When to Use Monitoring, Tracing, or Logging? A Practical Guide

1. Monitoring & Tracing & Logging

In any system the three needs—monitoring, tracing, and logging—are inevitable, yet their relationships are often unclear. The author reflects on whether to introduce multiple components (Prometheus+Grafana, Jaeger, ELK) and creates this note to illustrate the differences.

External link: Metrics, tracing, and logging – http://peter.bourgon.org/blog/2017/02/21/metrics-tracing-and-logging.html

2. Monitoring

Monitoring is like a regular health check: a monitoring system collects key metrics, generates reports, and alerts on abnormal data.

Low frequency

Periodic

Quantitative

Because monitoring does not require high concurrency or massive data volume, tools such as Prometheus are simple and efficient for this purpose.

3. Tracing

Tracing is comparable to a regular work report: each step of a request (A, B, C, …) is recorded, forming a trace of the entire operation.

High frequency

Massive volume

Fixed format

Tracing captures the interactions of an API with many components, producing a huge amount of data. Therefore, tracing systems usually write logs to local disk (the most efficient and cheapest method), then use agents and possibly message queues to forward data to aggregation servers. The industry standard is OpenTracing, which defines a required format for trace data.

4. Logging

Logging is illustrated by a waste recycling station: various items are collected, classified, and stored for later processing. In large systems, logging refers to a log aggregation system rather than simple log files.

Fundamentally, both monitoring and tracing are special cases of logging; logging is the superset that covers the widest range of data. However, developers often cannot anticipate all the data that will end up in the log system, and only during retrieval can they decide which subset to query.

Monitoring can be performed on a logging system by extracting metrics from aggregated logs, and tracing can also be built on top of logging if the raw data is available. Consequently, logging systems must handle high frequency, high concurrency, and massive data volumes, similar to tracing.

5. Summary

Each component has its own necessity:

Monitoring systems (e.g., Prometheus) are designed for low‑frequency, low‑volume metrics and cannot handle the high‑frequency, high‑volume demands of tracing or logging.

Tracing systems (e.g., Jaeger) require a specific data format and are suited for detailed request‑level analysis.

Logging systems (e.g., ELK) can process both monitoring and tracing data, but when specialized tools exist for those domains, it is not recommended to rely solely on a generic log aggregation system.