SAN JOSE, Calif., May 30, 2019 (GLOBE NEWSWIRE) -- OpsRamp, the service-centric AIOps software-as-a-service (SaaS) platform for the hybrid enterprise, today announced OpsQ Observed Mode to build confidence in machine learning models for IT event and performance analysis. The Summer 2019 Release also introduces automated alert suppression to reduce human time spent on first-response to alerts, continuous learning-based alert escalation using live event data, and new infrastructure monitoring capabilities for cloud native environments.
According to OpsRamp’s 2019 State of AIOps report, 67% of respondents have concerns about the relevance and reliability of the insights delivered by artificial intelligence for IT operations (AIOps) tools. OpsQ Observed Mode enables IT teams to assess the accuracy of machine-learning-driven correlation decisions in preview mode, enhancing the integrity of data for improved decision-making.
"We already use the OpsQ event management engine to reduce alert storms from 200,000 raw events per month down to a more manageable 10,000 incidents per month,” said Tim Hebert, Chief Managed Services Office of Carousel Industries, a leading managed services and cloud services provider. “The OpsRamp Summer Release allows our infrastructure teams to understand the alert suppression capabilities of inference models before we commit to them, and that's tremendously beneficial in our event management workflow."
Highlights of the OpsRamp Summer 2019 release include:
Service-Centric AIOps: OpsQ is OpsRamp's intelligent event management, alert correlation, and remediation solution. New OpsQ capabilities help IT teams drive faster incident prioritization and rapid mean-time-to-resolution (MTTR) for dynamic infrastructure workloads and include:
Service and Topology Maps: The Summer 2019 Release introduces new impact visibility and service context features that deliver dynamic relationship data for public cloud services and actionable insights for understanding cross-site interconnections.
Cloud Native Discovery and Monitoring: DevOps and site reliability engineering (SRE) teams can now monitor popular open source applications used in cloud native environments and access relevant performance insights for Mesosphere and Azure Stack in the OpsRamp platform.
“Our customers have told us that they’d like to see how AIOps inferences proactively detect, diagnose, and address service continuity issues. OpsQ Observed Mode is a no-risk option for IT operations and DevOps teams to assess the accuracy and power of machine intelligence-driven event management, ” said Mahesh Ramachandran, VP of Product Management for OpsRamp. “The Summer 2019 Release provides modern IT infrastructure teams the real-time intelligence to fix visibility gaps in their hybrid and multi-cloud environments.”
The OpsRamp Summer 2019 Release also includes new synthetic monitoring capabilities, service map enhancements, bulk export of operational data for data mining, and monitoring of integration failures.
To learn more about OpsRamp Summer 2019 Release, visit www.OpsRamp.com/whatsnew.
To sign up for the OpsRamp Summer Release Webinar, visit info.OpsRamp.com/summer-release-2019.
About OpsRamp
OpsRamp enables IT to control the chaos of managing their hybrid digital operations. Built in the cloud, the OpsRamp service-centric AIOps platform drives total visibility across hybrid infrastructures, offers complete multi-cloud infrastructure monitoring and management of business-critical services, and optimizes services through automation and integration with ITSM and DevOps tools. Now enterprise IT can deliver IT operations as a service and power a digital operations command center that’s built for the challenges of modern, hybrid infrastructure.
Hundreds of enterprises like Dolby, Epsilon, and Bio-Rad, and managed service providers like Carousel Industries, GreenPages, and NTT Data run OpsRamp to unify service availability information, transform contextual insight into action, and replace routine tasks with intelligent automation. Learn more at OpsRamp.com.
Media Contact:
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TGPR
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