https://github.com/ikepcampbell/kubemedic
Automated Kubernetes Remediation
https://github.com/ikepcampbell/kubemedic
go golang k8s k8s-cluster kubemedic kubernetes kubernetes-cli kubernetes-cluster
Last synced: about 1 year ago
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Automated Kubernetes Remediation
- Host: GitHub
- URL: https://github.com/ikepcampbell/kubemedic
- Owner: IkePCampbell
- License: apache-2.0
- Created: 2025-02-05T04:42:59.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-24T23:23:53.000Z (over 1 year ago)
- Last Synced: 2025-02-25T00:26:29.600Z (over 1 year ago)
- Topics: go, golang, k8s, k8s-cluster, kubemedic, kubernetes, kubernetes-cli, kubernetes-cluster
- Language: Go
- Homepage: https://kubemedic.io
- Size: 144 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# KubeMedic - Intelligent Kubernetes Auto-Remediation
KubeMedic is an advanced Kubernetes operator that goes beyond traditional autoscaling to provide comprehensive, intelligent, and safe automated remediation for your clusters. Unlike standard autoscalers, KubeMedic can handle complex scenarios through multi-dimensional analysis and varied remediation actions.
## What Makes KubeMedic Different?
### 🎯 Multi-Dimensional Remediation
Unlike traditional autoscalers that only scale based on single metrics, KubeMedic can:
- Combine multiple metrics (CPU, Memory, Error Rates, Pod Restarts)
- Perform varied remediation actions (scaling, restarts, rollbacks)
- Adjust resource limits and HPA settings dynamically
- Execute staged responses to escalating issues
### 🧠 Intelligent Policy Engine
- Combines multiple conditions for smarter decisions
- Supports duration-based triggers (e.g., high CPU for >5 minutes)
- Implements cooldown periods to prevent oscillation
- Provides conflict resolution with other controllers
### 🛡️ Advanced Safety Mechanisms
- Automatic state preservation before actions
- Gradual or immediate reversion strategies
- Resource quota awareness
- Protected namespaces and resources
- Audit trail of all actions
### 🔌 Rich Integration Capabilities
- Native Grafana integration for visualization
- Pre/post action webhooks for notifications
- Prometheus metrics integration
- State backup system
## Prerequisites
### Required
- Kubernetes cluster (v1.16+)
- [Metrics Server](https://github.com/kubernetes-sigs/metrics-server)
- [cert-manager](https://cert-manager.io/docs/installation/) (optional, recommended)
### Optional
- Prometheus & Grafana for advanced visualization
- Webhook endpoints for notifications
## Quick Start
1. **Install Metrics Server** (if not already installed)
```bash
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
```
2. **Install KubeMedic**
```bash
kubectl apply -f deploy/components.yaml
```
3. **Create an Intelligent Remediation Policy**
```yaml
apiVersion: remediation.kubemedic.io/v1alpha1
kind: SelfRemediationPolicy
metadata:
name: advanced-remediation
namespace: my-app
spec:
rules:
# CPU-based scaling with gradual approach
- name: cpu-scaling
conditions:
- type: CPUUsage
threshold: "80"
duration: "5m"
actions:
- type: ScaleUp
target:
kind: Deployment
name: my-service
scalingParams:
temporaryMaxReplicas: 5
scalingDuration: "30m"
revertStrategy: "Gradual"
# Memory leak detection and handling
- name: memory-leak-handler
conditions:
- type: MemoryUsage
threshold: "90"
duration: "10m"
actions:
- type: RestartPod
target:
kind: Pod
name: my-service
# Error rate-based remediation
- name: error-handler
conditions:
- type: ErrorRate
threshold: "100"
duration: "2m"
actions:
- type: RollbackDeployment
target:
kind: Deployment
name: my-service
cooldownPeriod: "5m"
grafanaIntegration:
enabled: true
webhookUrl: "https://grafana.example.com/webhook"
```
## Key Features
### 🔄 Intelligent Scaling
- Dynamic HPA limit adjustments
- Temporary resource overrides
- Gradual scaling with automatic revert
- Multi-metric based decisions
### 🛠️ Advanced Remediation
- Automatic pod restarts for memory leaks
- Deployment rollbacks for error spikes
- Resource limit adjustments
- Custom webhook integrations
### 📊 Comprehensive Monitoring
- Real-time metrics analysis
- Historical data tracking
- Grafana dashboard integration
- Prometheus metrics export
### 🔒 Enterprise-Grade Safety
- Protected system namespaces
- Resource quotas and limits
- State preservation and rollback
- Action audit trail
## Documentation
For detailed documentation, visit our [Documentation](docs/README.md) section:
- [Getting Started Guide](docs/getting-started/README.md)
- [Core Concepts](docs/concepts/README.md)
- [Advanced Usage](docs/advanced-usage/README.md)
- [API Reference](docs/reference/api.md)
## Examples
Explore our comprehensive examples:
- [CPU Scaling](examples/cpu-scaling-with-test.yaml)
- [Memory Management](examples/memory-scaling-with-test.yaml)
- [Error Rate Handling](examples/pod-restart-with-test.yaml)
Each example includes both the policy configuration and a test application to demonstrate the functionality.
## Contributing
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
## License
Apache License 2.0 - See [LICENSE](LICENSE) for details.