LogicMonitor Dexda offers contextualized data and observability capabilities

LogicMonitor announced that the company is bridging the AIOps gap with the launch of Dexda, an AI solution for hybrid observability.

Using machine learning and Natural Language Processing (NLP) to automate insights and deliver a contextualized experience, LogicMonitor’s Dexda empowers ITOps teams to effortlessly identify problems, determine the root cause of those problems faster than ever before, and prevent events from exploding into business-critical incidents.

“Being on the bleeding edge of technology requires shifting the organizational mindset from reactive responses to proactive insights, getting comfortable with humans leveraging machines for greater agility and innovation,” said Christina Kosmowski, CEO, LogicMonitor. “Our users crave superior anomaly detection, predictive analytics, and intelligent alerting – where we are best in class. Dexda is the latest step in the evolution of our AIOps technologies. Now, we are advancing Generative AI for solving customer challenges, making LogicMonitor even more user-friendly as a co-pilot.”

LogicMonitor’s AI capabilities

Without the superior real-time data access LogicMonitor provides, the journey from hybrid observability to AIOps can’t happen. Based on LogicMonitor’s research report, 50% of IT leaders doubt the readiness of their IT infrastructure for AI. With Dexda, LogicMonitor offers:

• Robust AI capabilities through the application of sophisticated algorithms on historical and real-time data to provide purpose-built, layered intelligence for faster resolutions. LogicMonitor first introduced AI into its platform with its LM Intelligence feature within the LM Envision platform.
• Using AI machine learning, LM Intelligence acts as an “early warning system” for IT and Cloud operations by providing dynamic thresholding, anomaly detection, forecasting and more, empowering teams to reach a significantly lower mean time to resolution (MTTR) and reduce risks to the business.

With the right insights, ‘man and machine’ can learn to work together to orchestrate a comprehensive, context-rich view of a business’ infrastructure. This context-rich view combined with automation results in thriving AIOps and ultimately a transformed company culture.

Dexda facilitates the AIOps leap

Dexda ingests events from LM Envision to transform them into contextualized insights. The advanced machine learning techniques automatically correlate data to identify and alert based on time, resources, and pattern disruption. Dexda users can resolve critical issues faster than their competitors with these capabilities:

• Reduced alert noise – Advanced machine learning techniques, contextual enrichment capabilities, and deduplication efforts filter through thousands of daily events to produce succinct alerts for the most critical incidents, and drive down MTTR
• ServiceNow ready – Includes a seamless bi-directional integration with ServiceNow Incident module to fit correlated insights into standard IT workflows. ServiceNow CMDB data automatically enriches Dexda alerts to drive additional context for alert correlations
• Adaptive correlation – Avoid delays in escalating insights to ServiceNow by automatically re-clustering alerts into new insights when a more optimal clustering option is found
• Extensible correlation – Customizable user-defined correlation models target both the alert and enriched CMDB data, based on what makes sense for the business
• MSP ready – Now supports multi-tenancy with correlations scoped to each tenant

Dream destination: Intelligence at the ege

“While some organizations have been using AI-powered capabilities in IT operations for several years, increasingly sophisticated applications of AI are emerging that have the potential for notable impact when it comes to solving problems in complex technology environments,” said Nancy Gohring, research director for IDC’s Enterprise System Management, Observability and AIOps program. “Some of the capabilities that are key to enabling much faster time to resolution include intelligent data correlation, context awareness and smart adoption of automation techniques.”

From the start, LogicMonitor’s unified observability strategy has been built on a foundation of practical AI. Moving forward, intelligent edge technology will be crucial for businesses to compete in the effort to maximize efficiencies and reduce latency.