magic-trace
Fastest to get started
Why teams pick it
2‑10 % runtime overhead, no code changes required
Open-source alternatives to AWS X-Ray
Compare community-driven replacements for AWS X-Ray in distributed tracing workflows. We curate active, self-hostable options with transparent licensing so you can evaluate the right fit quickly.
AWS X-Ray
AWS X-Ray collects, visualizes, and analyzes traces to build service maps, identify high-latency segments, and debug production issues across AWS workloads.Read more
Key stats
- 9Alternatives
- 8Active development
Recent commits in the last 6 months
- 5Permissive licenses
MIT, Apache, and similar licenses
Counts reflect projects currently indexed as alternatives to AWS X-Ray.
Start with these picks
These projects match the most common migration paths for teams replacing AWS X-Ray.
uftrace
AI-powered workflows
Why teams pick it
Multiple visualizations: Chrome trace, flame graphs, Graphviz & Mermaid
All open-source alternatives
uftrace
Comprehensive function call tracing for native and kernel code
Active developmentIntegration-friendlyAI-powered workflowsC
Why teams choose it
- Dynamic function tracing without recompilation via instruction patching
- Automatic capture of arguments and return values using DWARF and lib prototypes
- Multiple visualizations: Chrome trace, flame graphs, Graphviz & Mermaid
Watch for
Requires unstripped binaries or separate symbol files for full detail
Migration highlight
Identify slow functions in a C++ server
Pinpoint functions consuming the most CPU time and optimize them, reducing request latency by measurable percentages.
magic-trace
High‑resolution, low‑overhead tracing of every function call
Active developmentPermissive licenseFast to deployOCaml
Why teams choose it
- 40 ns resolution tracing of every function call
- 2‑10 % runtime overhead, no code changes required
- Intel PT‑based snapshots with configurable ~10 ms history
Watch for
Supports only Intel CPUs (Skylake or newer)
Migration highlight
Investigate intermittent latency spikes
Identify the exact function call chain and hidden page faults causing delays
XO
Programmable observability platform built for developers
Integration-friendlyAI-powered workflowsTypeScript
Why teams choose it
- Native OpenTelemetry support for metrics, logs, and distributed tracing
- WebAssembly-powered plugin system for custom data processing pipelines
- Deep chart and page interactivity with extensive customization options
Watch for
Core observability features still in development (pre-V1.0)
Migration highlight
Custom APM Dashboard
Build tailored application performance monitoring with OpenTelemetry traces, custom metrics aggregation via WebAssembly plugins, and interactive drill-down workflows.
bpftrace
Powerful, scriptable eBPF tracing for Linux with awk-like syntax
Active developmentPermissive licenseAI-powered workflowsC++
Why teams choose it
- Awk‑style syntax compiled to efficient eBPF bytecode
- Supports kprobes, uprobes, tracepoints, raw syscalls, and hardware counters
- Built‑in aggregation functions and interval timers for on‑the‑fly analysis
Watch for
Requires a recent Linux kernel with eBPF support
Migration highlight
Identify high‑latency syscalls per process
Generate per‑process histograms of syscall durations to pinpoint bottlenecks.
Jaeger
End‑to‑end distributed tracing for cloud‑native applications at scale
Active developmentPermissive licenseFast to deployGo
Why teams choose it
- Native OpenTelemetry SDK integration via HTTP/gRPC
- Pluggable storage architecture with multiple backend options
- Scalable collector and query services for high‑volume traces
Watch for
Requires separate storage backend configuration
Migration highlight
Root‑cause latency analysis
Correlate spans across services to pinpoint slow operations and reduce request latency.
Zipkin
Trace, visualize, and troubleshoot latency across microservices
Active developmentPermissive licenseFast to deployJava
Why teams choose it
- Searchable trace data by service, operation, tags, and duration
- Dependency graph visualizing inter‑service calls
- Multiple storage backends (in‑memory, Cassandra, Elasticsearch) and transport options (HTTP, Kafka, gRPC, etc.)
Watch for
Requires instrumentation of each service
Migration highlight
Debugging high latency in a payment service
Identify slow downstream calls and visualize the call chain to pinpoint bottlenecks.
Grafana Tempo
Scalable, cost-efficient tracing backend with seamless Grafana integration
Active developmentFast to deployIntegration-friendlyGo
Why teams choose it
- Queryless Traces Drilldown UI for point‑and‑click analysis
- TraceQL language for powerful trace queries and metric generation
- Supports Jaeger, Zipkin, OpenTelemetry, and Kafka ingestion formats
Watch for
Limited built‑in alerting; relies on external systems
Migration highlight
Identify latency bottlenecks in a Kubernetes microservice mesh
Engineers use the Traces Drilldown UI to pinpoint slow spans, reducing request latency by 30%.
Tokio Tracing
Structured, event-based diagnostics for Rust applications and libraries
Active developmentPermissive licenseIntegration-friendlyRust
Why teams choose it
- Macro‑based instrumentation for events and spans
- Subscriber model allowing custom data collection
- Compatibility layer for the `log` crate
Watch for
Steeper learning curve than simple `log`
Migration highlight
Async request handling
Correlate inbound request spans with downstream service calls for end‑to‑end latency analysis.
Kamon
Unified tracing, metrics, and context propagation for JVM applications
Active developmentIntegration-friendlyScala
Why teams choose it
- Automatic distributed tracing with minimal code changes
- Rich metric collection with built‑in reporters
- Seamless context propagation across threads and async boundaries
Watch for
License not explicitly stated (NOASSERTION)
Migration highlight
Microservice latency analysis
Identify slow endpoints across services by correlating traces and latency metrics.
Choosing a distributed tracing alternative
Teams replacing AWS X-Ray in distributed tracing workflows typically weigh self-hosting needs, integration coverage, and licensing obligations.
- 8 options are actively maintained with recent commits.
Tip: shortlist one hosted and one self-hosted option so stakeholders can compare trade-offs before migrating away from AWS X-Ray.