What is LogicMonitor?
LogicMonitor is an AI-powered observability platform that gives enterprise IT teams unified visibility across hybrid infrastructure, cloud environments, and digital services. It collects and analyzes metrics, logs, and event data across on-premises systems, multi-cloud deployments, containers, networks, databases, and applications. The platform runs an AI agent called Edwin AI that correlates alerts, identifies root causes, and initiates remediation across connected tools. Teams can access observability data through customizable dashboards, a resource explorer, and integrations with over 3,000 tools across their tech stacks. LM Envision is the underlying platform architecture that powers the full observability and AIOps workflow.
LogicMonitor Video
Features & Benefits
- Infrastructure Monitoring: monitor servers, networks, virtual machines, databases, storage, SD-WAN, and physical hardware across hybrid environments. Configuration monitoring tracks changes across managed devices.
- Cloud & Multi-Cloud Monitoring: monitor workloads across AWS, Google Cloud Platform, Microsoft Azure, and Oracle Cloud Infrastructure. Container monitoring covers Kubernetes and related environments. AI workload monitoring tracks AI service performance specifically.
- Application Performance Monitoring: track app health, response times, and error rates across internal services and APIs to detect performance degradation before it affects end users.
- Website & SaaS Monitoring: monitor external websites and third-party SaaS services for availability and performance. Synthetic monitoring, real user monitoring (RUM), and internet performance monitoring (IPM) extend visibility to user-facing experiences and internet dependencies.
- Log Management & Analytics: collect, search, and analyze log data alongside metrics in the same observability platform for correlated incident investigation.
- Edwin AI Event Intelligence: correlate and compress thousands of alerts into prioritized incidents. AI enriches each incident with topology context and CMDB data before surfacing it to the team.
- Edwin AI Agent: investigate incidents through a conversational interface. The agent checks logs, metrics, recent deployments, and past incidents simultaneously to identify root cause and recommend next steps in plain language.
- Edwin AI Automation: find or generate a remediation action for a detected issue and execute it across the environment. Workflows run with approvals, audit logging, rollback, and validation built in.
- Anomaly Detection: detect unusual patterns in metrics data before they escalate into incidents. The system identifies deviations based on learned baselines.
- Dynamic Thresholds: set alert thresholds automatically based on historical patterns rather than static values. Thresholds adjust over time as behavior changes.
- Root Cause Analysis: identify the source of performance issues through automated correlation of signals across infrastructure, applications, and logs.
- Service Insights & Topology Mapping: map services and their dependencies automatically. Topology context attaches to incidents to show what systems and business services an issue may affect.
- Resource Explorer: search, filter, and browse every monitored resource and its relationships across the hybrid IT environment.
- Forecasting & Capacity Planning: use AI-driven forecasting to project resource usage trends and plan capacity before constraints cause issues.
- Customizable Dashboards: build and share real-time dashboards scoped to specific teams, services, or SLAs.
- Integrations: connect with over 3,000 tools spanning observability, APM, ITSM, security, and CMDB. Includes bidirectional sync with ITSM platforms.
What can LogicMonitor do?
- Monitor hybrid cloud and on-premises infrastructure in one platform
- Detect anomalies in server and network performance
- Correlate IT alerts across multiple monitoring domains
- Identify root cause of infrastructure incidents
- Monitor Kubernetes and container environments
- Track AWS, Azure, and Google Cloud workload performance
- Monitor network devices and SD-WAN performance
- Analyze log data alongside infrastructure metrics
- Monitor application performance and API response times
- Monitor SaaS application availability
- Automate IT incident response and remediation workflows
- Forecast infrastructure capacity and resource usage
- Monitor real user experience and web performance
- Route and escalate incidents to the right team
Real-World Applications
IT operations teams managing large hybrid environments may find the observability platform particularly useful during high-incident periods. When thousands of alerts fire across network, cloud, and application layers simultaneously, the AI correlation layer can compress those into a small number of actionable incidents with root cause context already attached. This kind of alert noise reduction can make the difference between a fast recovery and hours of manual triage.
Financial services firms and healthcare organizations that run always-on infrastructure may rely on the observability platform to maintain continuous monitoring across data centers and cloud regions at the same time. The service topology mapping can help these teams understand which business services are affected when a database or network component shows degraded performance, so the right people get notified with the right context.
Managed service providers overseeing multiple client environments can use the observability platform to track infrastructure health across separate accounts from a single view. Automated incident routing and ITSM integration may reduce the manual handoffs that slow down resolution across large client portfolios.
DevOps and CloudOps teams moving workloads to multi-cloud environments can monitor container performance, cloud resource utilization, and application response times in the same observability platform used for on-premises infrastructure. Capacity forecasting may help these teams plan resource allocation ahead of demand spikes rather than reacting to them after the fact.
