Awesome GitHub RepositoriesCloud Infrastructure Cost Optimization

Azure Docs is the official technical documentation repository for Microsoft Azure, the cloud computing platform. It provides comprehensive guidance on the full spectrum of Azure services, covering everything from core infrastructure components like virtual machines, Kubernetes clusters, and serverless computing to platform services for AI, machine learning, data analytics, and storage. The documentation details how to provision, manage, and govern cloud resources at scale, including policy enforcement, identity management, and cost optimization. The documentation distinguishes Azure through i

AutoMQ is a cloud-native streaming platform and Kafka-compatible message broker. It implements the Kafka protocol to provide integration with existing clients and ecosystems while functioning as a message queue that persists data directly to cloud object storage. The system decouples compute from storage, allowing processing power and storage capacity to scale independently. It utilizes a shared-log architecture and object-storage-based persistence to remove dependencies on local disks, which reduces operational costs and eliminates manual disk management. The platform includes mechanisms fo

Boto3 is the AWS SDK for Python, providing a programmatic interface for managing and automating AWS cloud infrastructure and services. It serves as a cloud management API client and resource manager for provisioning, configuring, and scaling virtual servers, databases, and storage. The library enables the implementation of infrastructure-as-code through declarative templates and scripts, allowing for the deployment of identical resource stacks across multiple accounts and geographic regions. It also provides a framework for coordinating distributed workflows, serverless functions, and contain

The Byte Book is an open-source book that covers cloud-native infrastructure, focusing on kernel networking, Kubernetes, service meshes, and containers. It serves as a technical reference for designing stable and cost-effective infrastructure, combining DevOps workflows and site reliability engineering principles. The book provides a deep dive into Kubernetes networking, including CNI, service mesh integration, and container network interfaces for production clusters. It also covers container runtime operations, service mesh architecture for observability and traffic management, and Linux ker

Cortex is a Kubernetes-based machine learning infrastructure platform designed for deploying, scaling, and managing models and workloads. It functions as a serverless inference engine and GPU cluster orchestrator, providing the tools necessary to execute real-time, asynchronous, and batch model predictions. The platform utilizes declarative infrastructure-as-code for provisioning model clusters and environments. It optimizes operational costs by elastically scaling CPU and GPU resources through the use of spot instances. The system covers a broad set of operational capabilities, including wo

karpenter-provider-aws is a Kubernetes node autoscaler and infrastructure provider for AWS. It serves as a node lifecycle manager and cluster cost optimizer that automatically provisions and removes compute instances based on the resource requirements of pending pods. The project distinguishes itself through advanced AWS spot instance orchestration and price-capacity optimized selection to reduce cloud spend. It minimizes costs by consolidating underutilized nodes and prioritizing spot or reserved instances over on-demand capacity, while proactively migrating workloads before cloud provider i

Coroot is an observability platform and Kubernetes performance monitor that utilizes eBPF to automatically collect metrics, logs, and traces without requiring manual code instrumentation. It functions as an OpenTelemetry trace analyzer and an LLM observability gateway, exposing system health data to large language models through the Model Context Protocol. The platform differentiates itself by combining automated root cause analysis and AI-driven diagnostics to investigate performance regressions. It also includes a cloud cost monitoring tool that attributes infrastructure spending to specifi

Agones is a Kubernetes game server orchestrator designed for hosting, scaling, and managing dedicated multiplayer game servers. It extends the Kubernetes control plane using custom resource definitions to define game server and fleet objects, utilizing a dedicated fleet manager to maintain pools of warm server instances. The system provides a game server SDK and language-specific client libraries that allow server processes to signal readiness, health, and shutdown states directly to the controller. It distinguishes itself through specialized scaling logic, including the use of WebAssembly mo

ClearML is a comprehensive MLOps platform designed to manage the end-to-end machine learning lifecycle, from initial experimentation to production deployment. It provides a suite of integrated tools including a pipeline orchestrator for automating workflows, an experiment tracking tool for logging hyperparameters and metrics, and a metadata-driven data versioning system for managing large-scale datasets and model artifacts. The platform is distinguished by its advanced compute management and serving capabilities. It features a GPU compute manager that supports fractional resource slicing and

CloudQuery is a cloud infrastructure ETL tool and multi-cloud data pipeline designed to collect, synchronize, and normalize resource metadata from various cloud providers and SaaS platforms. It functions as a centralized asset inventory manager and security posture manager, extracting configuration and state data into relational databases, data lakes, or data warehouses. The system distinguishes itself by transforming complex, nested cloud API responses into flat relational tables, enabling the use of standard SQL for asset querying and analysis. It employs a modular plugin system for data ex

Osmedeus is a security workflow orchestration engine that coordinates AI agents, shell commands, and scanning tools through declarative YAML pipelines. It functions as a distributed security scanner, a declarative workflow automator, and an AI agent framework for security, enabling automated multi-step security analysis with conditional branching, parallel execution, and distributed workers. The engine distinguishes itself through a hybrid runner model that executes workflow steps on the local host, inside Docker containers, or over SSH to remote machines, selected per step or module. It supp

This project is a performance optimizer and resource benchmarker for AWS Lambda. It analyzes the trade-off between execution speed and cost by testing various memory configurations to identify the most cost-effective settings and minimize operational spending. The tool utilizes an AWS Step Functions orchestrator to automate the execution and data collection of multiple function test runs across different power levels. It simulates production workloads by injecting custom static or remote data and using weighted payload distribution to mimic real-world traffic patterns. The suite covers sever

