Infrastructure¶
Guance provides unified monitoring for all underlying computing resources that support application operations. Including but not limited to:
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Physical machines and virtual machines
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Containers and Kubernetes clusters
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Network devices and services
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Various cloud services
Guance uses DataKit to uniformly collect metrics, logs, and object data from infrastructure such as hosts, containers, and cloud services. It automatically builds dynamic dependency relationships between components, forming a visual infrastructure topology. This topology clearly shows the actual running locations and relational status of resources like services, containers, and host machines, providing users with operational insights from a global down to a granular level.
Based on a unified tagging system and flexible search capabilities, the platform supports users in quickly locating target resources and can correlate data from different sources such as metrics, traces, and logs. Through smooth cross-data-type navigation and contextual linkage, users can rapidly trace the root cause of issues, enabling efficient troubleshooting and performance optimization.
Getting Started¶
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Collects 200+ system-level metrics in real-time, covering in-depth performance data like CPU steal time, memory swap activity, disk IOPS, etc. Precisely identifies resource contention issues in virtualized environments and provides real-time data support for capacity planning.
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Automatically builds cluster resource topology maps, monitors Pod lifecycle status and resource quota utilization in real-time, accurately tracks HPA elastic scaling efficiency, and effectively warns of container restart events caused by insufficient resources.
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Deeply monitors process-level resource consumption, establishes correlations between processes and business logic, and supports quick drilling down from anomalous processes to corresponding application performance traces and log data.
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Automatically collects performance metrics for mainstream databases (e.g., MySQL, Redis, PostgreSQL) in a non-intrusive manner. Monitors key performance data like QPS, connection counts, and slow queries in real-time.
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Utilizes eBPF technology for non-intrusive collection of network traffic data. Comprehensively monitors network performance indicators such as TCP retransmissions and connection anomalies. Visualizes service dependencies through real-time topology.
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Automatically integrates cloud provider APIs for unified monitoring of managed services like RDS and load balancers. Correlates with cloud billing data to achieve dual control over cost and performance.