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Next-generation Kubernetes resource optimization platform. Unified intelligence for monitoring, optimization, cost analysis, and autoscaling. Goes beyond requests/limits with multi-dimensional optimization across compute, network, storage, and security.

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Mochi 🍑

⚠️ Early Development: Mochi is currently in active development. First release (v0.1.0) expected soon. Not production-ready yet.

License: GPL v3 Go Version Kubernetes

Next-generation Kubernetes resource optimization platform that combines monitoring, optimization, cost analysis, and autoscaling into a single, unified tool. Mochi goes beyond simple requests and limits, offering multi-dimensional optimization across compute, network, storage, and security.

🎯 Why Mochi?

Existing Kubernetes optimization tools are fragmented, you need separate tools for monitoring, cost analysis, autoscaling, and optimization. Mochi unifies all of this into one intelligent platform that:

  • Eliminates tool fragmentation - One tool for everything
  • Goes beyond requests/limits - Multi-dimensional optimization
  • Predicts before problems - Statistical and ML-based forecasting
  • Optimizes intelligently - Network, storage, security-aware
  • Automates safely - Auto-pilot mode with safety mechanisms

✨ Key Features

Intelligent Resource Analyzer

  • Deep pod-level analysis (CPU, memory, network, I/O)
  • Dependency mapping between services
  • Bottleneck identification
  • Resource waste detection (over-provisioned, idle resources)

Predictive Autoscaling

  • Predict demand spikes (deployments, traffic patterns, cron jobs)
  • Pre-scale before demand hits
  • Multi-metric scaling (not just CPU/memory)
  • Cost-aware scaling (spot instances, reserved capacity)

Cost Intelligence

  • Real-time cost attribution (namespace, team, service)
  • Cost forecasting
  • Savings opportunities (rightsizing, spot usage, reserved instances)
  • Multi-cloud cost comparison

Network Optimization

  • Service mesh optimization (Istio, Cilium, Linkerd)
  • Pod affinity/anti-affinity recommendations
  • Network topology optimization
  • Traffic pattern analysis

Storage Optimization

  • PV/PVC usage analysis
  • Storage tier recommendations
  • Snapshot lifecycle management
  • Storage cost optimization

Security-Aware Optimization

  • Security context analysis
  • RBAC optimization
  • Network policy recommendations
  • Compliance checking

Nice Features

  • "What-if" Scenario Engine - Simulate changes before applying
  • Auto-Pilot Mode - Fully automated optimization with safety limits
  • Multi-Cluster Intelligence - Cross-cluster learning and federated optimization
  • Developer-Friendly - GitOps integration, PR comments, CI/CD integration
  • Observability-First - Built-in observability, audit trails, custom dashboards

πŸ—οΈ Architecture

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                    Prometheus Ecosystem                      β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”     β”‚
β”‚  β”‚ kube-state-  β”‚  β”‚   cAdvisor   β”‚  β”‚   node-      β”‚     β”‚
β”‚  β”‚   metrics    β”‚  β”‚              β”‚  β”‚  exporter   β”‚     β”‚
β”‚  β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜     β”‚
β”‚         β”‚                 β”‚                 β”‚              β”‚
β”‚         β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜              β”‚
β”‚                           β”‚                                β”‚
β”‚                    β”Œβ”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”                         β”‚
β”‚                    β”‚ Prometheus  β”‚                         β”‚
β”‚                    β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜                         β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                            β”‚
                            β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                    Mochi Controller (Go)                      β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”        β”‚
β”‚  β”‚  Analyzer    β”‚  β”‚  Optimizer   β”‚  β”‚ Recommender  β”‚        β”‚
β”‚  β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜        β”‚
β”‚         β”‚                 β”‚                 β”‚                 β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”        β”‚
β”‚  β”‚   Enforcer   β”‚  β”‚  Cost Engine β”‚  β”‚  Network     β”‚        β”‚
β”‚  β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜  β”‚  Analyzer    β”‚        β”‚
β”‚                                       β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜        β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
               β”‚                               β”‚
               β–Ό                               β–Ό
    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”            β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
    β”‚   PostgreSQL     β”‚            β”‚      Redis       β”‚
    β”‚ - Recommendationsβ”‚            β”‚ - Cache          β”‚
    β”‚ - Costs          β”‚            β”‚ - Real-time      β”‚
    β”‚ - History        β”‚            β”‚ - Sessions       β”‚
    β”‚ - Configs        β”‚            β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
    β”‚ - Audit trails   β”‚
    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

πŸ› οΈ Tech Stack

  • Language: Go (everything built in Go)
  • Metrics: Prometheus, kube-state-metrics, cAdvisor, node-exporter
  • Storage: PostgreSQL (non-metric data), Redis (caching), Prometheus TSDB (metrics)
  • Kubernetes: client-go, controller-runtime
  • API: Gin/Echo (REST), gRPC (internal)
  • Messaging: NATS/JetStream (event streaming)

πŸ“Š Current Status

βœ… Completed

  • Project planning and architecture design
  • Feature specification

🀝 Contributing

Contributions are welcome! Mochi is in early development, so there are many opportunities to contribute:

  • Bug reports
  • Feature suggestions
  • Documentation improvements
  • Code contributions
  • Testing

Please read our Contributing Guide for details on our code of conduct and the process for submitting pull requests.

πŸ“ License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

πŸ™ Acknowledgments

  • Built with ❀️ for the Kubernetes community
  • Inspired by the need for unified optimization tools
  • Thanks to all contributors and early adopters

πŸ“§ Contact & Support

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Next-generation Kubernetes resource optimization platform. Unified intelligence for monitoring, optimization, cost analysis, and autoscaling. Goes beyond requests/limits with multi-dimensional optimization across compute, network, storage, and security.

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