Overview
What is Osuite?
Section titled “What is Osuite?”Osuite is AI-native observability built on OpenTelemetry. It brings application performance monitoring, distributed tracing, log management, infrastructure metrics, real user monitoring, and a set of AI agents into a single product — so your team spends less time switching tools and more time fixing problems.
Two things make Osuite different:
- Live in under an hour. The Instrumentation Agent wires up a service from your AI IDE in minutes — instrumentation that usually takes weeks.
- Root cause and a fix in minutes. When something breaks, the Investigation Agent lives in your IDE, correlates the whole system, and hands you the root cause and a suggested fix.
Every signal Osuite collects — traces, logs, and metrics — is correlated by design. A slow database query shows up in APM, connects to its trace, links to the logs emitted during that span, and ties back to the host CPU spike that caused it. With Real User Monitoring, that thread reaches all the way to the frontend click that started it. That full context is available without leaving the platform — and it is what lets the AI agents pinpoint a failure deep in a microservice graph.
Osuite is OpenTelemetry native. If your services already emit OpenTelemetry data, you are one endpoint change away from full visibility — see Already using OpenTelemetry.
Core features
Section titled “Core features”Application Performance Monitoring (APM)
Section titled “Application Performance Monitoring (APM)”APM gives you aggregate visibility into how each service in your stack is performing in production. Osuite tracks the three golden signals — request rate, error rate, and latency — across every service automatically.
- Service list : all your services in one view with live golden signal metrics
- Latency percentiles : p50, p90, p95, p99 breakdowns per service and per endpoint
- Service dependency map : visual graph of all service-to-service calls, with nodes sized by relative load
- Error tracking : errors grouped by exception type and stack trace, with trends and example traces
APM is the starting point for incident investigation: spot a latency spike in the service list, then drill into traces to find exactly which downstream call caused it.
Distributed Tracing
Section titled “Distributed Tracing”Distributed tracing lets you follow a single request through every service it touches — from the initial API call to the final database query. Osuite gives you multiple ways to visualise and analyse traces.
- Waterfall view : timeline of every span in a trace, showing parallelism, duration, and parent-child relationships
- Flamegraph view : aggregated view for finding where time is concentrated across deep call stacks
- Span list : tabular view of all spans with full attribute inspection
- Trace sampling : everything you send is ingested by default; tail-based sampling that keeps error traces and drops routine ones is available on request
Traces are automatically linked to logs and metrics. From any span you can jump to the correlated log lines or infrastructure data without switching views.
Log Management
Section titled “Log Management”Osuite ingests logs from application SDKs, file tails, Kubernetes pods, and syslog, and makes them instantly searchable. Logs are indexed for full-text search and automatically correlated with traces via trace and span IDs.
- Any source : OTel SDK logs, file tails, Docker and Kubernetes stdout, syslog
- Structured and unstructured : JSON, logfmt, or raw text with automatic field extraction
- Full-text search : exact match, wildcard, and regex across all fields
- Severity filtering :
TRACE,DEBUG,INFO,WARN,ERROR,FATAL - Trace correlation : jump from any log line directly to the trace that produced it
- S3 archival : enterprise plans can have logs synced to their own S3-compatible storage on request
Infrastructure Monitoring
Section titled “Infrastructure Monitoring”Osuite monitors the health of your hosts and Kubernetes clusters using the OpenTelemetry Collector. Infrastructure metrics are correlated with application data, so you can tell whether a service issue is caused by the code or the underlying machine.
- Host monitoring : CPU, memory, disk, and network metrics across all hosts
- Kubernetes monitoring : cluster, node, namespace, and pod-level visibility with workload breakdowns
- OpenTelemetry Collector based : no proprietary agents; use the open-source OTel Collector with the
hostmetricsandk8sattributesreceivers - Correlated with APM : from any degraded service in APM, navigate directly to the host or pod metrics beneath it
Custom Dashboards
Section titled “Custom Dashboards”Osuite dashboards let you build any view of your data — manually or with the Visualizer Agent.
- Drag-and-drop builder : compose dashboards from any metric, log count, or trace data with time series, heatmaps, bar charts, and stat panels
- Visualizer Agent : describe the dashboard you want in plain English and Osuite builds it — no PromQL, no metric hunting
- Pre-built dashboards : ready-made APM system overview, per-service, and Kubernetes dashboards that populate as data arrives
- Share across teams : dashboards for on-call engineers, executives, and everyone in between from one place
AI Agents
Section titled “AI Agents”Osuite includes AI agents purpose-built for observability. They live in your AI IDE and cover the full loop — instrument, investigate, visualize.
- Instrumentation Agent detects your stack and instruments your code to send traces and logs to Osuite, so most services are live in under an hour.
- Investigation Agent diagnoses incidents on demand. Describe what is wrong and it correlates logs, traces, metrics, Kubernetes events, and frontend sessions across your stack to surface what broke, why, which service is the origin, and a suggested fix.
- Visualizer Agent builds dashboards from natural language. Describe what you want to see and Osuite constructs it, including the metrics, visualisations, and time ranges.
How this documentation is organised
Section titled “How this documentation is organised”| Section | What you will find |
|---|---|
| Getting Started | Account setup, API keys, and sending your first trace |
| Instrumentation | Per-language and per-framework guides for sending traces, logs, and metrics |
| AI Agents | The Instrumentation, Investigation, and Visualizer agents |
| Logs | Sending and searching logs from apps, servers, and containers |
| Infrastructure | Host and Kubernetes metrics via the OpenTelemetry Collector |
| APM & Distributed Tracing | Golden signals, the dependency map, trace explorer, and sampling |
| Real User Monitoring | Frontend tracing, session replay, and errors, linked to the backend |
| Dashboards | Building dashboards manually or with the Visualizer Agent |
| Alerts | Creating alerts, setting thresholds, and configuring notifications |
How Osuite receives data
Section titled “How Osuite receives data”Osuite ingests all telemetry via the OpenTelemetry Protocol (OTLP). How you get data in depends on the signal:
- Traces come from instrumenting your application. Use the Instrumentation Agent to wire up OpenTelemetry from your AI IDE, or follow the manual instrumentation guides for your language and framework.
- Logs and infrastructure metrics can come from the OpenTelemetry Collector running alongside your services — no application code changes required. The Collector on its own does not produce application traces; those still come from instrumenting the app.
- Already running OpenTelemetry? You do not need to re-instrument. Point your existing exporter at the Osuite OTLP endpoint — see Already using OpenTelemetry.
New to Osuite? Start with Getting Started — it walks you through setting up your account and sending your first trace and logs.