Distributed Tracing

Read where the time went

A trace is one request laid out end to end. Maple keeps every span the SDK sent, with its attributes, its parent, and its exact millisecond offset — so a slow request stops being a guess.

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The surface

One request, 18 spans, one screen

Select any span and its full attribute set opens beside the waterfall — the SQL it ran, the status it returned, the pod it ran on. Nothing is summarised away.

A slow database span selected in an 18-span waterfall, with its query attributes open alongside
/traces trace 4f9ac21e…8b7d40f2
signal
traces
transport
OTLP/gRPC · OTLP/HTTP
views
waterfall · flamegraph · flow
attributes
db.statement · http.status_code · exception.type
joins.on
trace_id · span_id
sampling
head · tail

In motion

The real flamegraph, on a real trace

This is the component the product renders, running on a fixture trace. Hover a span to read its service, duration and share of the total.

/tracesa3f8c1d2e5b7f901
POST /checkout
8 spans across 4 services
api-gatewayauth-serviceorder-servicepayment-svc203msOk
Flow View
Mini Map
Click to select|Scroll to zoom|Drag to pan|
api-gateway
auth-service
order-service
payment-svc
|
Server
Internal
Error

What it does

Four ways to read the same spans

/traces
Waterfall
Spans nested by parent, bars scaled to the trace's own duration. A 1.24 s request with a 480 ms child reads as a shape before you read a number.
flamegraph
Flamegraph
The same spans stacked by depth instead of time. Fifty sibling db.query spans at one level is an N+1, and it is visible as a wall rather than a list.
flow view
Service flow
The trace collapsed to the services it crossed and the calls between them. Use it when the question is which boundary, not which line.
db.statement
Attributes
Every key the SDK sent, stored as sent. db.statement, http.status_code, exception.type and your own custom keys are all queryable, not just displayable.
trace_id
Jump to logs
Spans and logs carry the same trace id, so any span opens the log lines written while it was running. No timestamp arithmetic across two tools.

Keep going

Surfaces that share this data

01

Service Catalog & Map

All your services at a glance

→ 02

Log Management

Search and correlate logs instantly

→ 03

Error Tracking

Find and fix errors faster

→ 04

Microservices Debugging

Trace latency across service boundaries

→

Point OTLP at Maple.

One endpoint, one key. Traces, logs, metrics and sessions land on the same trace id from the first request.

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