What is the primary output of this skill?

It generates a structured Log Analysis Summary including error statistics, critical findings with timestamps, and a list of specific files for further manual investigation.

Does it support compressed log files?

Yes, it includes implementation steps for using zgrep to analyze rotated and compressed logs (e.g., .gz files) typically found in /var/log.

Can this skill analyze binary journald logs?

No, it specifically targets the text-based exports found within the 'sos_commands' directory of a standard sosreport to ensure compatibility and speed.

What types of critical errors can this skill detect?

The skill is optimized to find kernel panics, OOM (Out of Memory) killer events, segmentation faults, service failures, and application stack traces.

How does it handle extremely large log files?

For files exceeding 100MB, the skill employs sampling techniques using head and tail commands to prevent memory exhaustion while still capturing recent and initial errors.

Sosreport Logs Analysis

Name: Sosreport Logs Analysis
Author: openshift-eng

byopenshift-eng

•

分析と監視

Analyzes system and application log data from sosreport archives to identify root causes of system failures, crashes, and performance issues.

This skill empowers Claude to perform deep-dive forensics on Linux sosreport archives by systematically scanning journald, dmesg, and application-specific logs. It automates the detection of critical system events such as kernel panics, OOM killer actions, and service failures, providing structured summaries that correlate error patterns with specific timestamps and components. It is an essential tool for SREs and system administrators who need to rapidly diagnose infrastructure issues by extracting actionable insights from massive log volumes.

主な機能

01Error frequency categorization and chronological timeline generation

02Automated detection of kernel panics, OOM killer events, and segfaults

03Application-specific analysis for Java, Python, and web server logs

04Smart handling of large or compressed log files using sampling and zgrep

05Comprehensive parsing of both journald and traditional var/log files

0629 GitHub stars

ユースケース

01Troubleshooting failed systemd services and inter-service dependency issues

02Diagnosing sudden system reboots or freezes using kernel message analysis

03Identifying memory-hungry processes through OOM killer forensic data

主な機能

01Error frequency categorization and chronological timeline generation

02Automated detection of kernel panics, OOM killer events, and segfaults

03Application-specific analysis for Java, Python, and web server logs

04Smart handling of large or compressed log files using sampling and zgrep

05Comprehensive parsing of both journald and traditional var/log files

0629 GitHub stars

ユースケース

01Troubleshooting failed systemd services and inter-service dependency issues

02Diagnosing sudden system reboots or freezes using kernel message analysis

03Identifying memory-hungry processes through OOM killer forensic data