Show HN: Kaytu – Optimizing cloud costs using actual usage data
https://github.com/kaytu-io/kaytu
Reduce your cloud costs - SREs/DevOps/Cloud Engineers
Hi community!
We are Kaytu (“Kay-two,” named after the K2 mountain), and we've developed an open-source tool for engineering, DevOps, and SRE teams to reduce cloud costs.
Cloud inflation (“cloud-flation”) is real—AWS EC2 costs are up 23% (4-5x global inflation average [1]), and 30% of the capacity that is paid for is simply wasted ([2]).
The best way to improve cloud utilization is by simplifying the process so engineers can spot inefficiencies and suggest changes. We built a simple open-source CLI tool that recommends a cost-optimal workload based on actual usage data from observability tools. Check it out at https://github.com/kaytu-io/kaytu
Currently, we support AWS EC2 On-Demand Servers & EBS Storage using observability data from CloudWatch to determine utilization. You can optimize EC2 Servers based on CPU, Network, Memory, and Storage. We're expanding support to include OS License, GPU metrics, RDS, and Prometheus integration, and we plan to add more AWS services like EKS and OpenSearch, as well as Azure.
This is more than just a utility—we want to provide a no-nonsense platform that makes it ridiculously easy for engineers to build cost-effective apps on the cloud by optimizing workload configurations and customizing to scenarios.
Open Core: Inspired by Sid Sijbrandij and GitLab, we've open-sourced our CLI and are actively working on the server side. Our tooling will always remain straightforward and support open-source tools for free.
We made it as simple as possible to try out - it’s one command, no sign-up needed, no SaaS platform to share your credentials.
We would love you to try it out and give us your feedback! If there are bugs, we would greatly appreciate it if you reported them on GitHub.
Cheers, The Kaytu Team (Anil, Arta, Mahan, and Saleh)
References:
[1]Tangoe IT Trends Savings Recommendations and Liftr Insights data Cloud Pricing [2] Flexera State of Cloud Report - Multiple reports spanning 2017-2023
Automated Summary
Kaytu is an open-source tool designed to help engineering, DevOps, and SRE teams reduce cloud costs. It provides recommendations for optimal workload configurations based on actual usage data, analyzed from the previous seven days of CloudWatch monitoring. Kaytu supports customization for region, CPU, memory, network performance, storage, licenses, and more. It has a secure, open-core philosophy with no credential sharing required. The CLI is currently open-sourced, with server-side open-sourcing planned for the future. Upcoming features include non-interactive mode, Azure support, GPU optimization, credit utilization for burst instances, and observability data from Prometheus. To get started, users can install the Kaytu CLI, log in to their existing AWS CLI profile, and run the Kaytu CLI command.
What is the server component? Why is there a server component? What data does this send to the server?
Hi deadbunny,
I'm Saleh, co-author of the CLI tool. the reason we have the server component is that there are over +1M possible combinations for instance types which we recommend from. we're trying to find a efficient way to release this.
[flagged]
It’s a valid question. Trusting your business resources to a tool is not a decision you make lightly.
I appreciate the skepticism, however :)
We will release the open source server-side - promise :)
With three developers and the lookup involving 1M+ possible entries, we are trying to find an effective method.
No one's paid me, seems like a neat tool. I just prefer to know what data is being sent to servers I don't control.
Hi, Deadbunny. The server component is being open-sourced, and we will release it in 3 weeks.
https://github.com/kaytu-io/kaytu/blob/main/pkg/api/wastage/... has the data (it's just sizing info).
It's the sizing metadata that is being sent.
It would be nice to support a completely offline option where we can provide this metadata to disconnected environments. Perhaps by cloning a repo of metadata or otherwise.
How do you compare against Vantage, Dashdive, Infracost, Usage, etc.?
This looks interesting. Any plan to have Azure support?
Cool, Any chance on GCP integration?
hi dddw, we would love to. We are looking for someone who has $100K+ spend monthly on VMs and BigQuery on GCP. If you have or know someone, we can bang this out quickly.
GCPs partner team is mostly useless but they should at least be able to do that for you
Not in that ballpark, but I can ask around.
Hi dddw, sure. Thank you.
It helps with work prioritization.
anilc [at] kaytu.io is my email. If you can shoot me a note with some details on the workload (number of VMs, monthly spend), I'd be happy to add it to the backlog.
This looks really cool, definitely going to check it out. I'm very familiar with infracost and this seems to fill out that general idea of a cost analysis tool even more.
Great work thanks for posting
Always looking to conserve cloud spend, I'll give this a shot.
Heads up- there's an error on your landing page's Calendly link. "This Calendly URL is not valid."