Related Products
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About
Ambient Mesh is a next-generation, sidecar-less service mesh designed to simplify security, connectivity, and observability for cloud-native workloads. It enables teams to secure and connect applications without modifying application code or adding operational overhead. Ambient Mesh provides zero-trust, SPIFFE-based security with end-to-end workload encryption. Built-in observability tools deliver distributed tracing, logs, and real-time performance insights. The platform supports advanced traffic control features such as routing, failover, and blue-green deployments. Ambient Mesh allows organizations to migrate from traditional sidecar-based meshes with zero downtime. By reducing complexity and resource usage, it helps teams operate more efficiently at scale.
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About
Highly scalable and standards-based model inference platform on Kubernetes for trusted AI. KServe is a standard model inference platform on Kubernetes, built for highly scalable use cases. Provides performant, standardized inference protocol across ML frameworks. Support modern serverless inference workload with autoscaling including a scale to zero on GPU. Provides high scalability, density packing, and intelligent routing using ModelMesh. Simple and pluggable production serving for production ML serving including prediction, pre/post-processing, monitoring, and explainability. Advanced deployments with the canary rollout, experiments, ensembles, and transformers. ModelMesh is designed for high-scale, high-density, and frequently-changing model use cases. ModelMesh intelligently loads and unloads AI models to and from memory to strike an intelligent trade-off between responsiveness to users and computational footprint.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Ambient Mesh is designed for platform engineers, DevOps teams, and enterprises running Kubernetes-based microservices who want a simpler, more efficient alternative to traditional sidecar-based service meshes
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Audience
Developers and professionals searching for a model inference platform on Kubernetes
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAmbient Mesh
Founded: 2017
United States
ambientmesh.io
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Company InformationKServe
kserve.github.io/website/latest/
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Categories |
Categories |
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Integrations
Kubernetes
Amazon EKS
Amazon EKS Anywhere
Azure Kubernetes Service (AKS)
Bloomberg
Docker
Envoy
Gojek
GraphQL
Istio
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Integrations
Kubernetes
Amazon EKS
Amazon EKS Anywhere
Azure Kubernetes Service (AKS)
Bloomberg
Docker
Envoy
Gojek
GraphQL
Istio
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