Lumigo Features
Monitoring (10)
Usage Monitoring
Tracks infrastructure resource needs and alerts administrators or automatically scales usage to minimize waste.
Database Monitoring
Monitors performance and statistics related to memory, caches and connections.
API Monitoring
Detects anomalies in functionality, user accessibility, traffic flows, and tampering.
Real-Time Monitoring - Cloud Infrastructure Monitoring
Constantly monitors system to detect anomalies in real time.
Security and Compliance Monitoring
Enables monitoring of security and compliance standards across cloud infrastructure.
Performance Baselines
Performance Analysis
Performance Monitoring
AI/ML Assistance
Multi-System Monitoring
Administration (4)
Activity Monitoring
Actively monitor status of work stations either on-premise or remote.
Multi-Cloud Management
Allows users to track and control cloud spend across cloud services and providers.
Automation
Efficiently scales resource usage to optimize spend whith increased or decreased resource usage requirements.
Auto-Scaling & Resource Optimization
Automatically scales resources based on demand and optimizes for performance and cost.
Analysis (3)
Reporting
Creates reports outlining resource, underutilization, cost trends, and/or functional overlap.
Dashboards and Visualizations
Presents information and analytics in a digestible, intuitive, and visually appealing way.
Spend Forecasting and Optimization
Ability to project spend based on contracts, usage trends, and predicted growth.
Response (3)
Dashboards and Visualization
Incident Alerting
Root Cause Analysis (RCA)
Performance (2)
Real User Monitoring (RUM)
Captures and analyzes each transaction by users of a website or application in real time.
Second by Second Metrics
Provides high-frequency metrics data.
Functionality (4)
Synthetic Monitoring
Monitors and test apps to address issues before they affect end users.
Dynamic Transaction Mapping
Provides dynamic end-to-end maps of every single transaction.
Load Balancing
Automatically adjusts resources base on application usage.
Cloud Observability
Monitors cloud microservices, containers, kubernetes, and other cloud native software.
Telemetry Collection & Ingestion - Observability (2)
Multi-Telemetry Ingestion
Ingests and processes multiple telemetry types, such as logs, metrics, and traces.
OpenTelemetry Support
Supports ingestion and standardization of observability data via OpenTelemetry protocol.
Visualization & Dashboards - Observability (3)
Service Dependency Mapping
Displays relationships between services to visualize system dependencies.
Unified Dashboard
Provides a consolidated view of system-wide telemetry in a single dashboard.
Trace Visualization
Allows users to explore and visualize distributed traces and span relationships.
Correlation & Root Cause Analysis - Observability (3)
Cross-Telemetry Correlation
Correlates logs, metrics, and traces to surface performance patterns and root causes.
Root Cause Detection
Identifies likely causes of issues using system insights and correlation logic.
Intelligent Alerting
Automatically alerts users to anomalies or critical events using contextual data.
Scalability & Ecosystem Integration - Observability (2)
Kubernetes Monitoring
Provides observability into containerized workloads and Kubernetes clusters.
Hybrid/Multi-Cloud Support
Enables observability across public cloud, private cloud, and on-prem environments.
AI Features - Observability (3)
Predictive Insights
Forecasts future system issues based on historical performance trends.
AI-Generated Incident Summaries
Summarizes incident root causes and potential fixes using generative AI.
AI Anomaly Detection
Uses machine learning to detect unusual behavior across telemetry data.
Agentic AI - Application Performance Monitoring (APM) (5)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives
Agentic AI - Cloud Infrastructure Monitoring (6)
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives
AI Automation - Cloud Infrastructure Monitoring (2)
AI-Powered Anomaly Detection
Utilizes machine learning to automatically detect and alert on unusual patterns in infrastructure metrics.
AI-Driven Insight Recommendations
Provides AI-generated insights and actionable recommendations to optimize resource performance and cost.
Agentic AI - Observability Software (7)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives


