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Data Sources and Analysis

Relvy’s power comes from its ability to understand and correlate multiple types of observability data. The platform can analyze logs, metrics, traces, and events from your entire observability stack, providing a unified view of your production environment.

Logs

Structured and unstructured log analysis, pattern recognition, and log correlation across services and time periods.

Metrics

Time-series data analysis, anomaly detection, and cross-service correlation to identify impact patterns.

Traces & Spans

Distributed tracing analysis, span correlation, and service dependency mapping across microservices.

Events

Infrastructure, application, and deployment event correlation for incident investigation and timeline reconstruction.

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Cross-Correlation

Relvy’s true strength lies in its ability to correlate different types of data—events, traces, logs, and metrics—across your stack. This enables Relvy to surface root causes and patterns that would be impossible to find by looking at a single data source in isolation.

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Integrations

Relvy integrates seamlessly with your existing observability and collaboration tools, so you can get started quickly without changing your stack. Supported integrations include:

Datadog

Logs, metrics, and traces from Datadog’s observability platform.

Elasticsearch

Centralized log management and search with Elasticsearch.

AWS

Cloud infrastructure metrics, logs, and events from AWS services.

New Relic

Application performance monitoring and traces from New Relic.

Grafana

Visualization and dashboards from Grafana.

ObserveInc

Unified observability data from ObserveInc.

Prometheus

Time-series metrics and alerting from Prometheus.

Slack

Incident notifications and collaboration via Slack channels.