Distributed Tracing Platform

An open source, end-to-end distributed tracing platform designed for monitoring and troubleshooting workflows in complex microservices architectures. As a Cloud Native Computing Foundation graduated project, it maps the flow of requests and data as they traverse distributed systems, connecting the dots between disparate components to identify performance bottlenecks, troubleshoot errors, and improve overall application reliability. The platform supports distributed context propagation across service boundaries, allowing developers to trace a single user request through dozens of microservices, databases, message queues, and external API calls. Each trace consists of a hierarchical tree of spans, with each span recording the operation name, start time, duration, tags, logs, and process information. The trace visualization UI displays timing waterfalls showing where time is spent within and across services, with the ability to filter traces by service, operation, duration, and error status. Storage backends include Elasticsearch, Cassandra, and Badger with adaptive sampling to control data volume. The architecture supports both agent-based and agentless collection modes, with the OpenTelemetry Collector serving as the recommended ingestion pipeline. Integration with OpenTelemetry provides automatic instrumentation for popular frameworks and libraries, while the platform also maintains backward compatibility with its own client libraries. Notable adopters include major cloud providers, financial institutions, and transportation companies. The platform is horizontally scalable, handles billions of spans per day, and provides service dependency maps that auto-generate visual representations of inter-service communication patterns.