AI-Driven Observability: 8 Better Insights

Enterprise IT goes beyond traditional monitoring as AI-driven observability helps companies manage complex infrastructure and respond to incidents faster.

This week’s LogicMonitor Elevate event in Chicago focused on bringing together operational data, AI automation and governance to address challenges in hybrid environments. The results become tangible. GlobalFoundries reported a 98% reduction in alarm noise through Edwin AI, while managed service providers highlighted improvements in incident resolution and technical efficiency. These developments reflect LogicMonitor’s push toward autonomous IT, but questions remain about adoption, trust and operational monitoring.

“Observability is becoming an important foundation for both human decision-making and autonomous workflows,” said Paul Nashawaty, practice leader and principal application development analyst at theCUBE Research. “The opportunity is to connect performance, availability, resource utilization and cost so that engineering teams can understand the operational trade-offs behind the problem.”

Nashawaty spoke to technology managers, customers and partners during the event. TheCUBE’s coverage examined how Edwin AI, OpenTelemetry, application dependency mapping and controlled automation are transforming enterprise operations. Conversations also covered the growing importance of digital experience monitoring, the changing role of managed service providers, and the practical challenges of moving AI from experimentation to production. (*Disclosure below.)

Here are eight key takeaways from the event:

1. LogicMonitor’s AI strategy shifts observability to controlled automation.

Enterprise observability goes beyond static dashboards and endless alerts as AI-driven operations require more context, automation and control. Steven Dickens, CEO of HyperFRAME Research, joined theCUBE Research’s Nashawaty to evaluate LogicMonitor’s keynote announcements and its five strategic pillars, including unified context, AI-driven action and trust. The discussion highlighted how OpenTelemetry, Edwin AI and Catchpoint help shape LogicMonitor’s approach to connecting complex hybrid environments and delivering actionable insights directly into existing workflows. Dickens also emphasized that customer adoption, effective governance and execution will ultimately determine whether LogicMonitor can translate its AI roadmap into measurable operational value.

Find out more from Dickens and Nashawaty in their full interview on theCUBE.

2. Autonomous IT is gaining ground as AI governance and trust take precedence.

Organizations are turning to autonomous IT to reduce operational complexity, automate incident resolution, and build trust in AI-driven systems. An advanced approach that starts with trustworthy, low-risk automation can help companies expand AI capabilities in increasingly complex environments, according to Karthik Sj (pictured left), Chief Artificial Intelligence Officer, and Garth Fort (right), Chief Product Officer of LogicMonitor. The company’s latest Edwin AI enhancements expand these capabilities through multi-agent investigations, integrations into existing workflows, and controlled automation. Catchpoint integration and governance controls further support this transition by improving visibility into application performance while maintaining control of autonomous agents.

Don’t miss the full interview on theCUBE.

3. AI adoption drives workforce transformation and measurable business results.

Successful AI transformation requires more than just the adoption of new technologies, with employee trust, leadership and organizational change playing a critical role in adoption. LogicMonitor Chief Performance Officer Alyeneschneidewind shared how the company achieved 95% adoption of ChatGPT among its employees within four months and saw employees create more than 2,000 custom GPTs in the first year. This internal transformation has shifted to redesigning workflows and measuring business results, including an AI sales assistant that saves employees half a day each week. Governance, cross-functional collaboration and new approaches to people development are also helping the company rethink how teams work and how AI investments translate into business value.

Find out more in the full conversation on theCUBE.

4. AI-powered managed services shift focus on business outcomes.

Managed service providers are rethinking traditional IT operations as AI automation creates opportunities to reduce costs, improve incident resolution, and free up technical teams for higher-value work. According to John Grosshans, president of field operations at LogicMonitor, and Tim Wheeler, chief artificial intelligence officer at Bell Techlogix Inc., AI-powered observability and autonomous workflows are helping companies move beyond reactive support to more proactive service delivery. The shift is also changing the role of managed service providers, with a greater focus on measurable business results, customer relationships and proactive problem solving.

Check out the full discussion on theCUBE.

5. Breaking down IT silos creates a path to autonomous operations.

Fragmented IT environments are forcing organizations to rethink how they manage observability, automation and service delivery across hybrid infrastructures. According to Ryan Crosby, vice president of intelligent operations sales at AHEAD, consolidating disparate tools and standardizing operations can help companies improve efficiency and accelerate AI adoption. One customer reduced their technology footprint from 72 tools to seven platforms, simplifying their support model and creating a foundation for greater automation. Building toward autonomous IT also requires executive leadership, strong governance, and an integrated approach that combines observability with incident management, change control, and automated remediation.

Find out more in the full theCUBE interview.

6. AI agents speed incident resolution and improve customer retention.

AI is changing the economics of managed services as providers move from resolving incidents to preventing them and demonstrating measurable business value. According to Kyle Hill, chief technology officer of ANS Group Ltd., and Steve Smith, CTO of cloud services at Specialist Computer Centers PLC, faster resolution times, improved service level agreements and increased customer loyalty are among the benefits of adopting AI. At ANS, the introduction of Edwin AI improved technical efficiency and customer retention, while Smith highlighted an AI agent that identified a technical issue in about three minutes after engineers had spent 40 to 50 hours investigating it. Building customer trust in autonomous IT remains a gradual process. Governance, compliance and proven results help managed service providers expand automation while maintaining control.

Check out the full conversation on theCUBE.

7. AI-driven observability reduces alert noise by 98% at GlobalFoundries.

To prevent disruptions in semiconductor manufacturing, potential infrastructure problems must be identified before they impact production. An observability modernization initiative at GlobalFoundries US Inc. achieved a 98% implementation rate in just six months, with Edwin AI reducing alert noise by 98%, according to Vishal Mehra, chief information officer. The company is also consolidating its observability tools by using dependency mapping to understand legacy applications and integrating AI-driven insights with ServiceNow to improve incident management. With executive support and a phased automation approach, GlobalFoundries is working toward autonomous IT operations that can detect potential failures and enable preventative actions before costly production disruptions occur.

The full interview is available on theCUBE.

8. Five pillars of AI-driven observability point to autonomous IT.

Enterprise observability moves beyond traditional monitoring to a model that combines telemetry, operational context and driven AI to improve application reliability and incident response. In his final analysis at Elevate, Nashawaty highlighted five priorities shaping this transition: enterprise data foundations, unified context, AI-driven action, integrated experiences, and trust and governance. OpenTelemetry, Edwin AI, and deeper integration into existing workflows help organizations connect infrastructure performance to business impact while reducing alert noise and improving root cause analysis. The next phase of observability will depend on marrying operational evidence with informed decisions and controlled automation to enable companies to move from AI experiments to production-ready autonomous operations.

Find out more in the full analysis on theCUBE.

Here’s more of SiliconANGLE and theCUBE’s coverage of LogicMonitor’s Elevate event:

https://www.youtube.com/watch?v=videoseries

(*Disclosure: TheCUBE is a paid media partner for LogicMonitor’s Elevate event. Neither LogicMonitor, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over theCUBE or SiliconANGLE content.)

Photo: SiliconANGLE