Incident Management
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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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Why observability matters
Observability helps teams understand why a system is behaving abnormally, beyond simply detecting a problem. It connects metrics, logs, traces, RUM, profiles, Kubernetes, cloud resources, alerts, and business metrics so development, testing, operations, SRE, and business teams can work from the same evidence.
What observability helps you achieve
Improve productivity through digital transformation
Observability gives teams a shared language for systems, user experience, and business processes. Bringing development, testing, operations, and business teams into the same data context supports continuous improvements in product quality, service reliability, and operational efficiency.
Improve software engineering quality
During development and releases, applications can encounter slow requests, failing dependencies, API timeouts, JavaScript errors, slow database queries, and resource bottlenecks. Traces, logs, profiles, and version context help developers investigate these issues without relying solely on reproductions and guesswork.
Improve reliability and maintainability
Track system health and capacity trends to identify risks such as Kubernetes resource shortages, rising database load, queue backlogs, network latency, and third-party API failures.
Diagnose issues and identify root causes
Correlate metrics, logs, traces, frontend experience, alerts, and business data to build the context needed for an investigation. This helps teams reduce MTTR and retain the evidence behind their response for future reviews.
Who benefits from an observability platform?
Use a consistent approach to data across development, testing, staging, and production. Shared metrics, logs, traces, and user experience data help teams validate releases, troubleshoot incidents, optimize capacity, and improve service quality.
Developers
Investigate slow APIs, service errors, and database bottlenecks with APM traces, logs, profiles, and dependency context in one view, helping you improve code and service performance.
Test engineers
Compare API performance, error rates, resource consumption, and critical journeys before and after a release. Share traces, logs, and environment details directly with developers instead of relying only on screenshots and verbal descriptions.
Operations teams & SREs
Monitor hosts, containers, Kubernetes, cloud resources, alerts, and changes through a unified production view. Use the evidence to determine impact and prioritize your response.
Business teams
Understand service quality through application performance, user experience, and business events. Check whether page speed, API latency, or system errors affect critical steps such as registration, ordering, payment, and form submission.
How to build an observability platform
Start with recurring incidents rather than rebuilding every monitoring system at once. Unify data collection for critical systems, then develop resource models, alert response, troubleshooting workflows, and incident review practices.
Understand how observability differs from traditional monitoring and determine which data types and platform capabilities your organization needs.
Build unified monitoringBring signals from Prometheus, ELK, SkyWalking, cloud monitoring, and business systems into a shared context.
Connect application performance monitoringUse service topology, traces, logs, and profiles to locate slow requests, failing dependencies, and performance bottlenecks.
Connect 650+ integrationsUse DataKit and integration templates to collect data from hosts, containers, middleware, databases, cloud services, and custom sources.
