Shared agentsLogs
Ingest and query trillions of log lines with familiar SQL: no indexing tax, no surprise storage bills.
- Live tail
- Full-text search
- SQL queries
- Parquet storage
DO Sense//Leap for Resilience
Open-source, unified observability for the AI era
Logs, metrics, traces and AI telemetry on one engine, at full resolution and kept as long as you need.
Unmatched efficiency
Columnar storage and a Rust query engine: less storage and compute per GB.
Unified observability
Logs, metrics and traces auto-correlated across every layer.
Open source at scale
An open core you can read, run and extend, built for petabyte workloads.
No vendor lock-in
Your bucket, your collectors, your OpenTelemetry data.
//Leap Today withDataObserve
Pick a signal and see Sense at work
Metrics
Store and query Prometheus-compatible metrics at any scale, on the same engine as your logs.
- PromQL
- Remote write
- Full resolution
- Long retention
Traces
Follow every request across services with full trace context, correlated with logs and metrics.
- OpenTelemetry
- Service maps
- No sampling
- Span search
Dashboards
Drag-and-drop panels across every signal, or bring your existing Grafana boards straight over.
- Live panels
- Variables
- Grafana import
- Sharing
Alerts
Real-time and scheduled alerts on logs, metrics and traces, routed to Slack, PagerDuty, email and more.
- Thresholds
- Anomalies
- Routing
- Silences
AI SRE
An always-on agent that triages incidents, correlates the root cause and drafts the postmortem.
- Triage
- Root cause
- Timelines
- Postmortems
AI Assistant
Ask questions in plain language across every log, metric and trace, and get an answer, not a query.
- Plain language
- Dashboards
- Alert setup
- Explanations
LLM Observability
Trace prompts, completions, token usage and cost across your LLM applications to debug quality and spend.
- Prompts
- Token cost
- Quality scores
- Tool calls
SLOs
Define service-level objectives, track them continuously and alert on error-budget burn.
- Error budgets
- Burn rate
- Targets
- Reports
RUM
See how real users experience your app: sessions, Core Web Vitals and errors, linked to backend traces.
- Sessions
- Web Vitals
- JS errors
- Replays
Synthetic monitoring
Monitor your applications and APIs from the outside in, from global and private locations.
- API checks
- Browser journeys
- Global locations
- Private locations
//One platform, every workload
Correlate between environments and signalsacross every source with the built-in correlation engine.
Kubernetes
Full-stack visibility across every cluster
Deploy the collector with one command. Container logs, cluster events and metrics arrive together, plus zero-code traces for workloads already running.
- Container logs, Kubernetes events and cluster metrics from one install
- Zero-code traces for workloads you have not instrumented
- Dashboards and alert rules ship pre-built
- Helm chart
- Zero-code traces
- Pre-built dashboards
Helm chart//Integrations
Plug into your stack
- Collector · NativeOpenTelemetryOTLP
- Metrics · NativePrometheusRemote write
- Logs · AgentFluent BitForward
- Logs · AgentVectorHTTP
- Cloud · AWSCloudWatchFirehose
- Cloud · GoogleCloud LoggingPub/Sub
- Cloud · AzureAzure MonitorEvent Hubs
- PlatformKubernetesHelm
- DashboardsGrafanaImport
- AlertsPagerDutyRouting
- AlertsSlackRouting
- StorageS3 · GCS · Azure BlobYour bucket
//FAQs
Sense, answered
What is DataObserve Sense?
DataObserve Sense is a unified observability platform for logs, metrics, traces and AI telemetry, with an AI SRE, agent and API management, and governance built in.
Is DataObserve Sense OpenTelemetry-native?
Yes. Logs, metrics and traces arrive over OTLP from any OpenTelemetry SDK or collector, with no proprietary agent required.
Does DataObserve Sense sample data?
No. Every log, metric label and span is kept, stored in columnar format on object storage, so the data you need during an incident is always there.
What is the DataObserve Sense AI SRE?
An AI agent that starts investigating the moment an alert fires, reasons over full-fidelity telemetry and reports a likely root cause with its evidence chain, using the AI provider you choose.
Can DataObserve Sense monitor LLM applications and agents?
Yes. LLM observability captures every prompt, tool call and response as a span with cost and quality scores, and AI observability evaluates and improves them.
Where is my observability data stored?
In your own S3, Google Cloud Storage or Azure Blob bucket if you choose, kept as long as you want at your provider's storage rates.
