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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Sandboxed containers and virtual private cloud (VPC) configurations facilitate network isolation, thereby safeguarding application runtimes. SAE offers robust solutions geared towards high availability for large-scale events, which necessitate exact capacity management, extensive scalability, along with service throttling and degradation. Fully-managed Infrastructure as a Service (IaaS) utilizing Kubernetes clusters presents cost-effective options for businesses. SAE is capable of scaling in mere seconds while enhancing the efficiency of runtimes and expediting Java application initialization. The One-Stop Platform as a Service (PaaS) encompasses seamlessly integrated basic services, microservices, and DevOps tools. SAE also supports comprehensive lifecycle management for applications, allowing the implementation of various release strategies, including phased and canary releases. Furthermore, it accommodates a traffic-ratio-based canary release model, ensuring that the entire release process is fully observable and can be easily reverted if necessary. This comprehensive approach not only streamlines deployment but also enhances overall operational resilience.

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

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud
Bloomberg
Docker
Gojek
IBM Cloud
Kubeflow
Kubernetes
NAVER
NVIDIA DRIVE
ZenML
Zillow
vLLM

Integrations

Alibaba Cloud
Bloomberg
Docker
Gojek
IBM Cloud
Kubeflow
Kubernetes
NAVER
NVIDIA DRIVE
ZenML
Zillow
vLLM

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

Alibaba Cloud

Founded

2008

Country

China

Website

www.alibabacloud.com/product/severless-application-engine

Vendor Details

Company Name

KServe

Website

kserve.github.io/website/latest/

Product Features

Serverless

API Proxy
Application Integration
Data Stores
Developer Tooling
Orchestration
Reporting / Analytics
Serverless Computing
Storage

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

Calisti Reviews

Calisti

Cisco

Alternatives