Usage 2.0 – Cut AWS Spend by 57% in 5 Minutes
Hey HN: Kaveh here, the founder of https://www.usage.ai/ We launched on Hacker News for the first time early last year, and we've made a lot of progress since then. We've saved tens of millions of dollars for companies, and we are even more excited to announce the launch of a new product: insured reservations for RDS! We worked closely with AWS on this feature and are excited to finally make it generally available. We help companies drive down AWS EC2 & RDS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs…
In plain words
Usage 2.0 is a platform that helps companies reduce AWS spending on EC2 and RDS instances. It automates the process of managing cloud costs and reservations, which typically requires significant time from engineering teams. The tool includes insured reservations for RDS, developed in collaboration with AWS, and claims to have saved tens of millions of dollars across its customers. It is designed for DevOps engineers and software teams looking to optimize their cloud infrastructure expenses without manual cost management.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN: Kaveh here, the founder of https://www.usage.ai/ We launched on Hacker News for the first time early last year, and we've made a lot of progress since then. We've saved tens of millions of dollars for companies, and we are even more excited to announce the launch of a new product: insured reservations for RDS! We worked closely with AWS on this feature and are excited to finally make it generally available. We help companies drive down AWS EC2 & RDS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs and reservations rather than focusing on business problems. In the early days, we saw horror stories of customers with millions of dollars in monthly on-demand spend simply because their finance team didn't want them committing to AWS. Worst yet, we've seen AWS users who ended up overspending by hundreds of thousands of dollars a month because they overcommitted their Savings Plan commitment. Here's how it works: We are typically brought in by a DevOps manager to cut AWS EC2 costs. The app is entirely self-service and the savings are generated automatically, typically we do this live on a call. On average, we reduce AWS EC2 spend by 50% for 5 minutes of work, and RDS spend by ~30%. To reduce by 50%+, we don't touch the instances, require any code change, or change the performance of your instances. We buy Reserved Instances on your behalf (a billing layer change only) and bundle them with guaranteed buyback. So you get the steep 57% savings of 3-year no-upfront RIs with none of the commitment. We make money off of a 20% Savings Fee. Happy to chat directly [email protected] Have you experienced any issues with managing your company or organization's AWS expenses? We'd love to hear your feedback and ideas!
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, March 2023
the whole month →




- BI
I'm a big fan of the BBC podcast In Our Time -- and (like most people) I've been playing with the OpenAI APIs. In Our Time has almost 1,000 episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all still available, so it's my starting point to learn about most topics. But it's not well organised. So here are the episodes sorted by library code. It's fun to explore. Web scraping is usually pretty tedious, but I found that I could send the minimised HTML to GPT-3 and get (almost) perfect JSON back: the prompt includes the Typescript definition. At the same time I…
AI · 2023 · genmon.github.io