This comprehensive human-based pattern-oriented trace and log analysis and anomaly detection training for software technical support engineers, system and network administrators, software developers and testers, DevOps and DevSecOps, digital forensics and malware analysts, data analysts and data scientists, human-assisted AI, ML and data mining includes a training course about basic analysis patterns, 5 seminar transcripts outlining foundations and various pattern language applications, and a pattern reference for more advanced analysis patterns:

This comprehensive training for software technical support engineers, system administrators, site reliability engineers, software developers, performance engineers, testers, and legacy application maintainers features:

Anolog.io is our latest cloud project for anomaly detection in software traces and logs. It consists of 4 main elements:

35 years ago:

"Considerable time, resources and money now lost on unorganized, trial-and-error approaches to storage dump debugging ..."

Daniel H. Rindfleisch, Author of "Debugging System 360/370 Programs Using OS And VS Storage Dumps"

Since then, software became much more complex and widespread. Unfortunately, today we can still quote the same phrase:

Huge amount of "time, resources and money now lost on unorganized, trial-and-error approaches to [memory] dump debugging".

Adding AI. Analysis Improvement.

Problem: You are not satisfied with a crash analysis report.

Problem: You are a novice and need expert pattern-oriented analysis of your crash and hang memory dump files or debugger logs.

Problem: Your critical issue is escalated to the VP level. Engineers analyze memory dumps and software traces. No definite conclusion so far. You want to be sure that nothing has been omitted from the analysis.