Alternatives
Products that do what Terradev does
End To End GPU Provisioning
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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
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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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Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://oblivus.com/cloud - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be…
2023 · oblivus.com
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2024 · github.com
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2020 · github.com
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Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…
2024 · github.com
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2021 · diggerdev.com
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2022 · terragen.dev
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Simulate AWS, GCP & DigitalOcean without paying the bill
Jun 2026 · cloudworldmodel.ai
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Hi HN, we’re Nick and Drew, and we’re building boxes.dev – the first cloud-only agentic dev environment (ADE) that gives every Codex and Claude Code agent its own cloud computer. We’re two engineers who previously built Gem (co-founder/CTO and first hire), and we spent the last year coding almost exclusively using Codex and Claude Code. It’s been a huge change to how we code, and it’s been exhilarating seeing the models keep getting better – but we eventually realized that developing on localhost was holding us back: - Git worktrees are clunky to set up and use for parallelizing work -…
Jun 2026 · boxes.dev
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Hello Hacker News! We're Roxane, Julien, Pierre, Mawen and Stephane from Anyshift.io. We are building a GitHub app (and platform) that detects Terraform complex dependencies (hardcoded values, intricated-modules, shadow IT…), flags potential breakages, and provides a Terraform ‘Superplan’ for your changes. To do that we create and maintain a digital twin of your infrastructure using Neo4j. - 2 min demo : https://app.guideflow.com/player/dkd2en3t9r - try it now: https://app.anyshift.io/ (5min setup). We experienced how dealing with IaC/Terraform is…
2025 · app.anyshift.io
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We have been working on Multy, an open-source[1] tool that enables developers to deploy and switch to any cloud - AWS, Azure and GCP for now. We realized that, even when using Terraform, writing infrastructure code is very different for each cloud provider. This means changing clouds or deploying the same infrastructure in multiple clouds requires rewriting the same thing multiple times. And even though most core resources have the same functionality, developers need to learn a new provider and all its nuances when choosing a new cloud. This is why we built Multy. Multy is currently…
2022 · github.com
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We have been working on multy.dev, an open-source cloud agnostic API that makes it easy to deploy the same infrastructure to any cloud provider using native managed services. The motivation was the realisation that, even when using Terraform, migrating infrastructure code requires an end-to-end re-write. Even though most core resources are the same in any major cloud, developers need to learn a new provider to deploy the same infrastructure when moving providers. We are still in early days of development and currently support the core services from AWS and Azure: - Networking…
2022 · multy.dev
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