Until now, fault management tools have been unable to ‘turn the on lights’ to application interruptions, especially across highly virtualized dynamic infrastructures. We’ve all experienced these types of application interruptions; whether it be from the jitter and latency or signaling of VoIP and Video Conference sessions, or when there are delays in using online web applications that cause us to wonder if our application session is even still alive.

Prelert is the first of a new generation business service management solution that isolates application behavior abnormality root-causality in real-time, using all available service assurance telemetry and, without topographical knowledge.

There is No Early Warning of Application Interruptions

The reality for service assurance staff is that their first notification of an issue that impacts their customers’ experience is when affected users report their problem.

Where the Customer has become the notification service inflates the Incident MTTR cost by greater than 300%; subjugating resources from multiple management silos for hours at a time in an effort to isolate the causality of the application interruption.

Prelert’s Service Causality Analysis will have isolated both that an application interruption occurred and, how that application interruption occurred, often allowing operations to resolve the issue even before the Customers call.



Prelert is designed to reduce the risk of adverse customer experience leading to uncontrollable service assurance costs.

Back to top

Test the value of Prelert using your own data with no software install

If you have service assurance products like: IBM Tivoli Netcool, Splunk, CA e-Health, InfoVista, HP OpenView, EMC-SMARTS, and LogLogic for example, we’re pretty sure that you will already be collecting telemetry that can demonstrate the value of Prelert to your business.

To make it easy to show demonstrate the value of Service Causality Analysis, Prelert offers a Causality Analysis Verification (CAV) process. The CAV takes your existing data and identifies episodes of causality that lead to application errors from your data, all without any on premise software installation or huge effort on your part.

The CAV is designed to:

• Snapshot the causality in your environment
• Model causality episodes, if any, which exists in your existing datasets
• Demonstrate Prelert’s ability to greatly reduce the operational efforts and risks associated with isolating application errors
• Enable comparison of value between Prelert’s causality approach to legacy rules-driven root cause approaches
• Prove that application error causality can be achieved with low Opex
• Outline recommendations for where the use of causality modeling will best reduce service management costs

REQUEST A PRELERT CALL

Back to top