From the user to the line of code: application observability with context
Follow every transaction end to end, trace errors back to the method and fix performance bottlenecks before customers notice
Tracing in practice: from the first span to root cause in 60 seconds
Live demo with OpenTelemetry, Obseria TraceFlow and profiling.
Register nowApplication observability that delivers answers
One platform that connects traces, logs, metrics and profiles per transaction, for faster releases and fewer incidents.End-to-end distributed tracing
Obseria TraceFlow captures every request with timing and code-level context across services, queues, databases and third-party APIs, without sampling gaps for errors.
Code-level diagnostics and profiling
CPU, memory and allocation profiles at method level, continuously and with under 1% overhead. See hotspots right inside the trace.
Explainable root cause
Obseria Intelligence links deployments, configuration changes and dependencies to name the cause of every failure with evidence.
85% faster fault diagnosis
Fjord Software finds the cause of production errors directly in the trace instead of in log files.
Read the Fjord story3× more releases per week
Deltaforge ships three times as often with automatic release validation, at the same error rate.
Read the Deltaforge story< 1% instrumentation overhead
Halo Games runs continuous profiling in production with no measurable latency for players.
Read the Halo story50% fewer incidents after deployments
Lumen Retail links every deployment to SLOs and stops faulty rollouts automatically.
Read the Lumen storyEmpower your business with AI-driven observability
Harness trusted answers instead of alert floods, for measurable business outcomes at scale
Explore the Obseria approachFrom signal to answer in three steps
- Step 1
Instrument
Use OpenTelemetry SDKs or zero-code auto-instrumentation via the Kubernetes Operator for Java, .NET, Node.js, Python and Go.
- Step 2
Trace every request
Obseria TraceFlow follows each transaction across services, queues and databases and keeps every failed and slow trace.
- Step 3
Fix at the line of code
Profiles, logs and deployments are linked to the trace, so the root cause is visible down to the method.
What's included
- End-to-end distributed tracing
- Continuous profiling under 1% overhead
- Service maps and dependency analysis
- SLOs, error budgets and release validation
- Tail-based sampling in the pipeline
- Serverless and messaging context propagation
Explore capabilities in detail
Products for production applications
Obseria TraceFlow
End-to-end distributed tracing with code-level context for every transaction.
Continuous Profiling
CPU, memory and allocation profiles in production, linked to traces.
Log Analytics
Logs in the context of the trace: no more searching for request IDs.
Digital Experience
Follow browser and mobile sessions all the way into the backend.
Application Security
Detect vulnerabilities and attacks at runtime in the same context.
OpenTelemetry
Every OTel instrumentation works from day one, no proprietary agent required.
Application observability use cases with Obseria
Understand every request, across all services
Obseria TraceFlow shows every transaction as a waterfall with spans, attributes, logs and errors. Tail-based sampling guarantees that all failed and slow traces are kept while routine traffic is aggregated efficiently.
Explore TraceFlowValidate deployments against SLOs automatically
Every deployment is compared on error rate, latency and saturation. If an SLO degrades, Obseria stops the rollout via Argo Rollouts or Flagger and notifies the team with the cause.
Explore AutomationFind hotspots at method level
Continuous profiling in production shows which methods consume CPU and memory, right in the context of the slow trace. Measure optimizations before and after the release.
Explore profilingLambda, Functions, Kafka and queues in one trace
Asynchronous architectures are traced seamlessly with context propagation across Kafka, RabbitMQ, SQS and Pub/Sub. Make cold starts, retries and dead-letter queues visible.
See integrationsWorks with your stack
Connect the technologies you already run. 700+ integrations, discovered and put into context automatically.
Leading organizations that run on Application Observability
Get started with Application Observability training and documentation
Application Observability FAQ
APM monitors availability, performance and errors of applications from the perspective of users and code. Modern application observability extends APM with distributed tracing, profiling and the linkage to logs, metrics and topology to answer unknown problems in distributed systems.
Java, .NET, Node.js, Python, Go, PHP, Ruby, Rust and C++ via OpenTelemetry SDKs and automatic instrumentation. Plus frameworks such as Spring, ASP.NET Core, Express, Django, FastAPI, Rails and Laravel as well as serverless platforms.
No. Obseria is OpenTelemetry-native. The optional Obseria Agent adds automatic instrumentation and profiling but is not a prerequisite. Existing OTel pipelines work unchanged.
Obseria uses tail-based sampling in the pipeline: failed, slow and rare traces are kept in full, routine traffic is aggregated in a statistically representative way. Costs stay predictable without losing important traces.
With automatic instrumentation via the Kubernetes operator or OTel Collector, most teams see their first traces in under 15 minutes. The free training covers tracing basics in two hours.
Ready for observability that delivers answers?
Take the first steps toward reliable operations