AWS X-Ray

What it is

AWS X-Ray is Amazon’s native distributed tracing service, launched in 2016 to help developers analyze and debug requests as they travel through distributed applications built on AWS. It integrates natively with services like Lambda, API Gateway, ECS, EKS, Elastic Beanstalk, and EC2, capturing trace segments as requests flow between them and rendering service maps and trace timelines in the AWS console.

The service’s role within AWS’s observability stack has shifted significantly. Amazon CloudWatch Application Signals — an APM-style layer providing service maps, SLOs, and automated anomaly detection — has become the primary surface AWS steers customers toward for application tracing and performance monitoring, with X-Ray increasingly functioning as the underlying trace storage and query backend behind it. Separately, AWS announced that the original X-Ray SDKs and daemon entered maintenance mode in February 2026 (with end-of-support in February 2027), as AWS migrates its tracing instrumentation strategy toward OpenTelemetry (OTel) as the standard going forward, rather than X-Ray’s own proprietary SDKs.

Why teams choose it

• Zero-friction tracing on AWS-managed compute. For Lambda, API Gateway, and other fully managed AWS services, enabling X-Ray tracing is close to a checkbox operation, with no separate collector infrastructure required.
• Deep integration with AWS-native services. Because it’s built by AWS, X-Ray understands AWS service boundaries (Lambda cold starts, DynamoDB calls, SQS hops) natively in ways third-party tracers sometimes need extra configuration to capture.
• In active architectural transition. With the classic SDK in maintenance mode and Application Signals absorbing much of the user-facing tracing workflow, teams adopting X-Ray today should plan around OpenTelemetry-based instrumentation rather than the legacy X-Ray SDK.
• Limited outside AWS. X-Ray’s value is concentrated on AWS-hosted workloads; multi-cloud or hybrid architectures get much less benefit from it compared to cloud-agnostic tracing tools.

Pricing model

X-Ray is usage-based, priced per trace recorded and per trace retrieved/scanned, with a free tier covering a monthly allotment of traces. CloudWatch Application Signals, where much of the newer tracing workflow now lives, is billed separately on its own usage basis (typically per monitored entity or trace volume). There’s no seat-based pricing — cost scales with request volume and sampling rate, which teams can tune down via head-based sampling rules to control spend.

Alternatives

Jaeger and Grafana Tempo are open-source tracing backends that work identically across any cloud, avoiding AWS lock-in at the cost of self-hosting the backend. For a managed alternative with broader cross-cloud reach, Datadog and Honeycomb both offer distributed tracing that works the same way regardless of which cloud (or clouds) a workload runs on. Within AWS itself, Amazon CloudWatch’s Application Signals is becoming the more commonly recommended entry point, with X-Ray operating underneath it.