In the world of software development, tracing is often seen as a purely technical tool. It's the magnifying glass we pull out to debug a thorny issue, the map we use to follow a request through a maze of microservices. While it’s invaluable for pinpointing bottlenecks and resolving issues faster, this view only scratches the surface of its potential.
What if your trace data could do more? What if, beyond showing you why an API call is slow, it could also tell you how that slowness impacts user conversion rates?
Welcome to the next evolution of observability. With trace.do, raw performance data is transformed into powerful business intelligence. It’s time to move beyond simple debugging and start using your observability stack to drive strategic decisions.
Modern applications are complex, distributed systems. A single user action—like adding an item to a cart or viewing a profile—can trigger a cascade of events across dozens of services. Traditional application monitoring might tell you if a service is up or down, but it can't tell you the story of that user's journey.
This is where tracing excels. It provides a complete, end-to-end view of a request's lifecycle. But the true power lies in aggregating this data to uncover patterns that affect the business's bottom line.
Consider this simplified trace from trace.do:
{
"traceId": "a1b2c3d4e5f67890",
"traceName": "/api/user/profile",
"durationMs": 150,
"spans": [
{
"spanId": "span-001",
"name": "HTTP GET /api/user/profile",
"service": "api-gateway",
"durationMs": 150
},
{
"spanId": "span-002",
"parentSpanId": "span-001",
"name": "auth-service.verifyToken",
"service": "auth-service",
"durationMs": 25
},
{
"spanId": "span-003",
"parentSpanId": "span-001",
"name": "db.query:SELECT * FROM users",
"service": "user-service",
"durationMs": 110
}
]
}
A developer sees a 150ms request where the database query (db.query) takes up 110ms. A business strategist using trace.do analytics can see much more:
Connecting technical metrics to business outcomes requires a tool that is both powerful and intuitive. trace.do is built from the ground up to provide this connection, turning complex data into clear, actionable insights for your entire team.
Raw data is hard to interpret. trace.do transforms cascading logs and metrics into clean, interactive visualizations. Service maps show you how your components interact, while Gantt charts for traces make it immediately obvious where time is being spent. This visual approach democratizes observability, allowing product managers and business analysts to understand every action without needing to read a single line of code.
The utility of tracing extends far beyond simple web requests. Modern businesses rely on complex, multi-step processes, from AI data pipelines to customer order fulfillment. trace.do is designed to monitor these critical workflows. You can trace an entire AI inference process—from data ingestion and preprocessing to model execution—to optimize performance and ensure your intelligent applications are running efficiently.
Getting started shouldn't be a hassle. With the .do SDK, you can integrate trace.do into your existing applications with minimal configuration. Furthermore, trace.do is compatible with open standards like OpenTelemetry. This means you can easily ingest data from already-instrumented services, consolidating all your observability data in one place without vendor lock-in.
Your application's performance data is one of your most valuable, untapped assets. Stop thinking of it as just a tool for putting out fires. Start using it to build a better, more efficient, and more profitable business.
trace.do provides the effortless tracing and powerful analytics you need to gain deep insights into your application's performance. It’s time to debug your business strategy, monitor your most critical workflows, and optimize your systems with complete visibility.
Ready to transform your trace data into business insights? Explore trace.do today!