What is full-stack observability?

Full-stack observability involves associating metrics, logs, links, RUM, profiles, Kubernetes, cloud resources, alerts, and business data into the same context to explain why system anomalies occur and where they affect them.

What is the difference between full-stack observability and traditional monitoring?

Traditional monitoring usually focuses on individual systems or single-class metrics, while full-stack observability emphasizes data association across services, resources, and teams, helping teams follow from alerts to requests, logs, resources, versions, and business paths.

What data should be integrated first to build full-stack observability?

It is recommended to first integrate infrastructure metrics, application traces, critical logs, and alerts, then supplement RUM, Kubernetes events, cloud resources, profiles, and business metrics according to business scenarios.

Full-stack observability - APM logs Unified monitoring by RUM Kubernetes

The three pillars of observability

Logs

Uniformly collect logs from applications, hosts, containers, and cloud platforms, combined with structured fields, Trace IDs, and alert contexts to quickly retrieve root causes of anomalies.

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Metrics

Continuously monitor hosts, containers, services, databases, and business metrics, using trend, threshold, and anomaly detection to identify capacity risks and performance degradation.

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Traces of the link

APM Trace reconstructs the service, dependencies, and time spent on a single request, identifying slow interfaces, erroneous dependencies, and cross-service call bottlenecks.

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What is an observability platform?

What is the difference between monitoring and observability?

How to build a unified monitoring platform?

What is the difference between full-link monitoring and observable platforms?

How to choose an observability platform?

A single platform integrates all data

Logs, metrics, links, RUM, profiles, events, cloud resources, and business metrics from the system are centralized on a single platform, unified by service, environment, version, region, and responsible person, building queryable, analytical, and collaborative, observable data views.

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Trace evidence from alarms, slow requests, Pod restarts, interface timeouts, or slow page loading

Use a unified context to determine the scope of impact, boundaries of responsibility, and next steps to handle

Ready-to-use visual monitoring capability

Build real-time interactive monitoring scenarios

Unified and efficient management of your infrastructure

Comprehensive and comprehensive log monitoring and log analysis

Make distributed applications observable

Real user monitoring

Cloud dial-up real-time task feedback

Intelligent anomaly detection and comprehensive alert reach

AI AI Agent assists in analysis and troubleshooting

Observability Workflow

Starting from a single fault, string the full-stack signal into a troubleshooting path

When microservice interfaces timed out, Kubernetes Pods frequently restarted, frontend pages were blank, or order payments failed, full-stack observability did not pile up charts but placed each signal on the same timeline and the same set of object relationships.

Application performance monitoring

Moving from slow requests to service topology, trace, errors, profiles, and logs to identify interface bottlenecks.

Log monitoring and log analysis platform

Reconstruct the anomaly scene using log retrieval, structured fields, trace associations, and alert contexts.

Kubernetes monitoring

Correlate clusters, nodes, pods, workloads, events, and application links to assess release and resource risks.

Real user monitoring

Judge whether experience issues affect business by analyzing page performance, JS errors, interface time, and access paths.

Ensuring project team solutions enables efficient collaboration among development, testing, and operations

Break the bottleneck of relying solely on personal experience to resolve issues, connecting development, testing, operations, SRE, and business teams with objective data. Every alert, release, change, and fault review returns to the same factual context, reducing tool switching and disputes over responsibility boundaries.

Still using complex, time-consuming, and labor-intensive open-source systems?

Still struggling to find a suitable observable platform?

Build a unified observable platform with 'Guance'

The two main elements of a monitoring product with observable capabilities

Unified Objects: Services, hosts, containers, databases, cloud resources, and business processes can be associated

Data unification: metrics, logs, links, RUM, profiles, and events can be queried and analyzed in a unified manner

A full-stack observable platform for the AI era

650+ technology stacks and cloud service integration

Unified collection, storage, query, and display

APM, logs, RUM, Kubernetes, and business data association

View the capabilities of 'Guance' products