Agentic AIOps in Action: LogicMonitor, IBM, and Red Hat Deliver Self-Healing IT
A practical look at how LogicMonitor, IBM, and Red Hat have made self-healing IT real—through agentic AI, contextual awareness, and orchestrated automation.
Why traditional incident response can’t keep pace with modern hybrid infrastructure and how it’s costing organizations millions
How LogicMonitor (contextual awareness), IBM watsonx (solution synthesis), and Red Hat Ansible Automation Platform with Ansible Lightspeed (orchestrated execution) work together to create self-healing systems
How your organization can implement autonomous operations through an early access program launching soon
Your most skilled engineers shouldn’t be spending nights and weekends piecing together root causes of outages. Yet many organizations still rely on manual incident response across sprawling hybrid and multi-cloud environments. The result: slower resolution times, frustrated customers and lost revenue that can reach up to $1 million per hour according to IDC.
At LogicMonitor, we believe the answer isn’t just better monitoring. It is systems that can heal themselves. That’s why we’re excited to share that LogicMonitor and IBM are working together to bring autonomous, intelligent automation to enterprise IT.
This relationship combines the power of LogicMonitor’s Edwin AIwith IBM watsonx Code Assistant and Red Hat Ansible Automation Platform, creating a closed loop of observability, diagnosis, and automated remediation. It is a step toward what we call agentic AIOps, where AI doesn’t just surface insights but also takes action on your behalf.
The Problem with Manual Incident Response
Today’s IT operations landscape is defined by complexity. Infrastructure sprawls across on-premises environments and multiple cloud providers, producing a constant stream of monitoring data. Operations teams face an overwhelming volume of alerts, events, and metrics, and most organizations still rely heavily on manual processes.
When incidents occur, engineers act like digital detectives. They piece together fragments of evidence from disparate systems, convene cross-team war rooms, and work command by command to restore services. Diagnosis often consumes the majority of resolution time, leaving little room for actual remediation. For complex failures, troubleshooting alone can take hours.
This model is costly and risky. Outages drag on, mean time to resolution (MTTR) breaches service level agreements, and customer experiences suffer. Every minute of downtime compounds business and reputational impact. In highly regulated industries, downtime can even lead to compliance violations and penalties. Most critically, the gap between infrastructure complexity and human capacity continues to widen. Incremental workflow improvements are not enough. A fundamentally different approach is required: one that shifts from human-centered remediation to systems that can heal themselves.
Anatomy of the Self-Healing Loop: The Three-Layer Intelligence Stack
The collaboration between LogicMonitor, IBM, and Red Hat delivers what operational teams have long sought: a continuous, autonomous remediation pipeline that minimizes human intervention. This integrated system, part of what we call “agentic AIOps,” functions through three complementary layers that together create a seamless intelligence-to-action workflow.
Layer 1: Contextual Awareness (LogicMonitor)
At the foundation lies LM Envision, LogicMonitor’s hybrid observability platform. By unifying metrics, logs, events, and traces across the IT environment, LM Envision captures relationships between systems and establishes performance baselines.
Built into the platform is LogicMonitor’s AI agent for ITOps, Edwin AI. Edwin continuously processes all this observability data to filter out noise, identify likely root causes, assess the blast radius and recommend the best remediation path. If an existing automation playbook can solve the issue, Edwin suggests or triggers it immediately, shortening resolution time.
Layer 2: Solution Synthesis (IBM watsonx)
If no existing playbook is available, Edwin activates IBM watsonx Code Assistant, which transforms understanding into action. Leveraging IBM’s Granite foundation models, watsonx analyzes Edwin’s findings and crafts precise Red Hat Ansible Automation Playbooks with Ansible Lightspeed tailored to the specific environmental conditions. These are not generic fixes but context-specific solutions that can be reused and refined over time.
Layer 3: Orchestrated Execution (Red Hat Ansible)
Finally, Red Hat Ansible Automation Platform executes the remediation. Its enterprise-grade orchestration delivers reliability across hybrid cloud environments, from legacy on-premises systems to modern cloud workloads.
This creates a closed loop: Edwin detects and diagnoses, watsonx translates insight into automation, and Red Hat Ansible Automation Platform executes the fix. The process is fully auditable, governed, and designed to keep human operators in control while reducing manual intervention.
What This Means for Enterprises
The integration of LogicMonitor, IBM, and Red Hat technologies is designed to unlock measurable improvements for IT operations:
Predictive resilience: Systems anticipate issues and prevent outages before they occur.
Faster resolution: Automated detection, diagnosis, and execution shrink MTTR and reduce downtime.
Scalable impact: Automation becomes accessible to IT staff of all skill levels, not just specialists.
Continuous learning: Each resolved incident enriches the platform’s knowledge base, making responses smarter over time.
Strategic focus: Skilled engineers spend less time firefighting and more time innovating.
Early adopters are already seeing results. Managed service providers, for example, are using the joint solution to reduce repetitive tasks and empower a wider range of employees to run automation confidently.
“This is automation with frontier intelligence,” said Karthik SJ, General Manager of AI, LogicMonitor. “By combining the LogicMonitor Envision observability platform with watsonx Code Assistant and Red Hat Ansible Automation Platform, we give customers a trusted ally designed to anticipate issues, resolve them autonomously, and free teams to focus on building the future.”
Get Ready for the Self-Healing Data Center
Stay tuned for more customer stories, new capabilities, and opportunities to gain early access to this solution. In the meantime, explore how Edwin AI and LogicMonitor’s hybrid observability platform can help your team start its journey toward autonomous operations today.
Luca Gianaschi leads strategic partnerships at LogicMonitor. With roots in consulting, product management, and global BD & alliances across enterprise tech, he focuses on building partnerships that power LogicMonitor’s next stage of growth.
Disclaimer: The views expressed on this blog are those of the author and do not necessarily reflect the views of LogicMonitor or its affiliates.
