Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AppScaler CMS is designed to simplify the management, monitoring, and reporting of increasingly intricate distributed networks, enabling users to oversee multiple AppScaler devices from a single management server. This solution equips organizations, distributed enterprises, and service providers with an effective and user-friendly platform for the centralized administration and rapid deployment of AppScaler devices, while also offering real-time monitoring and detailed application performance analytics. With AppScaler CMS, users can ensure governance and adherence to policies through centrally managed configurations, which allow for easy importation of settings from AppScaler devices with just a single click. Additionally, it offers comprehensive policy management for load balancing across all AppScaler devices, along with robust options for configuration backup and restoration. The system also supports firmware upgrades, ensuring devices are consistently updated, and includes role-based access control, allowing for granular permission settings tailored to user requirements. This comprehensive approach makes AppScaler CMS an essential tool for organizations looking to optimize their network management capabilities.
Description
Transform your Kubernetes autoscaling from a reactive approach to a proactive one with PredictKube, enabling you to initiate autoscaling processes ahead of anticipated load increases through our advanced AI predictions. By leveraging data over a two-week period, our AI model generates accurate forecasts that facilitate timely autoscaling decisions. The innovative predictive KEDA scaler, known as PredictKube, streamlines the autoscaling process, reducing the need for tedious manual configurations and enhancing overall performance. Crafted using cutting-edge Kubernetes and AI technologies, our KEDA scaler allows you to input data for more than a week and achieve proactive autoscaling with a forward-looking capacity of up to six hours based on AI-derived insights. The optimal scaling moments are identified by our trained AI, which meticulously examines your historical data and can incorporate various custom and public business metrics that influence traffic fluctuations. Furthermore, we offer free API access, ensuring that all users can utilize essential features for effective autoscaling. This combination of predictive capabilities and ease of use is designed to empower your Kubernetes management and enhance system efficiency.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
No
Google Cloud Platform
No
Kubeflow
No
Kubernetes
No
Kuna Exchange
No
Microsoft Azure
No
Prometheus
No
TensorFlow
No
Velas
No
Integrations
Amazon Web Services (AWS)
Yes
Google Cloud Platform
Yes
Kubeflow
Yes
Kubernetes
Yes
Kuna Exchange
Yes
Microsoft Azure
Yes
Prometheus
Yes
TensorFlow
Yes
Velas
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
XPoint Network
Founded
2017
Country
Hong Kong
Website
www.xpointnetwork.com
Vendor Details
Company Name
PredictKube
Country
United States
Website
predictkube.com
Product Features
Load Balancing
Authentication
Yes
Automatic Configuration
Yes
Content Caching
Yes
Content Routing
Yes
Data Compression
Yes
Health Monitoring
Yes
Predefined Protocols
Yes
Redundancy Checking
Yes
Reverse Proxy
Yes
SSL Offload
Yes
Schedulers
Yes