Show HN: Kaytu – Optimizing cloud costs using actual usage data 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://ift.tt/xAtM8OC 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 https://ift.tt/xAtM8OC April 29, 2024 at 09:27PM
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