Repositories list

• guidance-for-processing-overhead-imagery-on-aws

  Public
  This Guidance demonstrates how to process remote sensing imagery using machine learning models that automatically detect and identify objects collected from satellites, unmanned aerial vehicles, and other remote sensing devices

  TypeScript

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  MIT No Attribution

  •2•14•0•0•Updated Dec 26, 2024Dec 26, 2024

• osml-model-runner-test

  Public
  Python

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  MIT No Attribution

  •0•2•0•2•Updated Dec 24, 2024Dec 24, 2024

• guidance-for-automated-geospatial-insights-engine-on-aws

  Public
  This Guidance shows how build an automated geospatial insights engine on AWS to improve supply and demand forecasting and risk management

  TypeScript

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  MIT No Attribution

  •3•4•1•6•Updated Dec 24, 2024Dec 24, 2024

• guidance-for-datalake-with-sap-and-non-sap-data-on-aws

  Public
  This Guidance demonstrates how to combine and consolidate SAP and non-SAP data from disparate sources using data lakes and machine learning services on AWS.

  Python

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  MIT No Attribution

  •1•6•0•0•Updated Dec 23, 2024Dec 23, 2024

• osml-imagery-toolkit

  Public
  Python

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  MIT No Attribution

  •0•14•0•0•Updated Dec 22, 2024Dec 22, 2024

• guidance-for-multimodal-data-processing-using-amazon-bedrock-data-automation

  Public
  This Guidance shows how Amazon Bedrock Data Automation streamlines the generation of valuable insights from unstructured multimodal content such as documents, images, audio, and videos through a unified multi-modal inference API.

  Python

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  MIT No Attribution

  •2•10•2•0•Updated Dec 22, 2024Dec 22, 2024

• osml-model-runner

  Public
  Python

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  MIT No Attribution

  •1•7•1•0•Updated Dec 21, 2024Dec 21, 2024

• guidance-for-collaborative-unified-data-and-ai-development-on-aws

  Public
  This Guidance demonstrates how to use Amazon SageMaker Unified Studio to create a unified development experience for building, deploying, executing, and monitoring end-to-end workflows across AWS data, analytics, and AI/ML services

  Jupyter Notebook

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  MIT No Attribution

  •2•5•0•1•Updated Dec 20, 2024Dec 20, 2024

• guidance-for-secure-blockchain-validation-using-aws-nitro-enclaves

  Public
  This Guidance shows how to deploy a secure, scalable, and cost-efficient blockchain key management solution for blockchain validation workloads like Ethereum 2.0 proof-of-stake networks.

  Python

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  MIT No Attribution

  •6•16•1•1•Updated Dec 20, 2024Dec 20, 2024

• guidance-for-deploying-high-performance-computing-clusters-on-aws

  Public
  This Guidance aims to instruct and guide users how to build a cloud HPC for the new NIST SP 800-223 standard using AWS Parallel Cluster

  high-performance-computingsecure-clusteringnist800-223

  MIT No Attribution

  •0•2•0•0•Updated Dec 19, 2024Dec 19, 2024

• guidance-for-similarity-search-based-retrieval-augmented-generation-on-aws

  Public
  This Guidance shows how to build an advanced question-answering application using the latest AI tools from AWS and its partners.

  MIT No Attribution

  •0•1•0•0•Updated Dec 19, 2024Dec 19, 2024

• guidance-for-simple-and-scalable-serverless-load-testing-on-aws

  Public
  This Guidance demonstrates how to set up a fully managed, distributed load testing solution using AWS services and Locust, an open-source load testing tool.

  HCL

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  MIT No Attribution

  •0•1•0•0•Updated Dec 19, 2024Dec 19, 2024

• guidance-for-automated-provisioning-of-application-ready-amazon-eks-clusters

  Public
  The EKS workload accelerator is a collection of reference implementations for Amazon EKS designed to accelerate the time it takes to provision a workload ready EKS cluster. It includes an "opinionated" set of pre-configured and integrated tools/add-ons, and best practices to support core capabilities including Autoscaling, Observability, Networking

  auto-scalingobservabilityterraform-aws+ 1eks-cluster

  HCL

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  MIT No Attribution

  •7•24•4•1•Updated Dec 18, 2024Dec 18, 2024

• guidance-for-multi-modal-data-analysis-with-aws-health-and-ml-services

  Public
  An end-to-end framework for storing, integrating, and analyzing multimodal HCLS data on AWS, using AWS HealthOmics, AWS HealthLake, AWS HealthImaging, Amazon SageMaker, Amazon Athena, Amazon QuickSight, and Amazon S3.

  Jupyter Notebook

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  MIT No Attribution

  •4•14•2•0•Updated Dec 17, 2024Dec 17, 2024

• guidance-for-data-management-core-on-aws

  Public
  The Data Fabric sample code focuses on the core data fabric implementation on AWS, providing a complete guide for deploying and using the data fabric capabilities.

