John Ritsema's starred repositories
autocomplete
IDE-style autocomplete for your existing terminal & shell
terraform-aws-github-runner
Terraform module for scalable GitHub action runners on AWS
components
React components for Cloudscape Design System
chinook-database
Sample database for SQL Server, Oracle, MySQL, PostgreSQL, SQLite, DB2
stargz-snapshotter
Fast container image distribution plugin with lazy pulling
soci-snapshotter
A containerd snapshotter plugin which enables standard OCI images to be lazily loaded without requiring a build-time conversion step.
awesome-claude-prompts
This repo includes Claude prompt curation to use Claude better.
amazon-bedrock-samples
This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models
terraform-aws-observability-accelerator
Open source project to help accelerate and ease observability setup on AWS environments
serverless-pdf-chat
LLM-powered document chat using Amazon Bedrock and AWS Serverless
karpenter-blueprints
Karpenter Blueprints is a list of common workload scenarios following best practices. You'll find here details of why configuring the Karpenter and Kubernetes objects in such a way is important when using Karpenter on EKS.
generative-ai-application-builder-on-aws
Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in AI. The solution includes integrations with Amazon Bedrock and its included LLMs, such as Amazon Titan, and pre-built connectors for 3rd-party LLMs.
guidance-for-natural-language-queries-of-relational-databases-on-aws
Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.
reference-implementation-aws
This is the reference implementation of CNOE and its toolings on AWS
python-fm-playground
Explore how you can use Amazon Bedrock with Python in a dynamic environment! It includes a FastAPI app and a Next.js frontend, perfect for learning and experimentation with generative AI on AWS.
handlebars
Handlebars template engine for Deno
aws-service-catalog-engine-for-tfc
Use to provision HashiCorp Terraform Cloud products in AWS Service Catalog
guidance-for-generating-product-descriptions-with-amazon-bedrock
Building Product Descriptions with AWS Bedrock and Rekognition