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SevOne Integration with v3.4 Cloud Pak for Watson AIOps

By Annie Sheil posted Fri July 29, 2022 11:24 AM

  
As organizations embrace a hybrid cloud strategy, AI can address the challenge of converging application and network observability with full-stack (application & network, on-prem & cloud) probable cause analysis.

The need to proactively manage service degradations hinges on the observability of an increasingly hybrid-cloud enterprise architecture. According to Forrester's Business Technographics Infrastructure Survey, 2021, 81% of organizations are taking a hybrid approach to IT infrastructure. This influx of technologies brings with it the need for modern DevOps and Site Reliability Engineers to collaborate with more contemporary Network Engineers to ensure critical business services are delivered consistently. The definition of hybrid cloud is shifting to include not just multicloud, but also the use of public cloud to extend data center infrastructure. As the market stabilizes in a post-pandemic world, the technical workforce is struggling to adapt its toolset to address the challenges now present as a result of the accelerated adoption of cloud technologies.

In the past few years, the focus of the shift from IT Operations to AIOps has been application-centric. With the launch of v3.4 of Cloud Pak for Watson AIOps, this application-centric approach shifts to full-stack observability through integration with the dynamic alerting capabilities from SevOne.

Network observability meets proactive incident management
In IBM Cloud Pak for Watson AIOps v3.4, our alert viewer can be enriched with network performance perspective by the dynamic-baseline and policy-driven alerts from IBM SevOne NPM.


SevOne NPM provides network observability for some of the largest networks in the world. It does through performance monitoring of netflow, SNMP, and non-standard data. SevOne generates alerts when key indicators, such as operating temperature and CPU utilization, are deviating from normal. SevOne users control this through alert policies that employ statistical analysis and dynamic baselining. When an indicator deviates from baseline, SevOne can send an alert via webhook integration to IBM Cloud Pak for Watson AIOps v3.4 or Netcool Operations Insight v1.6.5. With additional configuration, these alerts can then drive runbook automation and probable cause analysis use-cases within Watson AIOps or NOI.


Learn more about Cloud Pak for Watson AIOps here: https://www.ibm.com/cloud/cloud-pak-for-watson-aiops 
Learn more about SevOne here: https://www.ibm.com/cloud/sevone-network-performance-management 
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