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Automated OpenNebula Monitoring and Alerting Architecture
Designed an automated monitoring and observability architecture for a multi-region OpenNebula private cloud environment.
The solution automatically discovers newly created virtual machines through the OpenNebula API and registers them in Zabbix without requiring manual monitoring configuration. Once a VM is detected, it is assigned to the appropriate host group based on its region, environment, operating system, or customer.
Monitoring templates are then applied automatically for Linux, Windows, hypervisor, network, and storage systems. This ensures that every newly provisioned VM receives consistent monitoring, trigger thresholds, availability checks, and alerting policies from the moment it becomes active.
The architecture includes regional Zabbix proxies that collect monitoring data from each OpenNebula region and securely forward it to a centralized Zabbix Server. This reduces cross-region monitoring traffic and allows monitoring to continue locally during temporary network interruptions.
The platform monitors:
CPU and memory utilization
Disk capacity and performance
Network traffic and packet loss
Operating system availability
Services and running processes
VM uptime and availability
Hypervisor health
Storage availability and performance
Network devices using SNMP
Web services and APIs using HTTP checks
When a problem is detected, Zabbix evaluates the configured trigger and escalation policy. Notifications are then automatically routed to Telegram, Microsoft Teams, and email based on severity, environment, and operational responsibility.
Grafana is integrated with Zabbix as a centralized visualization platform. It provides real-time dashboards for infrastructure health, regional availability, VM performance, uptime, service-level objectives, resource capacity, and active alerts.
The monitoring environment is isolated from tenant and production networks using a dedicated monitoring network. Only controlled monitoring, API, and notification traffic is permitted between the cloud regions and the monitoring platform.
Key outcomes of the solution include:
Automatic VM discovery and monitoring enrollment
Consistent monitoring across all OpenNebula regions
Automated template and policy assignment
Centralized alerting and escalation
Telegram, Microsoft Teams, and email notifications
Real-time Grafana dashboards
Reduced manual administration
Faster incident detection and response
Scalable monitoring for future cloud expansion
This project demonstrates my ability to integrate OpenNebula, Zabbix, Grafana, API-driven automation, multi-region monitoring, centralized alerting, and secure network segmentation into a complete private cloud observability platform.
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🚀 Just published my latest Facility Management Platform case study.
A modern Facility Management SaaS platform designed for asset management, work orders, occupancy monitoring, maintenance operations, visitor management, and real-time facility intelligence.
I'd love to hear your feedback.
Overview
ICYEREKEZO OMS (Operations Management System) is an enterprise-grade Software-as-a-Service (SaaS) platform built for manufacturing companies. It allows multiple factories to operate independently while being centrally managed by a platform administrator.
The system simplifies production management, user administration, subscription billing, inventory operations, and factory oversight through an intuitive modern dashboard.
The Challenge
Manufacturing companies often rely on disconnected spreadsheets and legacy systems to manage production, inventory, subscriptions, and users. These fragmented workflows reduce efficiency and make scaling difficult.
The objective was to build a centralized, cloud-based solution that supports multiple factories while providing administrators with complete visibility and control.
Solution
I designed and developed a scalable multi-tenant platform that provides:
Platform administration
Factory onboarding
User management
Subscription management
Analytics dashboards
Secure authentication
Responsive administration interface
Multi-language support
Enterprise-ready architecture
Key Features
Platform Dashboard
Live statistics
Factory growth analytics
Subscription monitoring
User statistics
Support ticket tracking
Interactive charts
Factory Management
Register factories
Activate or suspend factories
Industry categorization
Factory overview
User allocation
User Management
Create users
Manage administrators
Password reset
Account activation
Factory assignment
Subscription Management
Create pricing plans
Monthly billing
Plan comparison
Subscription monitoring
Upgrade management
Enterprise Features
Multi-tenant architecture
Secure authentication
Role-based permissions
Dashboard analytics
Notification system
Localization
Responsive interface
My Responsibilities
Product Planning
UI/UX Design
Database Architecture
Backend Development
Frontend Development
Authentication System
Dashboard Development
Testing
Deployment
A working demo is not the same as a production-ready product.
Sometimes the best thing you can do for your client is delay deployment until the product is truly ready.
The project is feature complete.
Everything works perfectly in the demo.
So naturally, my client wanted to deploy it.
But during the final review, I found a few production-readiness issues.
And that's something many people misunderstand...
"It works" doesn't always mean "It's ready for production."
Before a real launch, a product needs proper testing, monitoring, security, reliability, and scalability.
If we skip these checks, the real users—not the developers—will find the bugs.
Delaying deployment isn't about slowing down the project.
It's about protecting the client's business and ensuring a successful launch.
A good developer doesn't just know when to deploy...
They also know when to say, "Not yet."
