Uptrace

Uptrace is an open-source application performance monitoring (APM) platform built from the ground up to be OpenTelemetry-native. Founded in 2021, Uptrace provides a unified interface for collecting, storing, and analyzing distributed traces, metrics, and logs from modern cloud-native applications. Unlike legacy APM tools that have bolted on OpenTelemetry support as an afterthought, Uptrace treats the OpenTelemetry standard as a first-class citizen, meaning it fully leverages the protocol's capabilities for data collection, processing, and correlation. Available both as a self-hosted open-source solution and as a managed cloud service, Uptrace offers a compelling European alternative to US-based observability giants like Datadog, New Relic, and Dynatrace.

OpenTelemetry-Native Architecture

OpenTelemetry has rapidly become the industry standard for instrumentation and telemetry data collection, backed by the Cloud Native Computing Foundation (CNCF) and supported by virtually all major cloud providers and observability vendors. Uptrace's decision to build natively on OpenTelemetry means that teams can use standard OpenTelemetry SDKs and instrumentation libraries to send telemetry data to Uptrace without any proprietary agents or vendor-specific code. This eliminates vendor lock-in and ensures that if you ever decide to switch to a different backend, your instrumentation investment is fully portable.

Uptrace supports the full range of OpenTelemetry protocols including OTLP/gRPC for high-performance binary data transmission in production environments and OTLP/HTTP for firewall-friendly deployments. It also supports legacy formats from Jaeger, Zipkin, and Prometheus, making it straightforward to migrate from existing observability stacks. This broad protocol support ensures that Uptrace can slot into virtually any existing infrastructure without requiring a complete rearchitecture of your telemetry pipeline.

Distributed Tracing

Distributed tracing is at the core of Uptrace's functionality. The platform visualizes the journey of requests as they travel across microservices, databases, message queues, and external APIs, displaying the complete call chain as a waterfall diagram. Each span in the trace shows its duration, status, attributes, and relationships to other spans, allowing developers to quickly pinpoint where latency is introduced or where errors originate. For complex microservice architectures where a single user request might touch dozens of services, this visibility is invaluable for debugging performance issues and understanding system behavior.

Uptrace goes beyond basic trace visualization with intelligent grouping that automatically identifies patterns in your traces and groups similar spans together. This makes it possible to spot systemic issues rather than getting lost in individual trace data. The query builder allows filtering traces by service name, operation, status, duration, and custom attributes, enabling developers to quickly narrow down to the specific traces relevant to an investigation.

Metrics Monitoring

Uptrace collects and visualizes application and infrastructure metrics through OpenTelemetry's metrics API. This includes standard runtime metrics (CPU usage, memory allocation, garbage collection), HTTP metrics (request rates, response times, error rates), database query metrics, and custom business metrics defined by your team. Metrics data is stored efficiently using columnar storage and can be visualized through customizable dashboards that provide real-time and historical views of system health.

The platform supports all OpenTelemetry metric types including counters, gauges, histograms, and summaries. Metrics can be aggregated across different dimensions, allowing teams to view performance data by service, endpoint, region, or any custom attribute. This flexibility is essential for organizations running complex distributed systems where understanding performance from multiple perspectives is critical for maintaining reliability.

Log Management

Uptrace provides integrated log management that correlates logs with traces and metrics, creating a unified observability experience. When investigating an issue through a trace, developers can instantly view the associated log entries without switching to a separate log management tool. Logs can be searched, filtered, and analyzed using the same query interface used for traces and metrics. This correlation between the three pillars of observability (traces, metrics, and logs) significantly reduces the mean time to resolution (MTTR) for production incidents.

Performance and Scalability

Uptrace is designed for high performance and efficiency. The platform can process over 10,000 spans per second on a single CPU core, and its advanced compression algorithms reduce the storage footprint from approximately 1 kilobyte per span to roughly 40 bytes. This level of compression is critical for organizations generating millions of spans per day, as storage costs can otherwise become prohibitive. The backend is built on ClickHouse, a columnar database that excels at analytical queries over large datasets, enabling fast search and aggregation even with billions of data points.