  TypeScript

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  MIT No Attribution

  •3•3•1•6•Updated Dec 17, 2024Dec 17, 2024

• guidance-for-retail-analytics-using-generative-ai-on-aws

  Public
  This Guidance shows how to use large language models (LLMs) to generate SQL queries and perform data analytics, enhancing the value of your data

  Python

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  MIT No Attribution

  •0•2•0•3•Updated Dec 16, 2024Dec 16, 2024

• osml-cesium-globe

  Public
  TypeScript

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  MIT No Attribution

  •1•2•0•3•Updated Dec 14, 2024Dec 14, 2024

• guidance-for-retrieving-data-using-natural-language-queries-on-aws

  Public
  Use natural language to Generate Amazon Athena SQL queries to fetch data.

  Python

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  MIT No Attribution

  •1•1•0•2•Updated Dec 13, 2024Dec 13, 2024

• guidance-for-multimodal-video-analytics-of-smart-product-subscription-services-on-aws

  Public
  This Guidance demonstrates how providers offering smart product subscriptions can use large language model (LLM) inferencing to create innovative video analytics services that drive customer value and revenue.

  Python

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  MIT No Attribution

  •0•3•0•2•Updated Dec 12, 2024Dec 12, 2024

• guidance-for-building-a-real-time-bidder-for-advertising-on-aws

  Public
  This Guidance helps you assess ad opportunities at scale using real time bidding (RTB)

  Go

  •

  Apache License 2.0

  •10•36•0•9•Updated Dec 12, 2024Dec 12, 2024

• guidance-for-smart-and-sustainable-buildings-on-aws

  Public
  This Guidance demonstrates how to integrate building systems, assets, and sensors to enable real-time and historical insights for sustainable building management.

  TypeScript

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  MIT No Attribution

  •0•5•0•0•Updated Dec 11, 2024Dec 11, 2024

• guidance-for-multi-account-environment-on-amazon-quicksight

  Public
  Guidance for helping customers with a prescriptive guidance to build Amazon QuickSight environments spanning across multiple accounts in line with AWS' best practices for multi-account strategy. This approach provides improved isolation, security, access management, and cost tracking.

  Python

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  MIT No Attribution

  •1•4•0•0•Updated Dec 11, 2024Dec 11, 2024

• guidance-for-custom-search-of-an-enterprise-knowledge-base-with-amazon-opensearch-service

  Public
  This Guidance demonstrates how to build an application for search based on the information in an enterprise knowledge base through the deployment of interface nodes, including large language models (LLMs).

  Python

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  MIT No Attribution

  •4•14•2•11•Updated Dec 11, 2024Dec 11, 2024

• osml-cdk-constructs

  Public
  TypeScript

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  MIT No Attribution

  •0•5•0•0•Updated Dec 7, 2024Dec 7, 2024

• guidance-for-carbon-data-lake-on-aws

  Public
  This Guidance, with the sample code, can be used to deploy a carbon data lake to the AWS Cloud using an AWS Cloud Development Kit (AWS CDK)

  Jupyter Notebook

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  Apache License 2.0

  •14•21•3•3•Updated Dec 5, 2024Dec 5, 2024

• guidance-for-custom-game-backend-hosting-on-aws

  Public
  The AWS Game Backend Framework allows you to integrate your game clients with AWS backend services, with secure scalable identity management and authentication, and integrations to commonly used game platform identity providers and game engines.

  awsgamesbackend+ 3unitygodot4unreal-engine-5

  Python

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  MIT No Attribution

  •22•45•1•4•Updated Dec 5, 2024Dec 5, 2024

• guidance-for-ai-assistants-with-amazon-q-business

  Public
  This Guidance demonstrates how enterprises can unlock the value of their data through the powerful generative AI capabilities of Amazon Q Business

  MIT No Attribution

  •2•3•0•1•Updated Dec 4, 2024Dec 4, 2024

• guidance-for-asynchronous-inference-with-stable-diffusion-on-aws

  Public
  Stable Diffusion is a popular Open Source project for generating images using Gen AI. Building a scalable and cost efficient inference solution is a common challenge. This project shows how to use AWS serverless and container services to build an end-to-end scalable, secure and price effecient asynchronous image generation architecture.

  aiserverlessgenerative+ 2eks-clusterstable-diffusion

  Python

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  MIT No Attribution

  •6•29•2•0•Updated Dec 4, 2024Dec 4, 2024

• guidance-for-automating-sap-configuration-health-checks-on-aws

  Public
  This Guidance shows how to automate evaluation of your SAP landscape on AWS against 100+ health checks and architecture best practices aligned with the AWS Well-Architected Framework.

  MIT No Attribution

  •2•3•1•1•Updated Dec 3, 2024Dec 3, 2024

• guidance-for-modernizing-electric-vehicle-charging-on-aws

  Public
  This guidance demonstrates how the OCPP Gateway acts as a proxy between OCPP and MQTT, enabling integration with AWS IoT Core and downstream CPO services built on AWS.

  iotawsocpp+ 5iot-coreevev-chargingecs-fargatecpo

  TypeScript

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  MIT No Attribution

  •30•78•3•8•Updated Dec 2, 2024Dec 2, 2024