aws-solutions-library-samples
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- This Guidance demonstrates how to enhance database resiliency using a Maximum Data Availability Architecture (MD2A). It introduces MD2A, a data platform that uses APIs and SDKs to deliver full-stack resiliency from the user interface to the database layers.
- The AWS DeepRacer Event Manager (DREM) is used to run and manage all aspects of in-person events for AWS DeepRacer, an autonomous 1/18th scale race car designed to test reinforcement learning (RL) models by racing on a physical track.
osml-model-runner
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.
osml-cdk-constructs
Publicdata-lakes-on-aws
PublicEnterprise-grade, production-hardened, serverless data lake on AWS- 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
- Tag based CloudWatch dashboard uses CDK and resource groups tagging API to automatically produce CloudFormation templates for CloudWatch dashboard.
- Galaxy on AWS Guidance provides all the infrastructure components required to run Galaxy in the cloud and are preconfigured with industry best practices for infrastructure monitoring and security, cost efficiency, and data governance.
- Guidance for Media2Cloud on AWS solution (formerly known as AWS Media2Cloud Solution) is designed to demonstrate a serverless ingest framework that can quickly setup a baseline ingest workflow for placing video assets and associated metadata under management control of an AWS customer.
- The Game Analytics Pipeline solution helps game developers to apply a flexible, and scalable DataOps methodology to their games. Allowing them to continuously integrate, and continuously deploy a scalable serverless data pipeline for ingesting, storing, and analyzing telemetry data generated from games, and services.
- This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance
- This solution sets up an automated migration process for moving tables (Apache Iceberg and Hive tables) registered in AWS Glue Table Catalog and stored in Amazon S3 general-purpose buckets to Amazon S3 Table buckets using AWS Step Functions, and Amazon EMR with Apache Spark.
- This Guidance demonstrates how developers can build applications on mobile iOS and Apple Vision Pro in the AWS Cloud using Unity—a widely-used game engine and development platform where developers can create immersive 2D and 3D interactive experiences.
- This Guidance demonstrates how to use Retrieval-Augmented Generation (RAG) for your environmental, social, and governance (ESG) or sustainability knowledge base by combining Amazon Kendra and a large language model (LLM) from Amazon Bedrock—a fully managed service offering high-performing foundation models. Designed to provide rapid insights, the