Incident Management
Platform
Dedicated compute
Dedicated compute keeps concurrent queries stable and complex analysis fast.
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Dedicated compute keeps concurrent queries stable and complex analysis fast.
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Logs
Collect application, host, container and cloud logs in one place. Use structured fields, Trace IDs and alert context to investigate the causes of anomalies.
Metrics
Monitor host, container, service, database and business metrics. Use trends, thresholds and anomaly detection to identify capacity risks and performance degradation.
Traces
Follow a request through services, dependencies and timings with APM traces to locate slow endpoints, failing dependencies and cross-service bottlenecks.
Follow alerts, slow requests, Pod restarts, API timeouts or slow pages to the relevant evidence.
Use shared context to assess impact, ownership and the next action.
Observability Workflow
When an API times out, a Kubernetes Pod keeps restarting, a page goes blank or a payment fails, full-stack observability connects signals on a shared timeline and through resource relationships. It goes beyond assembling charts.
Investigate slow requests through service topology, traces, errors, profiles and logs to find API bottlenecks.
Log monitoring and analyticsReconstruct incidents with log search, structured fields, trace correlation and alert context.
Kubernetes monitoringConnect clusters, Nodes, Pods, workloads, events and application traces to assess deployment and resource risks.
Real user monitoring (RUM)Use page performance, JavaScript errors, API latency and user journeys to assess business impact.
Spending too much time maintaining open-source tools?
Looking for the right observability platform?
Build a unified observability platform
Connected resources: relate services, hosts, containers, databases, cloud resources and business processes.
Connected data: query and analyze metrics, logs, traces, RUM, profiles and events together.
Connect supported technologies and cloud services
Unified collection, storage, queries and visualization
Connect APM, logs, RUM, Kubernetes and business data
Full-stack observability connects metrics, logs, traces, RUM, profiles, Kubernetes, cloud resources, events, and business data so teams can explain why a system changed and who or what was affected.
Full-stack monitoring emphasises coverage across technology layers. Full-stack observability also preserves identity, time, and resource relationships so teams can ask new questions during an unknown failure.
Not exclusively. OpenTelemetry provides open standards for telemetry generation, semantics, and collection, while a platform may also receive existing log pipelines, Prometheus, cloud APIs, RUM, and other supported sources.
