Alternatives
Products that do what nAG Optimization Cloud does
Run optimization jobs in parallel. No setup. Pay as you go.
- 1GC
2012 · goscale.com
- 2TC
Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
2022 · tensordock.com
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- 4FN
forkrun is the culmination of a 10-year-long journey focused on "how to make shell parallelization fast". What started as a standard "fork jobs in a loop" has turned into a lock-free, CAS-retry-loop-free, SIMD-accelerated, self-tuning, NUMA aware shell-based stream parallelization engine that is (mostly) a drop-in replacement for xargs -P and GNU parallel. On my 14-core/28-thread i9-7940x, forkrun achieves: * 200,000+ batch dispatches/sec (vs ~500 for GNU Parallel) * ~95–99% CPU utilization across all 28 logical cores, even when the workload is non-existant (bash no-ops / `:`)…
Mar 2026 · github.com
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Hi HN! We’re Yann, Edouard, and Bastien from Koyeb (https://www.koyeb.com/). We’re building a platform to let you deploy full-stack apps on high-performance hardware around the world, with zero configuration. We provide a “global serverless feeling”, without the hassle of re-writing all your apps or managing k8s complexity [1]. We built Scaleway, a cloud service provider where we designed ARM servers and provided them as cloud servers. During our time there, we saw customers struggle with the same issues while trying to deploy full-stack applications and APIs resiliently. As…
2023 · koyeb.com
- 7ST
I've been working on CloudRouter, a skill + CLI that gives coding agents like Claude Code and Codex the ability to start cloud VMs and GPUs. When an agent writes code, it usually needs to start a dev server, run tests, open a browser to verify its work. Today that all happens on your local machine. This works fine for a single task, but the agent is sharing your computer: your ports, RAM, screen. If you run multiple agents in parallel, it gets a bit chaotic. Docker helps with isolation, but it still uses your machine's resources, and doesn't give the agent a browser, a desktop, or a GPU to…
Feb 2026 · cloudrouter.dev
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We are delighted to introduce new, fully-rewritten Kraken.io featuring: - Outstanding image optimization - Intuitive, easy-to-use API - Significantly improved lossy optimization techniques - Support for Google’s WebP compression algorithm - Support for SVG file optimization - Comprehensive paid plans for API usage designed to please everyone - Free, unlimited 7-day trial on all of our plans - The free Web Interface, featuring more beauty with Retina graphics - Rackspace Cloud Files and Amazon S3 integration - Integration libraries for PHP, Ruby and Node.js
2013 · kraken.io
- 12AF
I built an unofficial CLI and MCP server for Lambda cloud GPU instances. The main idea: your AI agents can now spin up and manage Lambda GPUs for you. The MCP server exposes tools to find, launch, and terminate instances. Add it to Claude Code, Cursor, or any agent with one command and you can say things like "launch an H100, ssh in, and run big_job.py" Other features: - Notifications via Slack, Discord, or Telegram when instances are SSH-ready - 1Password support for API keys - Also includes a standalone CLI with the same functionality Written in Rust. MIT licensed. Note: This is an…
Jan 2026 · github.com
- 13SS
Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…
2023 · shadeform.ai
- 14AM
Hey all - I work at Vantage, a FinOps platform. I know AI is peak hype right now. But it has definitely changed some of our dev workflows already. So we wanted to find a way to let our customers experiment with how they can use AI to make their cloud cost management work more productive. The MCP Server acts as a connector between LLMs (right now only Claude, Cursor support it but ChatGPT and Google Gemini coming soon) and your cost and usage data on Vantage which supports 20+ cloud infra providers including AWS, Datadog, Mongo, etc. (You have to have a Vantage account to use it since it's…
2025
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For the last month or so I've been working on bewCloud, and today I'm making its source code public and open! Right now, the Dashboard (URLs + freeform notes), News (RSS/Atom/JSON feeds), and Contacts (CardDav) are working. If you have any suggestions, comments, or recommendations, I'd love to hear it. Thank you for your attention and kindness. I really appreciate it!
2024 · bewcloud.com
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2018 · cloudrun.co
- 21RT
I have posted a much earlier version of this over a year ago [0]. Since then a lot has changed. Obviously, the name has changed. This happened for the paper publication [1]. I have also optimized the speed, integrated ISA-L for special cases, limited the compression-ratio-dependent maximum memory consumption, and finally added parallelized CRC32 computation, which adds ~5% overhead no matter the number of cores used. At this point, I am leaning towards calling it production-ready although there are still many ideas for improvements. Redoing the benchmarks of the older Show HN, would look…
2023 · github.com
- 22LF
100% bootstrapped new startup. It lets you fine tune Mistral-7B and SDXL. In particular, for the LLM fine tuning we implemented a dataprep pipeline that turns websites/pdfs/doc files into question-answer pairs for training the small LLM using an big LLM. It includes a GPU scheduler that can do finegrained GPU memory scheduling (Kubernetes can only do whole-GPU, we do it per-GB of GPU memory to pack both inference and fine tuning jobs into the same fleet) to fit model instances into GPU memory to optimally trade off user facing latency with GPU memory utilization It's a pretty…
2023 · docs.helix.ml
- 23TO
Hey HN – We’re Danny and Ethan from Telophase (https://telophase.dev). We’re building automation to isolate cloud environments by tenant or team. You can think of us as an Open-Source AWS Control Tower[1]. Our CLI is a drop-in tool to manage multi-account AWS setups. To start, we support AWS Account Factory and landing zones defined in AWS CDK. We plan to support multi-project GCP and multi-subscription Azure setups soon! Features: 1. Manage accounts in code. 2. Provision accounts and their infrastructure with a single command, `telophase deploy`. 3. Deploy to a subset of accounts…
2023 · github.com
- 24IB
I wanted to play my Steam games but my aging PC couldn’t keep up, so I built Cloudy Pad - a tool to run Steam in the Cloud (GitHub: https://github.com/PierreBeucher/cloudypad) It runs on AWS, Azure, GCP, Scaleway and Paperspace with various cost optimizations and safeties: - Cost alerts - Auto stop inactive instances to avoid unwanted cost - Disk snapshots and data cleanup for cost efficiency - Spot instance support Under the hood: a Linux VM and a container running Sunshine (a streaming server https://github.com/LizardByte/Sunshine) with Steam. Most…
2025 · github.com
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