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Top 12 Go Mlops Projects
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Weaviate
Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
Project mention: Vector database built for scalable similarity search | news.ycombinator.com | 2023-03-25tbh. Looks like a huge overengineered legacy project. What is the clue to having all these ANN indexes in place? Is it a kinda art collection? What is the sense when you can just have HNSW in memory, with quantization, or on disk, GPU accelerated, etc. There are already better alternatives like Qdrant, which is written in Rust and super performant https://github.com/qdrant/qdrant, or Weaviate with GraphQL interface https://github.com/weaviate/weaviate
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
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Project mention: What’s your process for deploying a data pipeline from a notebook, running it, and managing it in production? | reddit.com/r/dataengineering | 2022-10-13
Feature store: new hot one: https://www.featureform.com/
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onepanel
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
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Hi everyone!
We've been working on making data teams more productive with Aqueduct for over a year, and we're really excited to share what we've been building.
There's a large (and growing!) number of programmers in the world who understand data and can solve business problems but don't want to spend their time wrangling low-level cloud infrastructure to get their work into the cloud. The existing MLOps tools that claim to solve this problem have been built by & for software teams, and they're incredibly complicated.
With Aqueduct, we've built a tool that's designed for data teams and abstracts away the underlying infrastructure. Aqueduct has a simple Python API that allows you to define a workflow as a composition of Python functions. Those workflows can be easily connected to data sources and can be run anywhere from your laptop to a Kubernetes cluster in the cloud. Once a workflow's running, Aqueduct has lightweight hooks to compute metrics and run tests over your pipelines to ensure they're producing high-quality results.
To learn more about what we're building, check out our GitHub repo or join our community Slack:
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terraform-provider-iterative
☁️ Terraform plugin for machine learning workloads: spot instance recovery & auto-termination | AWS, GCP, Azure, Kubernetes
You should look at terraform, and at the provider from iterative, the guys begind DVC, https://registry.terraform.io/providers/iterative/iterative/latest/docs
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Project mention: 🐂 🌾 Oxen.ai - Blazing Fast Unstructured Data Version Control, built in Rust | reddit.com/r/rust | 2023-02-16
There is also https://github.com/kevin-hanselman/dud
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SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
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distributed-inference
A project to demonstrate an approach to designing cross-language and distributed pipeline in deep learning/machine learning domain, using WebRTC and Redis Streams.
Project mention: Distributed Inference - Apply Deep Learning to WebRTC video frames w/Redis Streams | reddit.com/r/golang | 2023-02-05You can find it at: https://github.com/adalkiran/distributed-inference
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kubernetes-operator-roiergasias
'Roiergasias' kubernetes operator is meant to address a fundamental requirement of any data science / machine learning project running their pipelines on Kubernetes - which is to quickly provision a declarative data pipeline (on demand) for their various project needs using simple kubectl commands. Basically, implementing the concept of No Ops. The fundamental principle is to utilise best of docker, kubernetes and programming language features to run a workflow with minimal workflow definition s
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
The latest post mention was on 2023-03-25.
Go Mlops related posts
- 🐂 🌾 Oxen.ai - Blazing Fast Unstructured Data Version Control, built in Rust
- Show HN: Reproducible development environments using starlark, without Nix
- Kubeflow, Jupyter notebook online. Question to community [D]
- Show HN: envd – development environment for AI/ML, based on Docker buildkit
- GitHub - tensorchord/envd: 🏕️ Development environment for machine learning
- A command-line tool to create development environments for AI/ML based on build
- A command-line tool to create development environments for AI/ML
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A note from our sponsor - InfluxDB
www.influxdata.com | 28 Mar 2023
Index
What are some of the best open-source Mlops projects in Go? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Weaviate | 3,771 |
| 2 | envd | 1,548 |
| 3 | featureform | 1,230 |
| 4 | onepanel | 659 |
| 5 | aqueduct | 409 |
| 6 | terraform-provider-iterative | 275 |
| 7 | dud | 129 |
| 8 | oomstore | 78 |
| 9 | beneath | 76 |
| 10 | distributed-inference | 26 |
| 11 | kubernetes-operator-roiergasias | 7 |
| 12 | sdk-go | 3 |
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