Cloud Custodian is a multi-cloud governance engine and policy enforcement tool designed to automate security, compliance, and cost optimization across various cloud providers. It functions as a rules engine that uses a declarative domain specific language to query cloud resources and execute corrective actions based on predefined filters. The system operates as a serverless policy orchestrator, deploying provider-specific functions to trigger real-time enforcement in response to cloud resource changes. It provides a provider-agnostic resource abstraction to maintain consistent operational pol

Cloud Custodian is an open-source rules engine that uses declarative YAML policies to query, filter, and take automated actions on cloud resources for governance and compliance. It functions as a stateless policy execution engine, where each policy evaluation runs as an independent, idempotent operation without maintaining internal state between runs. Policies are defined using a YAML-based domain-specific language that structures rules as a query-filter-action pipeline. The engine supports dry-run validation, allowing users to simulate policy actions against live resources without applying c

GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without

Rivet este o infrastructură distribuită pentru gestionarea ciclului de viață, adresarea și persistența actorilor stateful și a motoarelor de execuție durabile. Oferă un sandbox de proces distribuit care execută logica aplicației în izolate ușoare, asigurând izolarea resurselor și porniri rapide (fast cold starts). Sistemul este conceput pentru a coordona operațiuni în mai mulți pași folosind cozi persistente și temporizatoare pentru a garanta finalizarea fiabilă a sarcinilor în medii distribuite. Platforma permite în mod specific orchestrarea agenților AI stateful care mențin memorie și stare persistentă pe parcursul interacțiunilor de lungă durată și al fluxurilor de lucru complexe. Se distinge printr-un framework de sincronizare a stării prin WebSocket care leagă componentele interfeței utilizator frontend de procese stateful la distanță prin comunicare bidirecțională în timp real. Sistemul acoperă o gamă largă de capabilități, inclusiv adresarea ierarhică a actorilor, un runtime de tip hibernate-on-idle pentru optimizarea resurselor și un strat de persistență pluggable pentru backend-uri de stocare modulare. Include, de asemenea, instrumente pentru depanarea sesiunilor active, monitorizarea stării de execuție în timp real și opțiuni de deployment automatizat pentru infrastructură edge, cloud sau privată. Proiectul este implementat în Rust și suportă dezvoltarea de actori în mai multe limbaje.

Koloda is an iOS gesture interaction library and SwiftUI view component used to create swipeable card interfaces. It provides a stack-based view component that manages overlapping views, ensuring only the top-most element remains actively interactive. The library allows for the customization of card appearance, including the configuration of overlays and animations that dictate how background cards move during a swipe. It manages drag behavior and swipe directions, triggering specific logic when cards are swiped, tapped, or fully exhausted. The component covers the implementation of gesture-

Side-Menu.Android este o componentă UI reutilizabilă pentru aplicațiile Android care oferă un meniu de navigare de tip slide-out. Este concepută pentru a ajuta dezvoltatorii să organizeze secțiunile aplicației și opțiunile utilizatorului într-un panou structurat, ascuns, care menține o interfață curată pentru zona de conținut principal. Componenta se distinge prin prezentarea sa vizuală, care urmează ghidurile Material Design pentru a asigura o experiență de utilizator consistentă și intuitivă. Dispune de o ierarhie de meniu bazată pe date care permite gruparea logică a elementelor de navigare și încorporează animații fluide de tip circular reveal pentru a oferi tranziții vizuale rafinate atunci când meniul este deschis sau închis. Prin încapsularea logicii complexe de layout și interacțiune într-o singură clasă modulară, biblioteca simplifică implementarea navigării pe mai multe ecrane. Suportă tranziții bazate pe evenimente, permițând dezvoltatorilor să decupleze interacțiunile din meniu de actualizările de conținut pentru a menține o arhitectură de aplicație curată și responsivă.

Mimir este o bază de date de serii temporale multi-tenant și un magazin de metrici distribuit, conceput pentru telemetrie scalabilă. Servește ca un backend compatibil cu Prometheus, oferind stocare pe termen lung și un motor de interogare scalabil pentru volume masive de date de serii temporale. Sistemul este construit pentru observabilitate multi-tenant, izolând datele de telemetrie și limitele de resurse pentru echipe sau organizații independente în cadrul unui singur cluster. Asigură disponibilitate ridicată și durabilitate prin sharding și replicarea datelor într-un cluster distribuit, utilizând stocarea de obiecte pentru persistență pentru a elimina dependențele de baze de date externe. Proiectul acoperă capabilități vaste, inclusiv agregarea globală a metricilor pentru analiză cross-region și execuția distribuită a interogărilor folosind paralelizarea și caching-ul. De asemenea, integrează instrumente de observabilitate precum alertarea federată, monitorizarea sintetică și fluxuri de lucru de rezolvare a incidentelor bazate pe AI pentru a accelera depanarea. Controalele administrative includ cote de resurse pentru chiriași, override-uri de resurse per-utilizator și shuffle-sharding pentru izolarea sarcinilor de lucru.

KRR is an open-source tool for analyzing Kubernetes resource requests and recommendations. It evaluates how pods are currently configured and provides suggestions for optimizing CPU and memory allocations based on actual usage patterns. The project focuses on helping teams right-size their Kubernetes workloads by identifying over-provisioned and under-provisioned resources. It scans clusters and generates reports that highlight where adjustments can reduce costs or improve performance without compromising reliability. KRR is distributed as a Python command-line tool that can be run directly