Search Results for "ecr"
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Showing 11 open source projects for "ecr"
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Containers Roadmap
This is the public roadmap for AWS container services
This repository is a public forum for the AWS Containers team to share plans, gather feedback, and track progress for services like Amazon ECS, EKS, Fargate, ECR, App Runner, and related tooling. Instead of buried changelogs, ideas and work items are represented as GitHub issues with labels that convey status, area, and priority. Customers watch, react, and comment directly on items, creating a transparent feedback loop between users and service teams. The issue history provides valuable context on trade-offs, design pivots, and integration plans across the container ecosystem on AWS. ... -
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AWS CodeBuild curated Docker images
AWS CodeBuild repository for managed Docker images
...When you provide information to CodeBuild about the build environment, you specify the identifier of a Docker image in a supported repository type. These include the CodeBuild Docker image repository, publicly available images in Docker Hub, and Amazon Elastic Container Registry (Amazon ECR) repositories that your AWS account has permission to access. We recommend that you use Docker images stored in the CodeBuild Docker image repository, because they are optimized for use with the service. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
...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. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role. -
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AWS Toolkit for Azure DevOps
AWS Toolkit for Azure DevOps
The AWS Toolkit for Azure DevOps adds tasks to easily enable build and release pipelines in Azure DevOps (formerly VSTS) and Azure DevOps Server (previously known as Team Foundation Server (TFS)) to work with AWS services including Amazon S3, AWS Elastic Beanstalk, AWS CodeDeploy, AWS Lambda, AWS CloudFormation, Amazon Simple Queue Service and Amazon Simple Notification Service, and run commands using the AWS Tools for Windows PowerShell module and the AWS CLI. This is an open source project... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Kemal
Fast, effective, simple web framework
...Websocket support. Request/Response context, easy parameter handling. Middleware support. Built-in JSON support. Built-in static file serving. Built-in view templating via ECR. Documentation. Before filters are evaluated before each request within the same context as the routes. They can modify the request and response. Since Crystal does not allow using variables in macro literals, you need to generate another helper macro to make the code easier to read and write. You can add many blocks to the same verb/path combination by calling it multiple times they will be called in the same order they were defined. ... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. 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... -
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SageMaker Spark Container
Docker image used to run data processing workloads
...The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker. -
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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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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
..."cpu", "gpu", "ei") has a different Dockerfile in each group. If your are testing locally, building the image is enough. But if you want to your updated image in SageMaker, you need to publish it to an ECR repository in your account. You can also run your container locally in Docker to test different models and input inference requests by hand. -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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It is a set of java classes (a library) for get the currency exchange rate for specific country. Useful for web developing when client want exchange rate on his web site.
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Oberon PLM is a Web based PLM/PDM, built on Oberon framework that facilitate its customization. Oberon PLM integrates people, data, processes, and business systems and provides a product information backbone for companies and their extended enterprise.
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