CloudClerk. We struggled with BigQuery finops, so we decided to fight
Hello HN, Lucas here. I’ve been working with BigQuery for ~5 years, mostly in large (petabyte-scale) environments. Over time we ended up spending a lot of money and engineering effort just trying to understand where costs were coming from, why and how to optimize them. At some point we decided to stop, leverage all our past experience and spend a full cycle building tooling focused on cost visibility and optimization. The main goal was to regain ownership of cost data and make it possible to understand our cost structure in under a minute, while aligning the views of engineering and FinOps…
What it does
In the maker’s words, at launch
Hello HN, Lucas here. I’ve been working with BigQuery for ~5 years, mostly in large (petabyte-scale) environments. Over time we ended up spending a lot of money and engineering effort just trying to understand where costs were coming from, why and how to optimize them. At some point we decided to stop, leverage all our past experience and spend a full cycle building tooling focused on cost visibility and optimization. The main goal was to regain ownership of cost data and make it possible to understand our cost structure in under a minute, while aligning the views of engineering and FinOps at the project level. To complement these, and given the recent rise of AI, we also built agents that review usage patterns and selected KPIs to surface issues and suggest concrete optimizations (always through an encoding layer for privacy). This ended up working well for us: we reduced monthly BigQuery spend by ~43% and made cost considerations part of normal engineering workflows instead of a separate FinOps exercise. After validating it with a few other teams facing similar problems, we decided to ship it publicly in November. Some transparency items to consider: - We only work with bigquery related information, not all gcs. - While we already support most sources of cost, the project is in constant development. If you use an uncommon feature it may not be covered, but we will implement it for you. - The larger the company the larger the impact, since there tends to be larger technical debt. Nonetheless, we've seen significant impact in lower scale startups. - We dont need labels. Labels are great, and should be taken care of, but we do not depend on them to provide insights. Happy to share details, lessons learned, or tradeoffs if this is interesting to others dealing with large-scale data warehouse costs. Check us out at https://www.cloudclerk.ai/
Does the same job
all alternatives →- IBI built a service to help companies save on their AWS bills2020 · ▲73
Hey HN: I'm Kaveh, the founder of Usage (https://www.usage.ai/) We help companies drive down AWS costs. Why? Because the way it's done now is a pain. Stakeholders, especially engineers, are required to spend unnecessary time manually finding underutilized or overly expensive EC2s. We believe the optimization process should be done automatically through a series of sophisticated algorithms. At the moment, there are over 70,000 AWS EC2 prices - doing that manually just won't scale at most organizations. My background is in software engineering. Previous to founding Usage, I…
- IWI wrote a book about using Lambda with Go2021 · ▲103
Hi HN! During the last few years, I worked on a few applications built with Go, running on AWS Lambda. As I got to know the platform better, I started to find Go & Lambda to be a really productive combination. The applications were fast, and they ended up being much cheaper to run than what my team & I had built before. It’s probably not the best platform for _every_ application, but I was surprised at how much of our workload worked well on it. As we brought new engineers on to our team and helped them get up to speed with the stack, I found that we were covering a lot of the same topics…
- IBI built a service to help companies reduce AWS spend by 50%2022 · usage.ai · ▲123
Hey HN: Kaveh here, the founder of https://www.usage.ai/ We help companies drive down AWS EC2 spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs rather than focusing on business problems. Previous to founding Usage, I worked on high-performance computing research at JP Morgan Chase and as a software engineer at a number of smaller startups. 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,…
- WBWe built a product to help companies reduce AWS/GCP/Azure spend by 50%2024 · ▲5
Hey HN: Kaveh here, founder of https://www.usage.ai/ We help companies drive down AWS, GCP, and Azure spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs rather than focusing on business problems. I have been building Usage AI for almost 4 years now (4 year anniversary in 1 month from now!) with an incredible group of founding people. We started as a product just to help lower AWS EC2 costs, and now we do all major AWS services (such as RDS, OpenSearch, ElastiCache, and Redshift with more on the way) and other…
- ABA Better Alternative to the AWS Console2022 · ▲6
Hey HN: Kaveh here, the founder of https://www.usage.ai/ We launched a new free tool to help engineers understand their AWS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up end up becoming cloud accountants or end up forking over a big % of their AWS bill for a tool to understand costs rather than focusing on business problems. Previous to founding Usage, I worked on high-performance computing research at JP Morgan Chase and as a software engineer at a number of smaller startups. Here's how this new tool works: It's fully self-serve and…
- BBBiq Blue – Destroy Your Google BigQuery Costs2023 · biq.blue · ▲5
Hi! I've been working on Biq Blue, a tool engineered to analyze your Google BigQuery tables, storage, and requests with the goal of drastically reducing your costs. Currently in early free beta, Biq Blue has already demonstrated its effectiveness on some big data sets. Essentially, it's a server that connects to your BigQuery database via the gcloud CLI, conducts analyses, and opens an HTTP port to serve both results and recommendations over web pages. Your data stays local, ensuring it never leaves your enterprise (I may only collects anonymous usage statistics and the email tied to your…
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Hey HN! I wanted to share something I built over the last few weeks: isometric.nyc is a massive isometric pixel art map of NYC, built with nano banana and coding agents. I didn't write a single line of code. Of course no-code doesn't mean no-engineering. This project took a lot more manual labor than I'd hoped! I wrote a deep dive on the workflow and some thoughts about the future of AI coding and creativity: http://cannoneyed.com/projects/isometric-nyc
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