SayPro “Extract weekly system errors and downtime from SayPro activity logs.”

SayPro is a Global Solutions Provider working with Individuals, Governments, Corporate Businesses, Municipalities, International Institutions. SayPro works across various Industries, Sectors providing wide range of solutions.

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SayPro Weekly System Error & Downtime Extraction Report

Report Title: Extraction of Weekly System Errors and Downtime from Activity Logs
Department: SayPro Digital Operations & Monitoring Office
Unit: SayPro Monitoring, Evaluation and Learning Royalty
Report Reference: SEDL-MAYW2-2025
Reporting Period: 8 – 14 May 2025
Prepared by: [Your Name / Technical Analyst]
Date of Submission: 15 May 2025


1. Overview

This report summarizes the extraction, analysis, and classification of system errors and downtime incidents from SayPro’s digital activity logs for the week of 8–14 May 2025. It supports ongoing system reliability monitoring, early warning identification, and service improvement.


2. System Logs Extracted

Log SourceSystem MonitoredDate RangeFile TypeExtraction Method
/logs/system_events.logSayPro LMS08–14 May 2025.log / .jsonCron-based scheduled pull
/logs/web_errors.logSayPro Public Website08–14 May 2025.logDaily parsing via LogMiner v3.0
/logs/backend_status.logDatabase & API08–14 May 2025.csvManual extraction + diagnostic tools

3. Summary of Detected Errors & Downtime

A. Downtime Incidents

DateSystemDurationCauseResolvedSeverity
May 9, 2025LMS17 minutesScheduled maintenance overranYesLow
May 13, 2025Website6 minutesUnexpected restart due to memory leakYesMedium
  • Total Downtime Incidents: 2
  • Total Duration of Downtime: 23 minutes
  • Overall System Uptime (Week): 99.78%

B. System Errors Logged

Error CodeSystemFrequencyError TypeDescriptionStatus
504LMS14 timesGateway TimeoutDelay in user login loadMitigated by backend scaling
403Website5 timesAccess DeniedMisconfigured user roleResolved via permission patch
502API Gateway3 timesBad GatewayTimeout in response from DB serverEscalated for performance tuning
  • Total Errors Detected: 22 unique instances
  • Error Peak Time: Between 12 PM – 2 PM daily
  • Most Frequent Error Type: LMS login timeout (504)

4. Actions Taken

Action DateIssue AddressedTechnical ActionStatus
May 9LMS login 504 errorsIncreased backend thread capacityResolved
May 10Website permission error (403)Updated user group policyResolved
May 13Website memory leakRestarted containers, upgraded RAM allocationMonitoring

5. Recommendations

  • Implement auto-scaling policy for LMS backend servers during peak usage
  • Establish alert system for memory threshold breach on website containers
  • Optimize API query logic to reduce timeout-related 502 errors
  • Schedule earlier maintenance windows to avoid user impact during peak hours

6. Conclusion

System performance remains stable with minor but manageable errors and downtime incidents. Rapid response to detected issues has maintained service availability within acceptable limits. Continued monitoring, proactive scaling, and optimization efforts are recommended.


7. Sign-Off

Prepared by: [Full Name]
Position: Technical Analyst / Digital Operations Officer
Signature: ______________________
Date: 15 May 2025

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