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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Navigating the complexities of leveraging cloud services can often be challenging for businesses. To simplify this process, we created BidElastic, a resource provisioning tool comprising two key elements: BidElastic BidServer, which reduces computational expenses, and BidElastic Intelligent Auto Scaler (IAS), which enhances the management and oversight of your cloud service provider. The BidServer employs simulation techniques and sophisticated optimization processes to forecast market changes and develop a strong infrastructure tailored to the spot instances of cloud providers. Adapting to fluctuating workloads requires dynamically scaling your cloud infrastructure, a task that is often more complicated than it seems. For instance, during a sudden surge in traffic, it could take up to 10 minutes to bring new servers online, resulting in lost customers who may choose not to return. Effectively scaling your resources hinges on accurately predicting computational workloads, and that's precisely what CloudPredict accomplishes; it harnesses machine learning to forecast these computational demands, ensuring your infrastructure can respond swiftly and efficiently. This capability not only helps retain customers but also optimizes resource allocation in real-time.

Description

You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks Data Intelligence Platform
Feast
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
LanceDB
PyTorch
Snowflake
TensorFlow
Union Cloud
io.net

Integrations

Amazon Web Services (AWS)
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks Data Intelligence Platform
Feast
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
LanceDB
PyTorch
Snowflake
TensorFlow
Union Cloud
io.net

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

BidElastic

Country

Poland

Website

bidelastic.com/products-and-services/

Vendor Details

Company Name

Anyscale

Founded

2019

Country

United States

Website

ray.io

Product Features

Cloud Cost Management

Cost Reduction Optimization
Dashboard
Data Import/Export
Data Storage
Data Visualization
Resource Usage Reporting
Roles / Permissions
Spend and Cost Reporting

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning

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

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