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architecture.md

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🏢 Architecture

The ElasticAI KubeWatch solution is built to provide intelligent auto-scaling for applications deployed on Azure Kubernetes Service (AKS) while leveraging AI-powered insights. 🚀

📚 Overview

ElasticAI KubeWatch architecture combines Azure Functions, Kubernetes, and machine learning components to achieve dynamic resource scaling based on real-time performance metrics. 📈

🧱 Key Components

The architecture consists of the following components:

  1. Azure Functions: Serve as the control plane for auto-scaling, analyzing real-time metrics to make scaling decisions. 🔍

  2. Kubernetes: Provides the foundation for running the application and enables the Horizontal Pod Autoscaler (HPA) for dynamic scaling. 🛡️

  3. Machine Learning Model (Optional): Forecasting model uses historical data to predict future demand and optimize resource allocation. 📊

🔄 Auto-Scaling Workflow

  1. Azure Functions collect performance metrics from Azure Monitor and analyze trends. ⏲️

  2. Based on configured rules and machine learning insights (if used), the Functions determine whether to scale up or down. ⚖️

  3. When scaling is required, Azure Functions interact with Kubernetes to adjust the number of replicas in the Deployment. ⚙️

  4. Kubernetes Horizontal Pod Autoscaler (HPA) continuously monitors the application's resource usage and triggers scaling events. 🚀

🌐 External Integrations

The ElasticAI KubeWatch solution can seamlessly integrate with various external tools and services, such as:

  • Azure Monitor: Collects and stores real-time performance metrics, ensuring effective monitoring. 📊

  • Azure Kubernetes Service (AKS): Hosts the application and provides auto-scaling capabilities through the HPA. 🛡️

🏋️‍♀️ Scalability & Performance

The architecture's modularity and use of AI-driven scaling empower applications to handle varying workloads efficiently. 💪

🔒 Security Considerations

ElasticAI KubeWatch implements secure practices to protect data and maintain the integrity of the auto-scaling process. 🔐

⚙️ Deployment

To deploy the ElasticAI KubeWatch solution, refer to the Deployment guide for step-by-step instructions.

📚 Further Resources

For more detailed technical information, refer to the User Guide and explore the source code in the src directory. 📖