Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The NGINX Service Mesh, which is always available for free, transitions effortlessly from open source projects to a robust, secure, and scalable enterprise-grade solution. With NGINX Service Mesh, you can effectively manage your Kubernetes environment, utilizing a cohesive data plane for both ingress and egress, all through a singular configuration. The standout feature of the NGINX Service Mesh is its fully integrated, high-performance data plane, designed to harness the capabilities of NGINX Plus in managing highly available and scalable containerized ecosystems. This data plane delivers unmatched enterprise-level traffic management, performance, and scalability, outshining other sidecar solutions in the market. It incorporates essential features such as seamless load balancing, reverse proxying, traffic routing, identity management, and encryption, which are crucial for deploying production-grade service meshes. Additionally, when used in conjunction with the NGINX Plus-based version of the NGINX Ingress Controller, it creates a unified data plane that simplifies management through a single configuration, enhancing both efficiency and control. Ultimately, this combination empowers organizations to achieve higher performance and reliability in their service mesh deployments.
Description
KServe is a robust model inference platform on Kubernetes that emphasizes high scalability and adherence to standards, making it ideal for trusted AI applications. This platform is tailored for scenarios requiring significant scalability and delivers a consistent and efficient inference protocol compatible with various machine learning frameworks. It supports contemporary serverless inference workloads, equipped with autoscaling features that can even scale to zero when utilizing GPU resources. Through the innovative ModelMesh architecture, KServe ensures exceptional scalability, optimized density packing, and smart routing capabilities. Moreover, it offers straightforward and modular deployment options for machine learning in production, encompassing prediction, pre/post-processing, monitoring, and explainability. Advanced deployment strategies, including canary rollouts, experimentation, ensembles, and transformers, can also be implemented. ModelMesh plays a crucial role by dynamically managing the loading and unloading of AI models in memory, achieving a balance between user responsiveness and the computational demands placed on resources. This flexibility allows organizations to adapt their ML serving strategies to meet changing needs efficiently.
API Access
Has API
API Access
Has API
Integrations
Kubernetes
Amazon EKS
Azure Kubernetes Service (AKS)
Diamanti
Gojek
Google Kubernetes Engine (GKE)
Grafana
IBM Cloud
IBM Cloud Private
Kubeflow
Integrations
Kubernetes
Amazon EKS
Azure Kubernetes Service (AKS)
Diamanti
Gojek
Google Kubernetes Engine (GKE)
Grafana
IBM Cloud
IBM Cloud Private
Kubeflow
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
F5
Founded
1996
Country
United States
Website
www.f5.com/products/nginx/nginx-gateway-fabric
Vendor Details
Company Name
KServe
Website
kserve.github.io/website/latest/
Product Features
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization