more effectively.
Scott is a tenant administrator with APEX Global NMS, a network management service provider. The organization aims to provide the best wi-fi experience at all its client locations. Any degradation or drop in the wi-fi services decreases customer satisfaction and affects their clients' business.
Scott is using BMC Helix Operations Management for his IT operations management tasks. Additionally, he can use the service-centric predictions feature in BMC Helix AIOps, which gives him the ability to predict and prevent sensitive wi-fi service issues in advance and deliver maximum customer satisfaction.
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