Error Log
An error log in the mainframe context is a persistent record of error conditions, abnormal terminations (abends), warnings, or significant events generated by the z/OS operating system, subsystems (like CICS, DB2, IMS), or application programs. Its primary purpose is to provide diagnostic information crucial for problem determination, debugging, and system health monitoring. An error log in the mainframe context is a persistent record of events, messages, and conditions indicating abnormal or noteworthy occurrences within the z/OS operating system, its subsystems, or applications. Its primary purpose is to aid in problem determination, system monitoring, and auditing by providing a chronological history of issues.
Key Characteristics
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- Persistent Storage: Error logs are typically stored in various forms, including sequential datasets (
PS), VSAM datasets, system logs (SYSLOG), or specialized subsystem logs. - Timestamped Entries: Each entry usually includes a timestamp, job name, program name, task ID, error code (e.g.,
abendcode likeS0C4,Uxxxx), and a descriptive message. - Severity Levels: Entries often indicate the severity of the event, ranging from informational messages and warnings to critical errors and program terminations.
- Automated Capture: Errors are generally captured automatically by the operating system, specific subsystems, or through explicit calls within application code.
- Diagnostic Information: May contain additional diagnostic data such as register contents, Program Status Words (
PSWs), references toSVC dumpsortransaction dumps, and trace information. - Centralized or Distributed: Can be centralized (e.g.,
SYSLOGfor system messages,SMFfor system activity records) or distributed across application-specific log files (e.g., CICSMSGUSR, DB2DSNJLOG).
- Persistent Storage: Error logs are typically stored in various forms, including sequential datasets (
Use Cases
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- Problem Determination: Analyzing
abendcodes (e.g.,S0C7for data exception,S0C4for protection exception) and error messages to diagnose program failures or system issues. - Application Debugging: Developers use error logs to trace program logic failures, identify data inconsistencies, and pinpoint the exact location of an error within their COBOL or Assembler code.
- System Monitoring: Operations teams monitor critical error logs for alerts indicating system instability, resource exhaustion, or impending failures, often using automated tools.
- Performance Tuning: Identifying recurring errors or warnings that might indicate inefficient code, resource contention, or design flaws that impact application performance.
- Auditing and Compliance: While
SMFis primary for security, some error logs can provide supplementary information regarding unauthorized access attempts or system integrity issues.
- Problem Determination: Analyzing
Related Concepts
Error logs are intrinsically linked to SYSLOG, SMF, and dumps. SYSLOG is the primary system-wide log for console messages and system events, often containing references to more detailed error conditions. SMF records provide comprehensive system and subsystem activity data, which can be correlated with error log entries. When a severe error or abend occurs, the system often generates an SVC dump or transaction dump, and the error log will typically contain a reference to this dump for in-depth analysis.
- Regular Review and Analysis: Operations and development teams should regularly review error logs for critical issues, recurring patterns, and trends to proactively address problems.
- Automated Alerting: Implement automated tools to scan error logs for specific critical messages or
abendcodes and trigger alerts to relevant support teams. - Clear and Actionable Messages: Application developers should strive to generate clear, concise, and actionable error messages that provide sufficient context for diagnosis without requiring source code access.
- Define Retention Policies: Establish and enforce appropriate retention policies for error log datasets to balance diagnostic needs with storage capacity and compliance requirements.
- Centralized Logging and Correlation: Where feasible, consolidate error log data from multiple sources (LPARs, subsystems) into a centralized logging solution for easier correlation and holistic problem analysis.