rootsongjc / awesome-cloud-native

# Awesome Cloud Native 
> A curated list of open-source cloud native tools, software, and tutorials.
>
Cloud Native is a behavior and design philosophy. At its essence, any behavior or approach that improves resource utilization and application delivery efficiency in the cloud is called Cloud Native.
## Table of Contents
- AI & Machine Learning Platforms
- API Design & Documentation
- API Gateways & Proxies
- Build & Packaging Automation
- Cluster Provisioning & Lifecycle
- Configuration & Policy Automation
- Continuous Delivery & GitOps
- Cost & Governance
- Dashboards & Portals
- Data Processing & Analytics
- Data Protection & Backup
- Databases
- Developer Workspaces & Productivity
- Diagnostics & Troubleshooting
- Edge & IoT
- Kubernetes Operators
- Load Balancing & Ingress
- Logging
- Networking & Connectivity
- Networking Utilities
- Observability & Monitoring
- Reliability & Chaos Engineering
- RPC Frameworks
- Runtimes & Platforms
- Security & Compliance
- Serverless Platforms
- Service Discovery & Registry
- Service Mesh
- Storage & Data Management
- Streaming & Messaging
- Testing & Conformance
- Tracing & Profiling
- Tutorials & Learning
- Workload Orchestration & Scheduling
## AI & Machine Learning Platforms
- allennlp - An open-source NLP research library, built on PyTorch.
- caffe2 - Caffe2 is a lightweight, modular, and scalable deep learning framework.
- elasticdl - Kubernetes-native Deep Learning Framework.
- h2o-3 - Open Source Fast Scalable Machine Learning API For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles.)
- jina - Cloud-native neural search framework for 𝙖𝙣𝙮 kind of data.
- keras - Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
- kserve - Standardized Serverless ML Inference Platform on Kubernetes.
- kubedl - Run your deep learning workloads on Kubernetes more easily and efficiently.
- kubeflow - Machine Learning Toolkit for Kubernetes.
- leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU).
- paddlepaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice, providing high-performance single-machine, distributed training and cross-platform deployment for deep learning and machine learning.
- predictionio - PredictionIO, a machine learning server for developers and ML engineers.
- pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- seldon-core - A framework to deploy, manage and scale your production machine learning to thousands of models.
- tensorflow - Computation using data flow graphs for scalable machine learning.
- vivacious-cli - Preflight CUDA memory validation and unified multi-cloud GPU orchestrator for cloud-native model training.
↑ Back to top
## Data Processing & Analytics
- fast-data-dev - Kafka Docker for development. Kafka, Zo