Alerting and Notifications

Uptrace includes a flexible alerting system that can trigger notifications based on metric thresholds, error rate increases, latency spikes, and custom conditions. Alerts can be routed to various notification channels including email, Slack, PagerDuty, OpsGenie, and custom webhooks. The alerting rules support both static thresholds and anomaly detection, helping teams catch issues before they impact end users. Alert grouping and deduplication prevent notification fatigue by consolidating related alerts into a single actionable notification.

Dashboards and Visualization

The platform provides customizable dashboards that display real-time and historical data through various chart types including time series, bar charts, heat maps, and tables. Dashboards can be shared across teams, embedded in documentation, and configured with variables that allow switching between different services, environments, or time ranges. Pre-built dashboard templates are available for common use cases such as HTTP service monitoring, database performance, and infrastructure health, reducing the time needed to set up meaningful visualizations.

Self-Hosted Open Source

The open-source edition of Uptrace is available on GitHub under a permissive license, allowing organizations to self-host the platform with full control over their data. The self-hosted version includes all core features without artificial limitations, making it suitable for organizations with strict data sovereignty requirements or those who prefer to manage their own infrastructure. Installation is straightforward, with Docker and binary distributions available for major operating systems. The open-source codebase also provides transparency, allowing security teams to audit the platform's data handling practices.

Uptrace Cloud

For teams that prefer a managed solution, Uptrace Cloud offers a hosted version with a generous free tier that includes 1 terabyte of storage and 100,000 timeseries. Paid plans start at approximately $30 per month and scale based on data volume. The cloud service eliminates the operational overhead of managing the observability infrastructure, including upgrades, scaling, and maintenance. For European customers, data processing can be configured to stay within European regions, ensuring compliance with GDPR and other data protection regulations.

Language and Framework Support

Because Uptrace uses standard OpenTelemetry protocols, it supports every programming language and framework that has an OpenTelemetry SDK. This includes Go, Java, Python, JavaScript/Node.js, Ruby, .NET, PHP, Rust, and many more. Uptrace provides detailed getting-started guides for popular frameworks including Spring Boot, Django, Express.js, Ruby on Rails, Laravel, and ASP.NET Core. The breadth of language support ensures that polyglot organizations can use Uptrace as a single observability platform regardless of the technology stack used by individual services.

GDPR Compliance and European Data Sovereignty

Uptrace's open-source self-hosted option provides the ultimate guarantee for data sovereignty, as all telemetry data remains on your own infrastructure without ever leaving your control. For the cloud service, Uptrace offers European data processing options. The platform does not collect personal user data as part of its APM functionality (traces and metrics contain application performance data rather than personal information), though organizations should ensure that their instrumentation does not inadvertently include personally identifiable information in span attributes or log entries.

Limitations to Consider

As a relatively young project founded in 2021, Uptrace has a smaller community and ecosystem compared to established APM platforms like Datadog or Grafana. The user interface, while functional and improving rapidly, may not yet match the polish of more mature commercial products. Advanced features like AI-powered anomaly detection, sophisticated service maps, and real user monitoring (RUM) that enterprise APM vendors offer are still maturing. For organizations that need extensive out-of-the-box integrations with cloud services, infrastructure monitoring, or synthetic monitoring, Uptrace may need to be supplemented with additional tools.

Who Should Use Uptrace?

Uptrace is ideal for development teams that have adopted or plan to adopt OpenTelemetry as their instrumentation standard. It is particularly well-suited for European organizations that need to keep observability data within EU jurisdiction, cost-conscious teams looking for an alternative to expensive APM platforms like Datadog, open-source advocates who prefer transparent and auditable software, and organizations that want to avoid vendor lock-in by standardizing on OpenTelemetry. The self-hosted option makes it especially attractive for regulated industries such as healthcare, finance, and government where data cannot leave organizational boundaries.