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Welcome to Guance
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Welcome to the Guance documentation!

Guance is dedicated to providing modern monitoring and observability cloud services

Unified monitoring for cloud, cloud-native, applications, and business needs in the AI era

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Technology Stack Integration

Seamlessly connect applications, databases, infrastructure, and public cloud platforms for cross-platform data collection, analysis, and monitoring

Provides a one-stop service for log collection, parsing, indexing, storage, and retrieval, supporting full-text search, field filtering, pattern analysis, and real-time monitoring

Real User Monitoring (RUM)

Captures real user behavior data on web and mobile, records page performance and user interactions, supports session replay for issue localization, and correlates frontend and backend data for full-stack root cause analysis

How to integrate an application?

Application Performance Monitoring (APM)

Builds service topology through distributed tracing for full-stack performance monitoring. When service anomalies occur, quickly locate code-level bottlenecks and resolve issues such as slow queries and API timeouts

Enable trace data collection

Get Started

01 What is Guance?

A one-stop observability platform covering infrastructure, APM, RUM, logs, Agent/LLM monitoring, and more, meeting comprehensive monitoring needs in the cloud-native and AI era

02 Quick Start

After registering for Guance, install DataKit and onboard data, then configure views in dashboards and other visual interfaces to directly view monitoring results

03 Start Data Collection

Start data collection with DataKit: after one-click installation, configure the required collectors and restart the service to start receiving data

Core Features

As the core module for data visualization, it includes multiple display formats such as dashboards (comprehensive data monitoring views), explorers (custom data query interfaces), and notes (text and graphics combined), supporting flexible construction of business monitoring scenarios

Records of abnormal states or important changes at specific time points, automatically triggered by monitors and SLO rules, containing status levels, timestamps, sources, and detailed context, supporting fault discovery and root cause localization

Aggregates anomalies from Intelligent Inspection, monitor alerts, and manual creation, presents complete context through correlation analysis, and supports team collaboration for event status tracking and process recording, ultimately achieving closed-loop management of incident events

Provides unified monitoring of infrastructure components such as hosts, containers, cloud resources, and network devices, collects performance metrics including CPU, memory, disk, and network in real time, and visualizes component relationships and health status through resource topology diagrams

Time-series system state data with four elements: name, value, tags, and timestamp. Supports automatic collection, storage, and multi-dimensional analysis, covering full-stack monitoring needs from infrastructure and application performance to business operations

Synthetic Monitoring

Simulates user requests through globally distributed monitoring nodes to detect the availability and response performance of websites, APIs, ports, and other services, providing multi-region availability statistics, performance comparison analysis, and fault alerts

Security Monitoring

Continuously monitors system security status, including security event log analysis, vulnerability scan result monitoring, anomalous login detection, and compliance policy checks, providing security posture assessment and risk alerts

An integrated monitoring system that detects data anomalies through monitors and triggers alerts, managed with alert policies and notification functions, assisted by mute and SLO for fine-grained governance

Agent Monitoring

A dedicated monitoring solution for Agent and LLM applications, covering the full chain of model, skill, and tool calls through full-stack tracing, quality evaluation, and cost measurement, ensuring AI application stability and cost control