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atlas

Don't confuse these

Distributed tracing vs Log

Distributed tracing

Observability

Following one user request as it passes through many services, timing each step, to see where it slowed down or failed.

Formal

A method where each request gets a shared ID that is passed from service to service, and every service records a timed step, called a span, under that ID, so the full path can be put back together as a trace.

In plain English

Like the tracking page for a parcel, showing each depot it passed and how long it sat there, so you can see it was stuck three days in one place.

In practice

A trace of a slow page in a region's patient portal shows the web service answered almost at once but waited four seconds for the appointment booking service, so the team knows where to look.

Why it matters

When one click touches dozens of services, logs from each one alone cannot show the chain of cause; traces link them into one story, which also helps follow an attacker's steps.

Log

Operating systems

A time-stamped record of events that a system or program writes down as they happen.

Formal

A list of entries that only grows at the end, one per event, each noting when it happened, which system or program reported it and what it was - for example a login, an error or a changed setting.

In plain English

Like the diary kept on a ship's bridge - the crew notes the time and what happened, entry after entry, so the voyage can be pieced together later.

In practice

The IT lead at a small accounting firm finds forty failed logins for the same account in the mail server's log within one minute at 3 a.m., followed by one success - a sign that someone guessed the password.

Why it matters

Without logs an incident cannot be noticed, explained or proven afterwards; they are what a SIEM and incident response work from.

Shared connections

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