Search Results for "aws" - Page 2
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Showing 40 open source projects for "aws"
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1
jCasbin
An authorization library that supports access control models
...Besides memory and file, Casbin policy can be stored into lots of places. Currently, dozens of databases are supported, from MySQL, Postgres, Oracle to MongoDB, Redis, Cassandra, AWS S3. jCasbin is a powerful and efficient open-source access control library for Java projects. It provides support for enforcing authorization based on various access control models. -
2
SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
...It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging Face Inference Toolkit implements various additional environment variables to simplify your deployment experience. The Hugging Face Inference Toolkit allows user to override the default methods of the HuggingFaceHandlerService. SageMaker Hugging Face Inference Toolkit is licensed under the Apache 2.0 License. -
3
Amazon Chime SDK for JavaScript
A JavaScript client library for integrating multi-party communications
...For example, they can add video to a health application so patients can consult remotely with doctors on health issues, or create customized audio prompts for integration with the public telephone network. The Amazon Chime SDK for JavaScript works by connecting to meeting session resources that you create in your AWS account. The SDK has everything you need to build custom calling and collaboration experiences in your web application, including methods to configure meeting sessions, list and select audio and video devices, start and stop screen share and screen share viewing, receive callbacks when media events such as volume changes. -
4
Faast.js
Serverless batch computing made simple
...Faast.js delivers the brute force power of the cloud with the convenience and familiarity of asynchronous function calls. Deploy without zip files. Zero-configuration support for bundling dependencies with built-in webpack support. Use native dependencies, even on AWS Lambda. Faast.js eliminates the friction of using packages with serverless functions. Cost snapshots estimate the cost of your serverless function invocations in real time. For deeper analysis, use the Cost Analyzer to estimate the cost of workloads against multiple serverless configurations. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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5
Empact Foundation Class Library
Cross-platform C++ library for use as a default application framework.
...Features include: * Threading & synchronization * Socket programming: SSL, NanoMsg & ZMQ * File I/O utilities: zlib, ini, yaml * Native Database access: MySQL, SQLite, BerkleyDB, Postgre, REDIS and ODBC * Built-in mini XML parser; optional EXPAT, LIBXML and MSXML support * Network protocol stack: HTTP, FTP, SMTP, POP3, SOAP, XMLRPC * Scripting languages: Perl, Python, JavaScript, VBScript, Java, Lua, TCL, Squirrel * Cloud Computing: AWS * Encryption: OpenSSL * Platforms: Linux/Posix, Windows, Arduino * Over 500+ highly reusable classes. 4000+ fully documented functions. Follow the 'Wiki' link above to explore everything about the framework. -
6
SageMaker Spark
A Spark library for Amazon SageMaker
...With SageMaker Spark, you can train on Amazon SageMaker from Spark DataFrames using Amazon-provided ML algorithms like K-Means clustering or XGBoost, and make predictions on DataFrames against SageMaker endpoints hosting your trained models, and, if you have your own ML algorithms built into SageMaker compatible Docker containers, you can use SageMaker Spark to train and infer on DataFrames with your own algorithms -- all at Spark scale. SageMaker Spark depends on hadoop-aws-2.8.1. To run Spark applications that depend on SageMaker Spark, you need to build Spark with Hadoop 2.8. However, if you are running Spark applications on EMR, you can use Spark built with Hadoop 2.7. -
7
Amazon Kinesis Flink Connectors
Contains various Apache Flink connectors to connect to AWS data
This library contains various Apache Flink connectors to connect to AWS data sources and sinks. This repository contains various Apache Flink connectors to connect to AWS Kinesis data sources and sinks. Flink maintain backwards compatibility for the Sink interface used by the Firehose Producer. This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. -
8
AWS AppSync JavaScript SDK
JavaScript library files for Offline, Sync, Sigv4.
AWS AppSync is a fully managed service that makes it easy to develop GraphQL APIs by handling the heavy lifting of securely connecting to data sources like AWS DynamoDB, Lambda, and more. You can use any HTTP or GraphQL client to connect to a GraphQL API on AppSync. For front-end web and mobile development, we recommend using the Amplify clients which are optimized to connect to the AppSync backend. -
9
Gaufrette
PHP library that provides a filesystem abstraction layer
Gaufrette is a PHP library designed to abstract filesystem operations, providing a consistent interface to interact with various storage backends. It allows developers to work with files stored locally, on cloud platforms, or via network protocols, without changing the code. Gaufrette supports plugins for caching, metadata management, and file transformation, making it a flexible choice for file management in web applications. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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10
Amazon Neptune Gremlin .NET SigV4
A custom library for Amazon Neptune that enables AWS Signature Version
This project provides a custom library that extends the Apache TinkerPop Gremlin.NET client to enable AWS IAM Signature Version 4 signing for establishing authenticated connections to Amazon Neptune. For example usage refer to: NeptuneGremlinNETSigV4Example.cs. This example shows how to leverage this library for establishing an authenticated connection to Neptune. The GremlinClient library accepts both a GremlinServer object as well as a webSocketConfiguration object that contains a custom configuration set for establishing the WebSocket connection to Amazon Neptune. ... -
11
SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. ... -
12
Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
13
libaco
A blazing fast and lightweight C asymmetric coroutine library
...It has no more than 700 LOC but has the full functionality which you may want from a coroutine library. The benchmark part shows that a context switch between coroutines only takes about 10 ns (in the case of the standalone stack) on the AWS c5d.large machine. User could choose to create a new coroutine with a standalone stack or with a shared stack (could be shared with others). It is extremely memory-efficient, 10,000,000 coroutines simultaneously to run cost only 2.8 GB physical memory (run with tcmalloc, each coroutine has a 120B copy-stack size configuration). The phrase "fastest" in above means the fastest context switching implementation which complies to the Sys V ABI of Intel386 or AMD64. -
14
StrongKey CryptoEngine
FIDO strong authentication, encryption, digital signature engine
...Its modules include: - A FIDO Engine to support FIDO U2F key registrations/authentications - An encryption engine to encrypt/decrypt files using AES/TDES keys - Escrowing keys to on-premises key management system (StrongAuth KeyAppliance/SAKA) - Integration to cloud storage services (AWS S3, Azure and Eucalyptus Walrus) - A signing engine to digitally sign documents, code, etc. with FIPS 140-2 HSM support - An LDAP Engine for AD/LDAP integration for authorization decisions SKCE is battle-tested and in production at one of the largest e-commerce companies in the world, protecting more than 50M documents within the business process; see http://bit.ly/14VPYlO for the case study. ... -
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Awesome AWS
A curated list of awesome Amazon Web Services libraries
...If you can vouch for the awesomeness of a repo with < 100 stars and you can explain why it should be listed, please submit a pull request. Pull requests might be left open for a period of time to let the community chime in and vouch for it. An official repo from aws or awslabs can be removed if the community wishes. The Python module awesome-aws regularly scans repos on Awesome AWS to maintain the accuracy of the Fiery Meter of AWSome.
