Sold by: Guance
Deployed on AWS
Guance (www.guance.com) is monitoring and observability infrastructure built for the AI era. Powered by the "four unifications" of data, Guance delivers end-to-end observability across both traditional systems and AI Agents. With its enterprise-grade intelligent Agent, Obsy AI, Guance closes the loop of "AI senses. Humans decide. Agents act."
Overview
Guance (<www.guance.com >) is monitoring and observability data infrastructure for the AI era, built for both humans and intelligent Agents to consume. Through unified data collection, unified tagging, unified storage, and a unified interface, Guance provides an end-to-end observability data foundation for development, operations, testing, business teams, and AI Agents. Built on this foundation, Obsy AI is Guance's self-developed enterprise-grade observability Agent, ready to use out of the box for SRE, DevOps, security, testing, FinOps, and other teams. It runs 24/7 to safeguard your systems and is designed for long-term, stable operation in enterprise production environments. Fully controllable, auditable, and governable, Obsy AI acts as a trusted observability digital worker by your side. It can autonomously handle a wide range of scenarios, including alert response, change rollback, system performance optimization, resource cost governance, and security vulnerability remediation. Every action comes with a complete evidence chain. High-risk operations automatically trigger tiered approvals, and incident handling supports one-click rollback. Guance keeps both system health and AI Agent behavior under control. AI senses. Humans decide. Agents act.
Highlights
- Unified Data Foundation | DataKit & GuanceDB: DataKit provides full-domain data collection, standardized tagging, GuanceDB delivers unified multi-model storage, and the integrated console brings everything together. Across all environments, high-cardinality metrics, logs, traces, business data, and AI Agent behavior data are ingested, governed, and analyzed in one place, creating a single source of truth shared by humans and Agents.
- Digital Workforce for Observability | Obsy Agent Team: Guance's self-developed observability Agents run 24*7 and can autonomously handle a wide range of scenarios, including alert response, rollback, performance optimization, cost governance, and security remediation. With built-in evidence chains, tiered approvals, and one-click rollback, they deliver a controllable, auditable, and governable production environment, fully operationalizing the loop of "AI senses. Humans decide. Agents act."
- AI-Native Observability | LLM & Agent Full-Trace Observability: Guance natively supports runtime observability for LLMs and AI Agents, including traces, token consumption, Agent Skill usage, Tool calls, abnormal behavior, and more. It makes the cost, performance, and security risks of AI Agents observable, auditable, and controllable just like traditional services. Guance supports mainstream Agents such as Openclaw, Hermes, and Codex.
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Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/unit |
|---|---|---|
Infrastructure | Infrastructure Monitoring ( 1k / day ) | $0.09 |
Logs | Logs ( 1 million / day ) | $0.15 |
Network Monitoring | Network Monitoring ( Each reported network data host / day ) | $0.29 |
APM / LLM ( trace ) | APM ( 1 million trace / day ) | $0.29 |
RUM | RUM ( 10k PV / day ) | $0.10 |
Synthetic Tests | Synthetic Tests ( 10k API dial / day ) | $0.143 |
Session Replay | Session Replay ( 1k sessions / day ) | $0.35 |
Triggers | Triggers(10 k / day ) | $0.14 |
Common | Common | $0.01 |
APM / LLM ( profile) | APM / LLM ( 10k profile / day ) | $0.03 |
Dimensions summary
You pay only for what you use across 18 independent monitoring dimensions. Each dimension bills separately by daily volume, so you scale each one to your own needs. Data-volume dimensions charge per gigabyte per day, including Data Forward (Internal and External), Sensitive Data Scanner, Central Pipeline, and Security. Count-based dimensions charge per unit block per day, such as Infrastructure per 1k, Logs per million, APM traces per million, RUM per 10k page views, Synthetic Tests, Session Replay, Triggers, Error, and profiles. Report and IVR bill per occurrence. Network Monitoring and Common round out the set.
Top-of-mind questions for buyers
These dimensions bill per gigabyte of data processed per day. Data Forward separates internal and external routing, so data sent to external storage or message queues meters differently from data kept inside the platform. Sensitive Data Scanner also bills per gigabyte scanned per day.
Infrastructure Monitoring bills per 1,000 time series per day, not per host. A time series is one tracked metric stream. Network Monitoring works differently, charging for each reported network data host per day. So one host can generate many infrastructure units but counts once for network data.
All dimensions bill independently and add up on one invoice. Log-heavy or high-trace workloads push Logs (per million/day) and APM traces (per million/day) up. Data-volume dimensions grow with gigabytes moved. You only accrue charges on dimensions you actually use, so unused features add nothing.
www.guance.com
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Support
Vendor support
Time:Work Day 9:00 - 18:00 UTC+8 Service scope: self-service activation, observation expert guidance, help documents and technical practices, developer resources, data export, data early warning, electronic invoices, etc. Hotline:00852 - 66419560 Email:guanceglobal@guance.com
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By Guance
By SolarWinds
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Unified Data Collection and Storage
DataKit provides full-domain data collection with standardized tagging, while GuanceDB delivers unified multi-model storage supporting high-cardinality metrics, logs, traces, business data, and AI Agent behavior data in a single repository.
Autonomous Agent Operations
Obsy AI agent autonomously handles alert response, system rollback, performance optimization, resource cost governance, and security vulnerability remediation with complete evidence chains and tiered approval workflows.
LLM and AI Agent Observability
Native runtime observability for large language models and AI Agents including trace collection, token consumption tracking, Agent Skill usage monitoring, Tool call tracking, and abnormal behavior detection.
Multi-Environment Data Governance
Unified tagging and governance framework across all environments enabling consistent data ingestion, analysis, and control of observability data from diverse sources.
Audit and Rollback Capabilities
Complete evidence chain documentation for all agent actions with one-click rollback functionality and automatic tiered approval triggers for high-risk operations in production environments.
AI-Powered Root Cause Analysis
Automatically investigates alerts and pinpoints root causes with 5x faster analysis capabilities.
Natural Language Query Interface
Enables querying of observability data using conversational natural language to identify issues and receive actionable insights.
Real-Time Anomaly Detection
Detects system anomalies in real-time to prevent incidents before they impact users.
OpenTelemetry Integration
Supports standardized OpenTelemetry integration for unified data collection across logs, metrics, and traces in cloud-native environments including Kubernetes, serverless, and microservices.
Multi-Tiered Storage Architecture
Implements multi-tiered storage and data management capabilities to optimize telemetry costs and achieve 30% to 50% cost savings.
Unified Observability Platform
Comprehensive visibility across applications, infrastructure, logs, databases, networks, and digital experiences through a single-pane-of-glass interface
AIOps and Machine Learning
AIOps enhanced with machine learning capabilities to simplify management of distributed environments and automatically prioritize alerts to reduce alert fatigue
Automated Instrumentation and Dependency Mapping
Automated instrumentation with dependency mapping and service relationship views to identify multi-level relationships across services
Open Source and Container Support
Support for open-source frameworks, container technologies, and third-party integrations for cloud-native environments
Rapid Deployment and Integration
Quick installation with automated setup and easy integration with SolarWinds Hybrid Cloud Observability for reduced time to value
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