Gain insights into diagnostic techniques and anomaly detection with over 200 trace and log analysis patterns, applicable across various software environments, operating systems, and platforms.

General trace and log analysis patterns allow the application of uniform diagnostics and anomaly detection across diverse software environments. It includes troubleshooting, debugging, describing, and explaining problems and incidents on various operating systems and platforms. It is also helpful in recording network traces, malware, general data, narratives, and text and image analysis (space-like narratology). This course, organized as a pattern language dictionary and cross-referenced with classification, explains and teaches more than 200 traces and log analysis patterns.

A Guide to Learning Software Trace and Log Analysis Patterns

# Calibrating trace
Multiple traces and logs are usually collected for diagnosing distributed systems. Different tools and tracing settings (circular, sequential, file size limit) may be used, systems may be unsynchronized, and individual system tracing may be started at different times due to manual tracing setup and switching between systems. There may be [blackouts](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/region-theatre-adjoint-thread-blackout-braid-group), circular, and [truncated](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/partition-shape-summary-truncated-visibility) traces. When we analyze such a trace set ([inter-correlation](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/inter-correlation-master-meta-news-polytrace)), we usually select one trace or log to use as **calibrating trace**. It is used for measuring all other traces against [basic facts](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/basic-hidden-indirect-facts-constants-vocabulary) such as start and end tracing times and the time of the problem. One such scenario is illustrated in the following diagram:

# Circular trace
It is an obvious structural trace analysis pattern. Sometimes, the information about circularity is missing in the problem description or the trace metadata does not reflect it. In such cases, **circular traces** can be detected by trace file size (usually large) and from timestamps, like this 100 Mb CDF trace snippet:

This lesson introduces the following analysis patterns: calibrating trace, circular trace, combed trace, density distribution, and empty trace.

Getting Started

Activity

Block and Data

Error and Large Scale

Message 1

Message 2

Trace as a Whole

Trace Set

Vocabulary, Memory, Code and Text

Conclusion

Index

Calibrating, Circular, Combed, Distribution, Empty

Calibrating trace