Search Results for "amazon" - Page 2
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Showing 44 open source projects for "amazon"
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Pacu
The AWS exploitation framework, designed for testing security
Pacu (named after a type of Piranha in the Amazon) is a comprehensive AWS security-testing toolkit designed for offensive security practitioners. While several AWS security scanners currently serve as the proverbial “Nessus” of the cloud, Pacu is designed to be the Metasploit equivalent. Written in Python 3 with a modular architecture, Pacu has tools for every step of the pen testing process, covering the full cyber kill chain. -
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TextTest is an application-independent tool for text-based functional testing. This means running a batch-mode binary in lots of different ways, and using the text output produced as a means of controlling the behaviour of that application.
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S3cmd
Command line tool for managing Amazon S3 and CloudFront services
...You will only have to pay Amazon for using their storage. Lots of features and options have been added to S3cmd, since its very first release in 2008.... we recently counted more than 60 command-line options, including multipart uploads, encryption, incremental backup, s3 sync, ACL and Metadata management, S3 bucket size, bucket policies, and more! -
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Muse: Middleware Universal Scripting idE
Automate: WebSphere; WebLogic; JBoss; Glassfish; Tomcat; Linux, WinRM
...Familiar Eclipse based Jython and Python Development IDE, pre-configured and ready to go. 4-Click Installer. Win x64, Linux WINE x64. Built-In JVM. Java 8/9/10, Amazon Corretto, JETPack13/14/16, IBM SDK Compatible. *** Now with powerful JBoss / GlassFish / Tomcat / Linux Active Auditing Framework. Tomcat / Glassfish 2 Python - Configuration Snapshots *** Infrastructure-as-Code, Code-Writing-Code Designed to Run on JETPack: https://sourceforge.net/projects/jetpack Muse.2025.06.x - Win 10 / Win11 Muse.2023.12.x - Win7 / Win8 / Win 10 / Win11 -
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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s3cmd
Command line tool for managing Amazon S3 and CloudFront services
Open-source tool to access Amazon S3 file storage. S3cmd is a free command line tool and client for uploading, retrieving and managing data in Amazon S3 and other cloud storage service providers that use the S3 protocol, such as Google Cloud Storage. Lots of features and options have been added to s3cmd since its very first release in 2008.... we recently counted more than 60 command line options, including multipart uploads, encryption, incremental backup, s3 sync, ACL and Metadata management, S3 bucket size, bucket policies, and more! -
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Amazon Braket Strawberry Fields Plugin
An open source framework for using Amazon Braket devices
An open-source framework for using Amazon Braket devices with the Strawberry Fields photonic device programming library. This plugin provides a BraketEngine class for running photonic quantum circuits created in Strawberry Fields on the Amazon Braket service. The Amazon Braket Python SDK is an open source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. -
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ECS Deploy
Powerful CLI tool to simplify Amazon ECS deployments, rollbacks, etc.
ecs-deploy simplifies deployments on Amazon ECS by providing a convenience CLI tool for complex actions, which are executed pretty often. Support for complex task definitions (e.g. multiple containers & task role), easily redeploy the current task definition (including docker pull of eventually updated images), deploy new versions/tags or all containers or just a single container in your task definition, scale up or down by adjusting the desired count of running tasks, add or adjust containers environment variables. ... -
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Amazon Braket Ocean Plugin
A Python plugin for using Ocean with Amazon Braket
The Amazon Braket Ocean Plugin is an open-source library in Python that provides a framework that you can use to interact with Ocean tools on top of Amazon Braket. Before you begin working with the Amazon Braket Ocean Plugin, make sure that you've installed or configured the following prerequisites. Download and install Python 3.7.2 or greater from Python.org. -
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SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
...Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
...In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance. -
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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
SageMaker TensorFlow Serving Container is an a open source project that builds docker images for running TensorFlow Serving on Amazon SageMaker. Some of the build and tests scripts interact with resources in your AWS account. Be sure to set your default AWS credentials and region using aws configure before using these scripts. Amazon SageMaker uses Docker containers to run all training jobs and inference endpoints. The Docker images are built from the Dockerfiles in docker/. ... -
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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. ... -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. -
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SageMaker Chainer Containers
Docker container for running Chainer scripts to train and host Chainer
SageMaker Chainer Containers is an open-source library for making the Chainer framework run on Amazon SageMaker. This repository also contains Dockerfiles which install this library, Chainer, and dependencies for building SageMaker Chainer images. Amazon SageMaker utilizes Docker containers to run all training jobs & inference endpoints. The Docker images are built from the Dockerfiles specified in Docker/. The Docker files are grouped based on Chainer version and separated based on Python version and processor type. ... -
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Zappa
Serverless Python
...With a traditional HTTP server, the server is online 24/7, processing requests one by one as they come in. If the queue of incoming requests grows too large, some requests will time out. With Zappa, each request is given its own virtual HTTP "server" by Amazon API Gateway. AWS handles the horizontal scaling automatically, so no requests ever time out. Each request then calls your application from a memory cache in AWS Lambda and returns the response via Python's WSGI interface. After your app returns, the "server" dies. -
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Awesome AWS
A curated list of awesome Amazon Web Services libraries
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome. Each repo listed meets at least one of the following requirements, community-authored repo with 100+ stars, community-vouched repo with < 100 stars, official repo from aws or awslabs. 100+ stars for community repos is not a strict requirement, it only serves as a guideline for the initial compilation. -
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Boto3
AWS SDK for Python
Get started quickly using AWS with boto3, the AWS SDK for Python. Boto3 makes it easy to integrate your Python application, library, or script with AWS services including Amazon S3, Amazon EC2, Amazon DynamoDB, and more. Boto3 has two distinct levels of APIs. Client (or "low-level") APIs provide one-to-one mappings to the underlying HTTP API operations. Resource APIs hide explicit network calls but instead provide resource objects and collections to access attributes and perform actions. Boto3's 'client' and 'resource' interfaces have dynamically generated classes driven by JSON models that describe AWS APIs. ... -
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isbnlib
A Python library to manipulate ISBNs.
A Python library to manipulate ISBNs. Through abstract classes and Factories, the library provides developers with a transparent interface to query any of the many different web services provided without efforts. -
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ETICS stands for "eInfrastructure for Testing, Integration and Configuration of Software". It provides software professionals with an "out-of-the-box" build and test system, powered with a build and test product repository.
