Distributed Trace Decoder & Waterfall Visualizer

Distributed Trace Decoder & Waterfall Visualizer | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: Development
Input types: textarea, select, checkbox
Output type: html
Sample coverage: 4
API ready: Yes

Overview

The Distributed Trace Decoder & Waterfall Visualizer transforms raw trace JSON from Jaeger, Zipkin, or OpenTelemetry into an interactive, browser-friendly waterfall report. Paste your trace export to instantly inspect span depth, service timing, execution order, and error hotspots without needing to spin up a dedicated tracing backend.

When to use

When debugging high latency or performance bottlenecks across distributed microservices.
When analyzing raw trace JSON exports locally without access to the original Jaeger or Zipkin UI.
When isolating error spans and failed requests within complex distributed transactions.

How it works

1Paste your raw trace JSON export into the input field.
2Select the trace format (Jaeger, Zipkin, or OpenTelemetry) or leave it on auto-detect.
3Choose your preferred time display unit (microseconds, milliseconds, or seconds) and optionally filter to show only error spans.
4The tool parses the JSON and renders an interactive waterfall chart displaying span timing, parent-child dependencies, and service summaries.

Use cases

SREs investigating a sudden spike in API latency by visualizing a Zipkin trace export to find the slowest database query span.
Backend developers debugging a failed microservice checkout flow by filtering a Jaeger JSON export to show only error spans.
DevOps engineers verifying OpenTelemetry instrumentation by inspecting the parent-child span hierarchy and timing units locally.

Examples

1. Debugging Checkout Latency

Backend Developer

Background

A microservices architecture is experiencing intermittent timeouts during the checkout process. The developer has downloaded a raw Jaeger trace JSON file for a slow request.

Problem

Identifying which specific downstream service is causing the delay without deploying a local Jaeger instance.

How to use

Paste the Jaeger JSON into the Trace JSON field, set the format to 'Jaeger JSON', and select 'Milliseconds' as the display unit.

Trace Format: Jaeger JSON, Display Unit: ms, Show Only Error Spans: false

Outcome

The tool renders a waterfall chart revealing that the payment-service span took 180ms, pinpointing it as the bottleneck.

2. Isolating Microservice Errors

Site Reliability Engineer

Background

An alert triggered for a high error rate in the API gateway. The SRE exported an OpenTelemetry trace containing hundreds of spans.

Problem

Sifting through a massive JSON file to find the exact span and service where the failure originated.

How to use

Paste the OpenTelemetry JSON, select 'Auto Detect' for the format, and check the 'Show Only Error Spans' box.

FAQ

Which trace formats are supported?

The tool supports raw JSON exports from Jaeger, Zipkin, and OpenTelemetry (OTel). You can select the specific format or use the auto-detect feature.

Can I filter the waterfall to only show errors?

Yes, you can check the 'Show Only Error Spans' option to hide successful operations and focus entirely on failed spans and error hotspots.

Does this tool send my trace data to a server?

No, all JSON parsing and waterfall rendering happens locally in your browser. Your trace data remains private and secure.

How do I change the time units on the waterfall?

Use the 'Display Unit' dropdown to toggle the span duration metrics between microseconds (us), milliseconds (ms), and seconds (s).

What information is displayed in the waterfall?

The waterfall visualizes execution order, parent-child span dependencies, service names, operation names, total duration, and highlights any spans tagged with errors.

Trace Format: Auto Detect, Show Only Error Spans: true

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Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. Debugging Checkout Latency

2. Isolating Microservice Errors

FAQ

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