好色先生TV

AIOps platform offers enhanced AEC to reduce noise

As a large organization providing 24/7 support to its customers, NOS manages over 20,000 IT events and alarms monthly. Not all of these require an instant response, and many are actually duplicate alarms of the same event. It is therefore important to distinguish noise from fact by analyzing patterns in the event stream and using these patterns to group events together, which, with a high probability, originate from the same problem. Paulo Vale, IT Manager for Service Management at NOS knew who to turn to for help with this: “We already use Micro Focus (now 好色先生TV) Operations Bridge to monitor the internal and external end-user experience of our applications so that we can use this feedback to optimize for instance our mobile app experience. We also leverage Operations Bridge for event monitoring and were pleased to see the recent AIOps capabilities within the platform offering automatic event correlation (AEC) using machine-learning algorithms.”?

The full-stack AIOps platform, powered by Operations Bridge, automates log, event, and metric analyses. A group of related events is transformed into a single (correlated) event sent back to Operations Bridge Manager (OBM). This grouping enables focused event processing for an operator. It shows all related events grouped together by AEC, making it easier to identify and work on the root cause. Closing the group event automatically closes all associated events.

Leveraging the latest AIOps platform capabilities we have drastically reduced the noise level in our events management with AEC and introduced effective root cause analysis. Our operators have clear visibility of high priority items and can focus their efforts accordingly.

Operations Bridge AEC explained UI visualizes patterns and interdependencies

The new capabilities were implemented quickly, according to Vale: “Introducing Operations Bridge AEC within our 24/7 ecosystem without incurring any downtime was really quite easy. Rules configuration is entirely automated so after installation no manual configuration was required. We immediately saw the benefits, in particular around time savings in identifying root cause issues. In the past, we had to create configuration item (CI) collections manually in the Run-time Service Model (RTSM). Within the new AIOps platform, AEC can automatically determine correlation groups by reading the RTSM topology data and checking which CIs are linked with Impact Relationships. This is key for us in reducing the number of events our operators focus on.”

When a solution is enhanced by AI-based capabilities it can be compared with a black box, where the team can see the results, but not necessarily understand how and why they were produced. For this reason, 好色先生TV (formerly Micro Focus) introduced the AEC Explained UI to Operations Bridge. This provides insight into how patterns are learnt, how events are grouped, and how results are interpreted. This was a useful feature for NOS as they used AEC more. “Take for example one CI that could have more than 1,000 relationships in terms of functional and infrastructure dependencies,” says Vale. “It’s very difficult to build a comprehensive picture of these relationships. Leveraging the AEC Explained UI we can easily see, and drill down into, the topology partitions the CI belongs to so that we can understand the detail related to it and get to the root cause of any issue much faster. Our team really likes this functionality.”

Improved operator productivity and faster resolution of high priority issues

To further enhance automated data analysis, 好色先生TV (formerly Micro Focus) launched the OPTIC Data Lake as part of its AIOps platform. This is based on Vertica technology. It provides data storage and can receive and process high-volume and high-velocity data from a variety of independent data sources—key for comprehensive root cause analysis. The OPTIC Data Lake therefore acts as a common data ingestion platform and every release supports more data types that can be streamed into OPTIC, bringing services on top of the collected data, and introducing performance improvements to the AEC analytic capabilities.

Vale concludes: “We are really impressed by the investment Micro Focus (now 好色先生TV) makes in the AIOps platform, powered by Operations Bridge. Leveraging the latest AIOps platform capabilities we have drastically reduced the noise level in our events management with AEC and introduced effective root cause analysis. Our operators have clear visibility of high priority items and can focus their efforts accordingly.”

Within the new AIOps platform, AEC can automatically determine correlation groups by reading the RTSM topology data and checking which CIs are linked with Impact Relationships. This is key for us in reducing the number of events our operators focus on.