Dibba
Lightweight Container Orchestration Platform
Production-ready, Python-based container orchestration built on containerd, Celery, and Redis. Deploy and manage containers at scale with Kubernetes-like capabilities without the complexity.
Open Source
Lightweight & Fast
Production Ready
Python Native
Everything you need to orchestrate containers in production
Kubernetes-style pod architecture with pause containers, multi-container support, and shared namespaces. Full lifecycle management from creation to termination.
Automatic replica management with min/max limits. Self-healing deployments that automatically recover from failures and scale based on demand.
Kubernetes-style liveness and readiness probes. Automatic container restart on health check failures with configurable intervals and timeouts.
Seamless AWS EC2 integration for dynamic worker node provisioning. Automatic instance lifecycle management and multi-region support.
Native Calico CNI integration for pod networking. Automatic IP assignment, network policies, and etcd-based network state management.
Real-time metrics and health monitoring. Centralized logging with rotation, worker node health tracking, and automatic state synchronization.
Persistent volumes and volume claims. Support for multiple storage backends with dynamic provisioning and snapshot capabilities.
FastAPI-based RESTful API with OpenAPI documentation. Full CRUD operations for deployments, pods, and infrastructure management.
Modern web dashboard for managing deployments, pods, and worker nodes. Real-time status updates and intuitive interface.
Modern architecture designed for reliability and performance
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β Dibba Control Plane β
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β FastAPI API β Celery Beat β Workers β
β β β β β β β
β Redis State Store β
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β β β
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β Worker β β Worker β β Worker β
β Node 1 β β Node 2 β β Node N β
βcontainerdβ βcontainerdβ βcontainerdβ
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Simple installation and quick deployment
Python 3.8+, containerd 2.0+, Redis, and Calico CNI
git clone https://github.com/tkcreddy/dibba.git
pip install -r requirements.txt and configure your settings
Start API server, Celery Beat, and workers - you're ready to deploy!
# Quick start example
curl -X POST "http://localhost:8080/scheduler/deploy/" \
-H "Authorization: Bearer <token>" \
-H "Content-Type: application/json" \
-d @deployment.yaml