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ADOPTERS.md

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Who is using Karpenter?

Karpenter has a variety of users and use cases for scaling Kubernetes. Many customers want to learn from others who have already implemented Karpenter in their environments.

The following is a self-reported list of users to help identify adoption and points of contact.

Community

If you would like to ask question from the community please join the Karpenter slack channel in the Kubernetes Slack or join the Karpenter working group bi-weekly calls.

Add yourself

If you are using Karpenter please consider adding yourself as a user by opening a pull request to this file. If you are open to others contacting you about your use of Karpenter on Slack, add your Slack name as well.

Adopters (Alphabetical)

Organization Description Contacts Link
Amazon, Inc. Scaling production workloads and batch jobs in all AWS regions @Alex Kestner, @Ellis Tarn Introducing Karpenter
Airtel Digital Ltd. Karpenter for all kind of spiky and base workload and to increase spot coverage. @Sagar Arora Homepage
Anthropic Better utilizing mixes of instance types for more reliable capacity N/A Homepage
Beeswax Using Karpenter to scale our high load AdTech platform efficiently @James Wojewoda Homepage
Codefresh Juggling workloads for the SAAS CD/GitOps offering @Vadim Gusev Codefresh
Cordial Using Karpenter to scale multiple EKS clusters quickly @dschaaff Cordial
H2O.ai Dynamically scaling CPU and GPU nodes for AI workloads @Ophir Zahavi, @Asaf Oren H2O.ai
idealo Scaling multi-arch IPv6 clusters hosting web and event-driven applications @Heiko Rothe Homepage
Nirvana Money Building healthy, happy financial lives - Using Karpenter to manage all-Spot clusters @DWSR Homepage
Omaze Intelligently using Karpenter's autoscaling to power our platforms @devopsidiot Homepage
Sendcloud Using Karpenter to scale our k8s clusters for Europe’s #1 shipping automation platform N/A Homepage
Stytch Powering the scaling needs of Stytch's authentication and user-management APIs @Elijah Chanakira, @Ovadia Harary Homepage
Tyk Cloud Scaling workloads for the Cloud Free plan @Artem Hluvchynskyi, @gowtham Tyk Cloud