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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.

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.

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

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

Audience

Developers and professionals searching for a model inference platform on Kubernetes

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

No information available.
Free Version
Free Trial

Pricing

Free
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

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

Review this Software

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

Ambient Mesh
Founded: 2017
United States
ambientmesh.io

Company Information

KServe
kserve.github.io/website/latest/

Alternatives

Alternatives

Categories

Categories

Integrations

Kubernetes
Amazon EKS
Amazon EKS Anywhere
Azure Kubernetes Service (AKS)
Bloomberg
Docker
Envoy
Gojek
GraphQL
Istio
Microsoft Azure
NVIDIA DRIVE
Red Hat OpenShift
Solo Enterprise
Splunk APM
Zillow
agentgateway
kgateway

Integrations

Kubernetes
Amazon EKS
Amazon EKS Anywhere
Azure Kubernetes Service (AKS)
Bloomberg
Docker
Envoy
Gojek
GraphQL
Istio
Microsoft Azure
NVIDIA DRIVE
Red Hat OpenShift
Solo Enterprise
Splunk APM
Zillow
agentgateway
kgateway
Claim Ambient Mesh and update features and information
Claim Ambient Mesh and update features and information
Claim KServe and update features and information
Claim KServe and update features and information