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aws-solutions-library-samples

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  1. guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker Public

    DeepRacer workshop content. This Guidance demonstrates how software developers can use an Amazon SageMaker Notebook instance to directly train and evaluate AWS DeepRacer models with full control

    Jupyter Notebook 1.2k 703

  2. cloud-intelligence-dashboards-framework cloud-intelligence-dashboards-framework Public

    Command Line Interface tool for Cloud Intelligence Dashboards deployment

    Python 536 241

  3. video-on-demand-on-aws video-on-demand-on-aws Public

    An automated reference implementation leveraging AWS Step Functions and AWS Media Services to deploy a scalable fault tolerant Video on demand workflow

    JavaScript 519 241

  4. data-lakes-on-aws data-lakes-on-aws Public archive

    Enterprise-grade, production-hardened, serverless data lake on AWS

    Python 484 156

  5. qnabot-on-aws qnabot-on-aws Public

    Guidance for QnABot on AWS is a multi-channel, multi-language conversational interface (chatbot) that responds to your customer's questions, answers, and feedback. The solution allows you to deploy…

    JavaScript 445 264

  6. guidance-for-claude-code-with-amazon-bedrock guidance-for-claude-code-with-amazon-bedrock Public

    This Guidance demonstrates how organizations can implement secure enterprise authentication for Amazon Bedrock using industry-standard protocols and AWS services

    Python 398 154

Repositories

Showing 10 of 345 repositories
  • accelerated-intelligent-document-processing-on-aws Public

    The IDP Accelerator provides a scalable, serverless approach for automated document processing and information extraction using AWS services, such as Amazon Bedrock Data Automation and Amazon Bedrock foundational models. It combines generative AI and optical character recognition (OCR) to process documents at scale.

    aws-solutions-library-samples/accelerated-intelligent-document-processing-on-aws's past year of commit activity
    Python 303 MIT-0 113 16 8 Updated Sep 9, 2026
  • cloud-intelligence-dashboards-data-collection Public

    This Guidance demonstrates how to deploy Cloud Intelligence Dashboards in your AWS environment using AWS CloudFormation templates or command line tools. These pre-built dashboards enable you to drive financial accountability, optimize costs, and track usage goals across their AWS infrastructure.

    aws-solutions-library-samples/cloud-intelligence-dashboards-data-collection's past year of commit activity
    Python 83 Apache-2.0 71 16 16 Updated Sep 9, 2026
  • guidance-for-game-server-hosting-using-agones-and-open-match-on-amazon-eks Public

    This guidance provides code and instructions to create a multi Kubernetes cluster environment to host a match making and game server solution, integrating Open Match, Agones and Amazon Elastic Kubernetes Service (Amazon EKS), for a session-based multiplayer game.

    aws-solutions-library-samples/guidance-for-game-server-hosting-using-agones-and-open-match-on-amazon-eks's past year of commit activity
    HCL 20 MIT-0 11 6 10 Updated Sep 9, 2026
  • guidance-for-multi-region-resilient-microservice-on-aws Public

    This Guidance demonstrates how to build highly resilient web applications that can withstand disruptions, minimizing impact on revenue and application downtime

    aws-solutions-library-samples/guidance-for-multi-region-resilient-microservice-on-aws's past year of commit activity
    Java 9 MIT-0 5 8 0 Updated Sep 9, 2026
  • global-capacity-orchestrator-on-aws Public

    GCO is a platform that spins up EKS Auto Mode clusters across AWS regions, wired together with Global Accelerator for low-latency routing. It handles multi-region compute orchestration — capacity-aware scheduling, spot fallback, globally distributed autoscaling inference — and offers a REST API, CLI, MCP and an integrated analytics environment

    aws-solutions-library-samples/global-capacity-orchestrator-on-aws's past year of commit activity
    Python 44 MIT-0 11 0 0 Updated Sep 9, 2026
  • aws-solutions-library-samples/guidance-for-ev-digital-twin-ai-powered-operational-monitoring's past year of commit activity
    JavaScript 5 MIT 0 0 16 Updated Sep 9, 2026
  • qnabot-on-aws Public

    Guidance for QnABot on AWS is a multi-channel, multi-language conversational interface (chatbot) that responds to your customer's questions, answers, and feedback. The solution allows you to deploy a fully functional chatbot across multiple channels including chat, voice, SMS and Amazon Alexa.

    aws-solutions-library-samples/qnabot-on-aws's past year of commit activity
    JavaScript 445 Apache-2.0 264 21 1 Updated Sep 9, 2026
  • live-streaming-on-aws Public

    The live stream solution is a reference deployment that demonstrates how to deliver highly available live streaming video through an integrated workflow between Elemental Cloud and AWS.

    aws-solutions-library-samples/live-streaming-on-aws's past year of commit activity
    JavaScript 301 Apache-2.0 109 0 2 Updated Sep 9, 2026
  • live-streaming-on-aws-with-amazon-s3 Public

    Live streaming on AWS with Amazon S3 automatically configures AWS Elemental MediaLive, Amazon S3 and Amazon CloudFront to ingest, encode, package and deliver a single source live stream through the AWS Cloud. The Solution provides 3 Encoding profiles to support 1080p through 288p HTTP live streaming (HLS) outputs.

    aws-solutions-library-samples/live-streaming-on-aws-with-amazon-s3's past year of commit activity
    JavaScript 125 Apache-2.0 32 0 2 Updated Sep 9, 2026
  • video-on-demand-on-aws-foundation Public

    How to implement a video-on-demand workflow on AWS leveraging AWS Lambda, AWS Elemental MediaConvert, Amazon s3 and Amazon CloudWatch. Source code for Video on Demand on AWS Foundation solution.

    aws-solutions-library-samples/video-on-demand-on-aws-foundation's past year of commit activity
    JavaScript 144 Apache-2.0 78 5 0 Updated Sep 9, 2026