cdk-appsync-project
aws-virtual-gpu-device-plugin
| cdk-appsync-project | aws-virtual-gpu-device-plugin | |
|---|---|---|
| 1 | 3 | |
| 12 | 132 | |
| - | - | |
| 0.0 | 0.0 | |
| about 1 year ago | over 1 year ago | |
| TypeScript | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cdk-appsync-project
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AWS open source news and updates No.41
Using projen to deploy AWS AppSync with AWS CDK Ken Winner shares a very brief post on how you can use projen, a tool I mentioned a few issues ago from Elad Ben-Israel, to scaffold out everything you need when setting up your projects. In this case Ken has created cdk-appsync-project to demonstrate how you would do this for a sample AWS AppSync application integrated with AWS Cognito. As Ken points out, projen helps you address some of the things that AWS CDK does not. This is a two minute read, so head over and check this out.
aws-virtual-gpu-device-plugin
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Share a GPU between pods on AWS EKS
This project (available here) uses the k8s device plugin described by this AWS blog post to make GPU-based nodes publish the amount of GPU resource they have available. Instead of the amount of VRAM available or some abstract metric, this plugin advertises the amount of pods/processes that can be connected to the GPU. This is controlled by what is called by NVIDIA as Multi-Process Service (MPS).
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[D] Serverless solutions for GPU inference (if there's such a thing)
AWS has apparently already started using this type of tech as of this year (see lost below). They mention virtual gpus but this particular solution probably won't help OP unfortunately. https://aws.amazon.com/blogs/opensource/virtual-gpu-device-plugin-for-inference-workload-in-kubernetes/
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AWS open source news and updates No.41
The post explores GPU device plugin to address how to set fractional number of GPU resource for each pod by implementing the Kubernetes device plugin and Nvidia MPS. This project has been open sourced on GitHub.
What are some alternatives?
cfn-diagram - CLI tool to visualise CloudFormation/SAM/CDK stacks as visjs networks, draw.io or ascii-art diagrams.
kserve - Standardized Serverless ML Inference Platform on Kubernetes
aws-sdk-js-v3 - Modularized AWS SDK for JavaScript.
aws-eks-share-gpu - How to share the same GPU between pods on AWS EKS
aws-robomaker-sample-application-meirorunner - This sample application can run on AWS RoboMaker and demonstrate reinforcement learning machine learning for robotics
k8s-device-plugin - NVIDIA device plugin for Kubernetes
Lambda-Extension-Secrets-Wrapper-Python - Repository with my AWS Lambda Wrapper for reading parameters from SSM
determined - Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
booster - Software development framework specialized in building highly scalable microservices with CQRS and Event-Sourcing. It uses the semantics of the code to build a fully working GraphQL API that supports real-time subscriptions.
terraform-provider-kubernetes - Terraform Kubernetes provider
kube-secret-syncer - A Kubernetes operator to sync secrets from AWS Secrets Manager