BentoML
cloud-nuke
BentoML | cloud-nuke | |
---|---|---|
16 | 35 | |
6,558 | 2,654 | |
1.8% | 0.6% | |
9.8 | 9.0 | |
3 days ago | 5 days ago | |
Python | Go | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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.
BentoML
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Who's hiring developer advocates? (December 2023)
Link to GitHub -->
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project ideas/advice for entry-level grad jobs?
there are a few tools you can use as "cheat mode" shortcuts to give you a leg up as you're getting started. here's one: https://github.com/bentoml/BentoML
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Two high schoolers trying to use Azure/GCP/AWS- need help!
Then you can look into bentoml https://github.com/bentoml/BentoML which is used to deploy ml stuff with many more benifits.
- Ask HN: Who is hiring? (November 2022)
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[D] How to get the fastest PyTorch inference and what is the "best" model serving framework?
For 2), I am aware of a few options. Triton inference server is an obvious one as is the ‘transformer-deploy’ version from LDS. My only reservation here is that they require the model compilation or are architecture specific. I am aware of others like Bento, Ray serving and TorchServe. Ideally I would have something that allows any (PyTorch model) to be used without the extra compilation effort (or at least optionally) and has some convenience things like ease of use, easy to deploy, easy to host multiple models and can perform some dynamic batching. Anyway, I am really interested to hear people's experience here as I know there are now quite a few options! Any help is appreciated! Disclaimer - I have no affiliation or are connected in any way with the libraries or companies listed here. These are just the ones I know of. Thanks in advance.
- PostgresML is 8-40x faster than Python HTTP microservices
- Congratulations on v1.0, BentoML 🍱 ! You are r/mlops OSS of the month!
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Show HN: Truss – serve any ML model, anywhere, without boilerplate code
In this category I’m a big fan of https://github.com/bentoml/BentoML
What I like about it is their idiomatic developer experience. It reminds me of other Pythonic frameworks like Flask and Django in a good way.
I have no affiliation with them whatsoever, just an admirer.
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[P] Introducing BentoML 1.0 - A faster way to ship your models to production
Github Page: https://github.com/bentoml/BentoML
- Show HN: BentoML goes 1.0 – A faster way to ship your models to production
cloud-nuke
- OpenTofu 1.7.0 is out with State Encryption, Dynamic Provider-defined Functions
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OpenTF Announces Fork of Terraform
- https://gruntwork.io/ - https://github.com/gruntwork-io
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Testing IaC Scripts 🧪
After discussing the testing approaches suggested by the two IaC providers Terraform and Pulumi, in the next post we will take a look at the dedicated IaC testing providers takes on this topic. Here we will have a look at Gruntwork and Snyk. So, stay tuned if you are interessted!
- Kubernetes on cloud practice
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Migrate from terragrunt to terraform
Or your working on gruntwork.io company, this is the only the thing that makes ok all what you say here. However I believe they can make better product instead of angry chat on reddit without getting in details.
- What NEEDS to be teared down after doing a project in AWS?
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Ask HN: I have an initial platform but not a product. Any SaaS ideas?
Like others have said, your infra might itself be the product.
Look at https://gruntwork.io.
They’ve made a lucrative business by selling infra scripts that others can use.
And their subscription model means they keep the scripts up to date.
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The Production Checklist & Terraform Advice
Have been checking out terragrunt and terratest lately(part of https://gruntwork.io)
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Ask HN: Who is hiring? (December 2022)
Gruntwork | Software Engineers (Principal, Staff) | 100% Remote/US time zones | Full-time | https://gruntwork.io/
We aim to improve humanity's most important invention: Software. Our product enables software teams to launch and maintain production-grade cloud infrastructure in days, not months. We create the building blocks that devs use to make launching in AWS with infrastructure as code 10x better.
We work with AWS, K8s, Terraform, Go, Typescript, and React/Next. We’re a small team (~20 people), but our clients include Toyota, Adobe, TicketMaster, Verizon, and lots of startups.
We are profitable, self-funded (no investors, no debt), pay salaries, equity, and bonuses according to transparent formulas, and are very focused on building a company we're proud of. We are 100% remote, with 2/3 of our team in the USA and 1/3 in Europe. We have company-wide in-person meetups every few months. We welcome applicants from all backgrounds.
Our measure of a successful Grunt is (1) think like an owner, (2) make impact, (3) communicate effectively, (4) be a good person. If this sounds like you, we're hiring!
- Principal Software Engineer
- Staff Software Engineer
Learn more at https://gruntwork.io/careers/
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Best way to install and use kubernetes for learning
Most people hesitate to use cloud hosted offerings for development. First of all, most providers have a generous free tier for devs, which can get you started. Secondly I recommend using tools like cloudnuke to avoid paying for cloud resources you're not using.
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
aws-nuke - Nuke a whole AWS account and delete all its resources.
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
terraform-modules - Xenit Terraform modules
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
former2 - Generate CloudFormation / Terraform / Troposphere templates from your existing AWS resources.
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
terraform
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
govuk-aws - Legacy AWS infrastructure for GOV.UK. Gradually being updated and moved to govuk-infrastructure.
kubeflow - Machine Learning Toolkit for Kubernetes
learn-cantrill-io-labs - Standard and Advanced Demos for learn.cantrill.io courses