Work · alternatives · 2026
24 alternatives to Dstack – a command-line utility to provision infra for ML workflows
Hi. :) I’m Andrey, the creator of dstack. I started this project while I was working at JetBrains where I helped the PyCharm team to improve support for Jupyter notebooks. As I was in close contact with many ML devs (who used PyCharm) I was able to see their struggle with running ML workflows. Unlike traditional dev workflows, ML workflows are difficult to run on a local machine (due to the lack of memory, more CPUs/GPUs, etc). This is why people often have to use remote machines (e.g. via SSH), or adopt one of the end-to-end MLOps platforms. Using remote machines is not difficult but…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Dstack – a command-line utility to provision infra for ML workflows launched in 2022; newer entries below may have overtaken it.
- 1DA
Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020 · its alternatives →
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dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters.
2024 · dstack.ai · its alternatives →
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Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
2019 · github.com · its alternatives →
- 6
TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
- 7
My immediate reaction to today's news that Splunk was being acquired was to comment in the HN discussion for that story: "I hated Splunk so much that I spent a couple days a few months ago writing a single 1200 line python script that does absolutely everything I need in terms of automatic log collection, ingestion, and analysis from a fleet of cloud instances. It pulls in all the log lines, enriches them with useful metadata like the IP address of the instance, the machine name, the log source, the datetime, etc. and stores it all in SQlite, which it then exposes to a very convenient web…
2023 · github.com · its alternatives →
- 8
Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io · its alternatives →
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Fast and simple IT automation and configuration management
2016 · its alternatives →
- 10
dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters.
2020 · dstack.ai · its alternatives →
- 11
Modelbit▲125Heroku for Data Science, from the founders of Periscope Data
2023 · modelbit.com · its alternatives →
- 12OA
A lightweight engine for durable execution / deterministic workflows I built with Rust, wasmtime and the WASM Component Model. Its main use is running reliable, long-running workflows that can automatically resume after failures. Looking for feedback on the approach and potential use cases!
2025 · obeli.sk · its alternatives →
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I started building a couple of years ago because I found no easy existing solution to build Slack bots that can be composed from/organized into plugins. Existing libraries like Bolt make it pretty easy to develop Slack bots, but hard to organize and scale the code base of your bot. I was also missing some crucial features such as scheduling actions for your bot. So I wrote my own framework! I recently rewrote the complete framework to make use of asyncio and the newest Slack SDK Let me know what you think!
2022 · github.com · its alternatives →
- 15
Heya HN, after spending +1 year building an ML-driven analytics product (that didn't pan out unfortunately), I've pivoted to solving a problem my team and I found while building the previous product … why the hell is it so hard to move a model from a Jupyter notebook, to a development server, then to a production pipeline!? To solve this my team and I started the open source KitOps project under the Apache 2 license. KitOps includes the Kit CLI that uses a Kitfile manifest to create ModelKits: 1. The kit CLI packages your model, datasets, code, and configuration into an OCI compliant…
2024 · kitops.ml · its alternatives →
- 16RS
2016 · rowstack.com · its alternatives →
- 17
This is a little project I've been working on for a while in order to better learn Python. Although IRC may not exactly be the most exciting medium, I still find it to be fun and useful, this interest lead me to writing a bot. In doing this I realized that what would actually be more interesting would be if I had a framework. There may already be such a thing, certainly there are IRC libraries, but I don't know if they're well-suited to deploying bots. At any rate if for no other reason than the fact that I am relatively new to programming and eager to learn I decided to build a framework.…
2011 · github.com · its alternatives →
- 18
Built this Python package because I wanted to run hardware controlling ML stuff and other control algorithms directly connected to industrial I/O hardware without jumping into annoying PLC toolchains (Windows only, licensing hassle, no editor choice, proprietary version control - you name it). For sure its not for ms‑cycle loops, or uptime critical production stuff, but in applications with relaxed timing it allows for fast iteration on the setup - making prototyping a pleasure. Its easy to use, has no dependencies beside Python, its fully type annotated and MIT licensed. Internal it…
2025 · github.com · its alternatives →
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I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a compiler that simply converts the model into plain source code with no dependencies, and it actually solved all my deployment problems. Now I'm curious if it can help anyone else too. Through the link you can submit your model file (Keras h5, onnx soon to be supported), and I'll…
2023 · waveworks.dk · its alternatives →
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RunStack▲5Build, test, and run LLM workflows — visually.
Jan 2026 · getrunstack.com · its alternatives →
- 22
Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…
2024 · github.com · its alternatives →
- 23PL
Hi! I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others. It supports all main Python ML frameworks (sklearn, torch, xgboost, …) and integrates with the quality assurance solution we are building at Giskard AI (https://giskard.ai) to systematically test models before putting them in production. It is still a beta and I would love to hear your feedback if you have the time to try it out. We have quite a few tutorials in the docs with ready-made colab notebooks to…
2023 · docs.giskard.ai · its alternatives →
- 24UD
I've been working a fair bit with DSPy lately, and I did some work in combining the benefits of vector search and LLMs (via a DSPy pipeline) to disambiguate records with a high degree of accuracy to help enrich a dataset. The blog post shows how this approach scales well, is very cost-effective and super concise - all it takes is < 100 lines of DSPy code and it all runs async. The code to reproduce is in this repo if anyone's interested (all tools are 100% free and open source, and the methodology will work with open weight LLMs too).…
2025 · blog.kuzudb.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →