Awesome GitHub RepositoriesObject Versioning

The AWS Cloud Development Kit is an infrastructure-as-code framework that enables developers to define and provision cloud resources using familiar programming languages. By utilizing construct-based synthesis, it translates high-level, object-oriented code into declarative templates, allowing for the automated management of complex cloud environments through a centralized, code-driven control plane. The framework distinguishes itself through its ability to model infrastructure as a dependency-aware resource graph, ensuring that components are provisioned and updated in the correct order. It

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

Sui is a blockchain platform featuring an object-centric state model and resource-oriented smart contracts. It utilizes parallel transaction execution to increase network throughput and supports programmable transaction blocks that bundle multiple operations into single atomic units. The platform distinguishes itself with a capability-based access control system and zero-knowledge login mechanisms, enabling users to authenticate via identity providers without seed phrases. It also implements deterministic object addressing to allow predictable state lookups and supports the creation of soulbo

This is a Golang client library for interacting with a cloud native distributed messaging system. It provides the necessary tools for Go applications to exchange messages using publish-subscribe and request-reply patterns, as well as specialized clients for managing persistent streams and distributed storage. The library includes a JetStream client for durable message streaming and replay, a Key-Value store client for managing distributed state with versioning and watchers, and an Object Store client for the storage and retrieval of large binary files via chunked delivery. The implementation

lakeFS is a data lake versioning system that provides Git-like branching and commits for large datasets stored in object storage. It functions as a version control layer, enabling the creation of immutable snapshots, atomic commits, and zero-copy branching to create isolated environments for data experimentation without duplicating physical files. The system serves as an S3-compatible storage gateway and an Iceberg REST catalog, allowing standard cloud storage protocols and compatible clients to manage versioned tables. It acts as a data quality gatekeeper by using an event-driven hook system

Acest proiect este un ghid arhitectural MLOps și un framework pentru proiectarea și implementarea sistemelor de deep learning în medii de producție. Oferă o abordare structurată pentru implementarea inferenței modelelor, orchestrarea pipeline-urilor ML și crearea de arhitecturi de machine learning la nivel de producție. Proiectul se distinge printr-un accent pe deep learning distribuit și optimizarea AI la margine (edge AI). Acoperă metodologii pentru paralelizarea antrenării modelelor pe mai multe GPU-uri pentru a gestiona seturi mari de date și aplică tehnici precum cuantizarea și distilarea pentru a reduce dimensiunea modelului pentru hardware-ul embedded. Suprafața de capabilități se extinde la monitorizare și observabilitate, incluzând urmărirea performanței modelului, data drift-ul și metricile experimentelor. Abordează, de asemenea, orchestrarea fluxului de lucru al datelor, versionarea seturilor de date prin object stores și gestionarea cererilor de inferență de mare volum folosind batching adaptiv și orchestrare bazată pe containere.

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