Alternatives
Products that do what Milk Infrastructure – AI that builds, deploys, manages infra does
I've been working on a platform that uses LLMs to build maintain and manage k8s clusters on any cloud. The system writes infra as code to your Github repos and automatically containerizes and scales any services (public or private). The goal is to give your average engineer a vercel-like deployment experience for any service in any language at minimal cost. We have humans involved at the moment auditing LLM outputs and keeping an eye on clusters. We are looking for folks who may be thinking about their first infra/devops hire. Just connect your github and your cloud provider. The system…
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Hey HN, I am the founder of Tensorlake. Prototyping LLM applications have become a lot easier, building decision making LLM applications that work on constantly updating data is still very challenging in production settings. The systems engineering problems that we have seen people face are - 1. Reliably process ingested content in real time if the application is sensitive to freshness of information. 2. Being able to bring in any kind of model, and run different parts of the pipeline on GPUs and CPUs. 3. Fault Tolerance to ingestion spike, compute infrastructure failure. 4. Scaling compute,…
2024 · getindexify.ai
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Hey HN, I am proud to show you guys that I have built an open source alternative to Azure OpenAI services. Azure OpenAI services was born out of companies needing enhanced security and access control for using different GPT models. I want to build an OSS version of Azure OpenAI services that people could self host in their own infrastructure. "How can I track LLM spend per API key?" "Can I create a development OpenAI API key with limited access for Bob?" "Can I see my LLM spend breakdown by models and endpoints?" "Can I create 100 OpenAI API keys that my students could use in a classroom…
2023 · github.com
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Hey folks, I’m Hassan, one of the co-founders of Infracost (https://www.infracost.io). Infracost helps engineers see and reduce the cloud cost of each infrastructure change before they merge their code. The way Infracost works is we gather pricing data from Amazon Web Services, Microsoft Azure and Google Cloud. What we call a ‘Pricing Service’, which now holds around 9 million live price points (!!). Then we map these prices to infrastructure code. Once the mapping is done, it enables us to show the cost impact of a code change before it is merged, directly in GitHub, GitLab etc.…
Jan 2026 · dashboard.infracost.io
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Manage AWS, GCP, Azure, Kubernetes, and 45+ cloud providers from one unified desktop and web app. SSH terminals, SQL editor, K8s exec, storage browser, and more.
Jul 2026 · infrawrench.com
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I've built this to make it easy to host your own infra for lightweight VMs at large scale. Intended for exec of AI-generated code, for CICD runners, or for off-chain AI DApps. Mainly to avoid Docker-in-Docker dangers and mess. Super easy to use with CLI / Python SDK, friendly to AI engs who usually don't like to mess with VM orchestration and networking too much. Defense-in-depth philosophy. Would love to get feedback (and contributors: clear & exciting roadmap!), thx
Oct 2025 · github.com
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Recently featured in a LangChain blog https://blog.langchain.dev/empowering-development-with-flowt... , use LLMs to construct an API first runnable workflow with an IDE experience.
2024 · github.com
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We’ve been building a Cloud-Managed Hypervisor that makes running applications on your own servers as effortless as the public cloud. Over my career I’ve watched the transition from on-prem to public cloud. The cloud paradigm shift is as much about empowering engineers as it is about elastic infrastructure, but the tooling for on-prem and private clouds is at best heavyweight and at worst stuck in the last century. We've tackled some interesting problems in the process of building this, such as providing a cloud-style metadata service from our platform. We’d love for you to read our story…
2023 · gallium.cloud
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I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
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Hi guys, we're Wilhem from Paris and Jean-Daniel from Tokyo, software engineers with a passion for all things cloud (IaaS, PaaS, SaaS). We recently decided to tackle the problem of Capacity Planning with Stacktical, a Scalability Prediction service (https://stacktical.com). For a decade, we've been observing our clients and colleagues trying to nail down their strategy using repeated cycles of defining, collecting and interpreting load testing campaigns. It's funny how most people don't realize how demanding the work of infrastructure managers and their teams really is... While…
2016
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Here is a production-first Keras-inspired LM framework, built with the advice of François Chollet (ex-Google, creator of Keras and ARC-AGI), our technical advisor. This system have already been deployed in production with our clients (which is why we have already every LLMOps practice implemented). It is also compatible with Jupyter and Marimo to integrate seamlessly in you Data Scientists workflows. You can try the code examples online on HF space and you can find more information in the documentation and FAQ. If you have any feedback for us don't hesitate to join our discord! More releases…
2025 · github.com
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2021 · github.com
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2023 · llm-atc.readthedocs.io
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hi everyone. how does moving llm call prompts and output structure definitions away from code into configuration land sound? would you use something like this if it was stable and well documented enough? please don't hold back the criticism. i appreciate all feedback (constructive & otherwise).
2024 · github.com
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