Karpenter

Karpenter

Amazon
+
+

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About

Karpenter simplifies Kubernetes infrastructure with the right nodes at the right time. Karpenter is an open source, high-performance Kubernetes cluster autoscaler that simplifies infrastructure management by automatically launching the appropriate compute resources to handle your cluster's applications. Designed to leverage the full potential of the cloud, Karpenter enables fast and straightforward compute provisioning for Kubernetes clusters. It enhances application availability by swiftly responding to changes in application load, scheduling, and resource requirements, efficiently placing new workloads onto a variety of available computing resources. By identifying opportunities to remove under-utilized nodes, replace costly nodes with more economical alternatives, and consolidate workloads onto more efficient compute resources, Karpenter effectively reduces cluster compute costs.

About

dstack is an orchestration layer designed for modern ML teams, providing a unified control plane for development, training, and inference on GPUs across cloud, Kubernetes, or on-prem environments. By simplifying cluster management and workload scheduling, it eliminates the complexity of Helm charts and Kubernetes operators. The platform supports both cloud-native and on-prem clusters, with quick connections via Kubernetes or SSH fleets. Developers can spin up containerized environments that link directly to their IDEs, streamlining the machine learning workflow from prototyping to deployment. dstack also enables seamless scaling from single-node experiments to distributed training while optimizing GPU usage and costs. With secure, auto-scaling endpoints compatible with OpenAI standards, it empowers teams to deploy models quickly and reliably.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

DevOps engineers in search of a tool to manage their dynamic workloads and optimize their resources

Audience

Machine learning teams and enterprises seeking a unified, cost-efficient orchestration layer to manage GPU-based development, training, and inference across cloud, Kubernetes, and on-prem environments

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
karpenter.sh/

Company Information

dstack
Founded: 2022
Germany
dstack.ai/

Alternatives

Spot Ocean

Spot Ocean

Spot by NetApp

Alternatives

AWS Fargate

AWS Fargate

Amazon
MicroK8s

MicroK8s

Canonical
k0rdent

k0rdent

Mirantis

Categories

Categories

Integrations

Amazon Web Services (AWS)
Google Cloud Platform
Kubernetes
Microsoft Azure
Python
Sedai
StormForge

Integrations

Amazon Web Services (AWS)
Google Cloud Platform
Kubernetes
Microsoft Azure
Python
Sedai
StormForge
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