OpsRamp, the service-centric artificial intelligence for IT operations (AIOps) platform, today announced the launch of OpsRamp OpsQ, an intelligent event management, alert correlation, and remediation solution for the hybrid enterprise.
Now, IT operations teams can optimize and automate routine tasks with context and insight at scale by understanding the business impact of an IT issue and ensure rapid service restoration. OpsRamp OpsQ introduces powerful machine learning inference models that learn how frequently specific alert sequences occur and recognize events correlated to the same cause.
With OpsQ, IT operations teams can analyze IT event streams in real-time, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection. OpsQ displays the critical root-cause alerts from native instrumentation and third-party event streams, suppresses non-emergency alerts, escalates critical events, and integrates with ITSM tools for faster remediation.
“We have seen dramatic improvements in certain alert volumes using OpsRamp OpsQ,” said Ravikumar Raghavender Rao, Vice President of Service Delivery at NetEnrich, a leading provider of automation-led cloud operations services, and a key partner of OpsRamp. “At some clients, for certain types of alerts, we’ve seen alert volumes reduce by over 90% due to effective correlation by OpsQ, improving our ability to provide first-to-know outcome-driven services to them.”
OpsRamp OpsQ includes several features to drive greater efficiency within modern IT operational environments, including:
- Inference Models. Enjoy a richer, deeper and more contextual view of your IT incidents using statistical evidence and reasoning with three inference models today:
- Topology-based correlation helps you visualize the upstream and downstream resources that comprise an IT service.
- Clustering-based correlation lets you create rules to correlate events based on their attributes.
- Co-occurrence-based correlation automatically recognizes alerts that are related by the same cause.
- Intelligent Alerting. Proactively identify service disruptions with forecasting and change detection alerts. Detect potential triggers and then speed incident detection by dramatically reducing the volume of alerts, so that IT teams can quickly focus on restoring the IT services that matter the most to the business.
- Alert Correlation. Surface accurate insights for problem isolation by ingesting, understanding and organizing alerts across dynamic and distributed IT environments.
- Alert Escalation. Drive faster mean-time-to-acknowledgement with smart and tailored notifications based on first-responder communication preferences (email, text, voice and chat) for faster reaction times.
- Auto-Incident Routing. Automatically send incidents to an appropriate team for rapid incident response using on-call schedules for your global NOC teams.
- Auto Remediation. Speed execution for incident remediation with automation policies that reduce administrative effort.
“Software is the critical enabler for digital transformation and the need for proactive performance monitoring of digital services has never been more important,” says Nancy Gohring, senior analyst from 451 Research. “Modern digital operations teams are increasingly looking to advanced analytical techniques like machine learning to assist in performance monitoring. The endgame is to deliver better customer experiences efficiently and at scale.”
“Our service-centric AIOps platform represents a fundamental transformation in how IT operations teams maintain business services and deliver exceptional customer experiences,” said Bhanu Singh, Vice President of Product Development and Operations for OpsRamp. “OpsQ helps enterprises and managed service providers handle previously unmanageable alert volumes, while OpsRamp’s service and topology maps let you visualize overall business-service health. Together, they’re a modern solution for IT monitoring and management in the hybrid, multi-cloud world.”