Awesome GitHub RepositoriesCloud Infrastructure Scaling

kops is a Kubernetes cluster provisioner and lifecycle manager designed to automate the creation, maintenance, and destruction of production-grade clusters on cloud infrastructure. It functions as a declarative infrastructure manager, synchronizing the live state of a cluster with versioned manifests stored in remote object storage to ensure idempotent operations. The project distinguishes itself by offering comprehensive automation for the entire cluster lifecycle, including high-availability control plane deployment, incremental rolling updates, and automated version upgrades. It also serve

The Kubernetes Cluster Autoscaler is a mechanism that automatically adjusts the number of nodes in a cluster to match the resource demands of pending pods. It functions as a cloud infrastructure scaler that manages the desired capacity of scaling groups to ensure sufficient compute resources for workloads. The system manages cloud infrastructure automation by adjusting node counts when resources are insufficient or nodes are underutilized. It includes a manager for scaling groups using mixed instance policies to balance on-demand and spot instances for cost and availability. The project also

reconftw is an attack surface management framework and reconnaissance workflow orchestrator designed to automate the discovery, mapping, and monitoring of external digital assets. It operates as a modular tool-chain pipeline that coordinates a sequence of security tools to perform intelligence gathering and vulnerability scanning. The project distinguishes itself through a cloud-native deployment model that parallelizes scanning workloads across a fleet of remote VPS instances to bypass local resource constraints. It utilizes container-based environment isolation to ensure consistent executio

该项目提供了战略路线图和指南，详细介绍了托管容器编排和安全服务的演进与部署模式。它作为 EKS、ECS、ECR 和 Fargate 即将推出的功能和开发优先级的公共跟踪文档。 该资源包括云容器编排指南以及 Kubernetes 和 ECS 战略，概述了云基础设施的托管 Kubernetes 和专有编排服务的开发。它还提供了专注于扫描恶意活动和跟踪工作负载健康状况的安全和监控计划。 该材料涵盖了广泛的基础设施功能，包括资源配置、计算和任务的自动扩展以及容器镜像管理。它通过负载均衡和 Pod 密度优化来解决网络和流量管理问题，并通过日志路由和性能跟踪来解决可观测性问题。

This project provides a programmatic interface and framework for integrating large language models with secure, stateful, and multimodal code execution environments. It functions as a code interpreter API that enables the execution of arbitrary Python scripts within isolated sandboxed runtimes. The system supports multimodal data analysis by processing combined text and file inputs to generate visualizations and computational results. It manages stateful workflows by maintaining conversation memory and session history, allowing language models to complete multi-step technical tasks. The fram

This project is a collection of structured study notes and conceptual breakdowns designed for the AWS Certified Cloud Practitioner exam. It serves as a technical reference and study guide, organizing cloud service details and architectural principles to assist in certification preparation. The knowledge base is built using markdown files and includes curated cheat sheets and interactive mind-map visualizations. These tools map complex certification topics into visual hierarchies to enable drill-down study paths and rapid revision. The materials cover a wide range of cloud capabilities, inclu

Polyaxon is a Kubernetes-native machine learning orchestration platform and MLOps pipeline orchestrator. It serves as a control plane for managing distributed deep learning workloads, automated machine learning pipelines, and experiment tracking. The platform distinguishes itself through specialized services for distributed training management, including MPI-based coordination for PyTorch and TensorFlow. It provides an automated hyperparameter optimization service utilizing Bayesian, random, and grid search algorithms, alongside managed interactive AI workspaces for launching Jupyter notebook