Uptrace

Uptrace is an open source

observability and application performance monitoring platform for distributed systems built on OpenTelemetry (OTel) (observability).

• OpenTelemetry-based distributed tracing, metrics, and logs collection and analysis (observability).
• Application performance monitoring for microservices and monolithic applications (APM).
• Query and visualization layer with dashboards, charts, and trace explorers (analytics and visualization).
• Self-hosted and managed deployment options with support for popular programming languages and frameworks (deployment and integrations).
• Error tracking, latency analysis, and service dependency exploration for production workloads (operations monitoring).

More About Uptrace

Uptrace is an Observability Platform (OP) (observability) built around the OTel standard, targeting teams that run distributed applications, microservices, and cloud-native workloads. It ingests traces, metrics, and logs emitted via OTel SDKs and collectors and provides a centralized environment to explore, correlate, and analyze this telemetry data. Enterprise and institutional users employ Uptrace to monitor the behavior of production services, diagnose performance issues, and understand inter-service dependencies across heterogeneous infrastructure.

The platform focuses on distributed tracing as a core capability, allowing developers and Site Reliability Engineering (SRE) teams to trace requests as they traverse multiple services, databases, and external dependencies. By storing spans and related attributes, Uptrace supports Root Cause Analysis (RCA) of latency issues, errors, and timeouts. The system integrates traces with metrics and logs so that users can pivot from a high-level performance indicator to individual traces and then to log entries for deeper inspection, following the common observability triad pattern.

Uptrace can be deployed as a self-hosted solution or consumed as a managed service, which aligns with deployment models commonly required in enterprises with regulatory, data residency, or customization needs. The self-hosted option typically uses a backend stack that includes a columnar database and scalable storage to handle high-cardinality telemetry data. Through configuration with the OpenTelemetry Collector (OTC) and SDKs, organizations can instrument services written in languages such as Go, Java, Python, and others that have OTel support.

From an architectural perspective, Uptrace sits downstream of application and infrastructure components as a telemetry backend. It receives data via OTLP (OpenTelemetry Protocol) and other compatible ingestion mechanisms, then indexes and enriches that data for querying. The user interface offers dashboards, charts, and trace explorers that allow filtering by service, endpoint, latency, error rate, and custom attributes. This positions Uptrace within the broader Application Performance Management (APM) and observability market, alongside other tools that support tracing and metrics, but with a design centered on OTel rather than proprietary agents.

For directory and taxonomy purposes, Uptrace fits into multiple enterprise IT categories: observability platforms (observability), application performance monitoring (APM), distributed tracing tools (monitoring and diagnostics), and log and metric analytics (IT operations analytics). Organizations adopt it to gain visibility into microservices architectures, analyze performance for APIs and background jobs, and support incident response workflows where correlation across traces, metrics, and logs is required.