Add K8s Agent: Streamlit-based on-prem Kubernetes cluster management UI

.gitignore

@@ -22,3 +22,6 @@ charts/*/charts/
 *.pem
 *.key
 kubeconfig*
+k8s-agent/__pycache__/
+k8s-agent/data/profiles/*.json
+k8s-agent/modules/__pycache__/

k8s-agent/README.md

@@ -0,0 +1,87 @@
+# K8s Agent — On-Prem Kubernetes Cluster Management
+
+A Streamlit-based UI for managing on-premises Kubernetes clusters with CRI-O container runtime and Flannel CNI.
+
+## Features
+
+1. **Profile Manager** — Create and manage profiles for multiple clusters with node definitions (control-plane / worker), SSH credentials, and K8s configuration.
+
+2. **Cluster Creation** — SSH into nodes and provision a full Kubernetes cluster:
+   - Installs CRI-O container runtime
+   - Installs kubeadm, kubelet, kubectl
+   - Initializes control plane with best-practice kubeadm config
+   - Deploys Flannel CNI
+   - Joins worker nodes automatically
+   - Applies security hardening (NetworkPolicies, RBAC, ResourceQuotas, PodSecurity)
+
+3. **Cluster Debugger** — Run diagnostic commands and get AI-powered analysis:
+   - Pre-built checks for nodes, pods, networking, storage, certificates
+   - Category-based scanning (Cluster Overview, Networking, Security, etc.)
+   - Custom command execution via SSH
+   - AI-powered root cause analysis and remediation recommendations
+
+4. **Monitoring Setup** — Deploy Prometheus + Grafana with production-ready configuration:
+   - One-click kube-prometheus-stack installation
+   - Grafana dashboard imports (cluster overview, node exporter, pods, etcd, API server, etc.)
+   - Alerting rules for node health, pod crashes, disk pressure, etcd latency
+   - AI-powered monitoring recommendations
+
+5. **Log Analysis** — Collect, parse, and correlate logs across cluster components:
+   - System component logs (kubelet, CRI-O, API server, etcd, Flannel, CoreDNS)
+   - Pod-level log collection with previous container support
+   - Automated error pattern extraction and grouping
+   - Cross-source error correlation
+   - AI-powered deep log analysis and root cause identification
+
+6. **AI Assistant** — Chat interface for Kubernetes questions powered by your LLM.
+
+## Quick Start
+
+```bash
+cd k8s-agent
+pip install -r requirements.txt
+
+# Set your LLM API key
+export LLM_API_KEY="your-api-key"
+# Or use the Infosys AI Gateway key
+export INFOSYS_CODER_API_KEY="your-key"
+
+# Run the app
+streamlit run app.py
+```
+
+## Configuration
+
+Environment variables:
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| `LLM_API_URL` | LLM API endpoint | Infosys AI Gateway |
+| `LLM_API_KEY` | LLM API key | Falls back to `INFOSYS_CODER_API_KEY` |
+| `LLM_MODEL` | Model name | `gpt-4` |
+| `LLM_TEMPERATURE` | Response temperature | `0.3` |
+| `LLM_MAX_TOKENS` | Max response tokens | `4096` |
+
+## Architecture
+
+```
+k8s-agent/
+├── app.py                     # Main Streamlit application
+├── config.py                  # Configuration and environment variables
+├── requirements.txt           # Python dependencies
+├── modules/
+│   ├── llm_client.py          # LLM API integration (query + streaming)
+│   ├── profile_manager.py     # Cluster profile CRUD operations
+│   ├── cluster_creator.py     # SSH-based cluster provisioning
+│   ├── cluster_debugger.py    # Diagnostic commands and AI analysis
+│   ├── monitoring_setup.py    # Prometheus/Grafana deployment
+│   └── log_analyzer.py        # Log collection, parsing, correlation
+├── templates/                 # Configuration templates
+└── data/profiles/             # Stored cluster profiles (JSON)
+```
+
+## Requirements
+
+- Python 3.10+
+- SSH access to target nodes (for cluster operations)
+- LLM API endpoint (Infosys AI Gateway or compatible OpenAI-style API)