NOC Analyst | Observability Engineer | SRE Enthusiast
📍 Nairobi County, Kenya

Welcome to my GitHub! I'm a Network Operations Center (NOC) Analyst with 5+ years in financial services, specializing in observability, monitoring, and reliability engineering. I transform complex system data into actionable insights using modern monitoring stacks, automation, and SRE principles to ensure high-availability infrastructure.

• System Observability: Building comprehensive monitoring solutions with ELK, Zabbix, and Grafana
• Site Reliability Engineering: Implementing SLOs, error budgets, and automation for infrastructure resilience
• Security Operations: Integrating security monitoring into observability pipelines
• Infrastructure as Code: Automating deployment and monitoring with Python and Bash scripting

Observability & Monitoring

Data Analytics & ML

Infrastructure & Automation

Network & Security

• Docker roadmap for RHEL environments: secure installs, SELinux considerations, and hardened defaults
• Covers images, networking, storage, logging, and baseline CI/CD patterns
• Practical checklists and commands for ops-ready RHEL container setups

• Trade analytics and import recommendation insights for the Kenyan market
• Data exploration, visualization, and signal extraction for decision support
• Modular notebooks/pipelines for reproducible analysis

• DevOps/SRE interview prep kit with curated Q&A, scenarios, and checklists
• Focus on observability, reliability, automation, and incident playbooks
• AI-augmented notes for faster review and retention

• Python-based detector for unused/orphaned files across 20+ file types
• CI-friendly JSON output, configurable rules, and heuristics for suspicious files

• Streamlit uptime/SLA analytics with Z-score + MAD spike detection
• Pushes SLA reports back to Zabbix; smart caching and history/trends auto-switching

• 99.8% average uptime across monitored services (tracked via custom Zabbix analytics)
• 12 minutes Mean Time to Detection (MTTD) using adaptive spike detection algorithms
• 22 minutes Mean Time to Resolution (MTTR) with automated correlation analysis
• 65% reduction in manual operational tasks through Python automation
• Zero false positive alerts through intelligent filtering and MAD-based anomaly detection
• Production-grade SLA monitoring with automated daily uptime reporting to stakeholders

Certification	Badge	Status
ISC2 Certified in Cybersecurity (CC)		✅ Active
CompTIA Linux+		✅ Active
CISCO Cybersecurity Essentials		✅ Active
AWS Solutions Architect		🎯 In Progress

• Advanced Analytics: Implementing Z-score and MAD algorithms for infrastructure anomaly detection
• SLA Engineering: Building comprehensive uptime calculation engines with automated reporting
• API Integration: Developing robust API clients with OAuth2, caching, and rate limiting
• Statistical Analysis: Cross-host correlation matrices for infrastructure pattern identification
• Performance Optimization: Auto-switching between Zabbix history/trends for optimal query performance
• Production Systems: Deploying enterprise-grade monitoring dashboards with 14-day log retention
• Code Quality Automation: Building dead code detection tools for automated repository maintenance

I'm passionate about advanced observability engineering, statistical monitoring algorithms, and production-grade SLA systems. Whether you're interested in anomaly detection, automated uptime reporting, or building enterprise monitoring dashboards, I'd love to share insights and collaborate!

🔗 LinkedIn: josephkibaki
📧 Email: kibaki.joseph1@gmail.com
💬 Open to: Mentoring, Knowledge Sharing, SRE Discussions