Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Auto Scaling is a service designed to dynamically adjust computing resources in response to fluctuations in user demand. When there is an uptick in requests, it seamlessly adds ECS instances to accommodate the increased load, while conversely, it reduces the number of instances during quieter times to optimize resource allocation. This service not only adjusts resources automatically based on predefined scaling policies but also allows for manual intervention through scale-in and scale-out options, giving you the flexibility to manage resources as needed. During high-demand periods, it efficiently expands the available computing resources, ensuring optimal performance, and when demand wanes, Auto Scaling efficiently retracts ECS resources, helping to minimize operational costs. Additionally, this adaptability ensures that your system remains responsive and cost-effective throughout varying usage patterns.
Description
Amazon SageMaker Model Training streamlines the process of training and fine-tuning machine learning (ML) models at scale, significantly cutting down both time and costs while eliminating the need for infrastructure management. Users can leverage top-tier ML compute infrastructure, benefiting from SageMaker’s capability to seamlessly scale from a single GPU to thousands, adapting to demand as necessary. The pay-as-you-go model enables more effective management of training expenses, making it easier to keep costs in check. To accelerate the training of deep learning models, SageMaker’s distributed training libraries can divide extensive models and datasets across multiple AWS GPU instances, while also supporting third-party libraries like DeepSpeed, Horovod, or Megatron for added flexibility. Additionally, you can efficiently allocate system resources by choosing from a diverse range of GPUs and CPUs, including the powerful P4d.24xl instances, which are currently the fastest cloud training options available. With just one click, you can specify data locations and the desired SageMaker instances, simplifying the entire setup process for users. This user-friendly approach makes it accessible for both newcomers and experienced data scientists to maximize their ML training capabilities.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon SageMaker
No
Amazon Web Services (AWS)
No
BERT
No
CodeGPT
No
DALL·E 2
No
F5 Distributed Cloud DDoS Mitigation Service
Yes
Hugging Face
No
NVIDIA NeMo Megatron
No
PyTorch
No
TensorFlow
No
Integrations
Amazon SageMaker
Yes
Amazon Web Services (AWS)
Yes
BERT
Yes
CodeGPT
Yes
DALL·E 2
Yes
F5 Distributed Cloud DDoS Mitigation Service
No
Hugging Face
Yes
NVIDIA NeMo Megatron
Yes
PyTorch
Yes
TensorFlow
Yes
Pricing Details
This service is available free of charge. You will be only charged for the standard cost of adding additional ECS resources.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
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)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Alibaba Cloud
Founded
2009
Country
China
Website
www.alibabacloud.com/product/auto-scaling
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/train/
Product Features
Server Virtualization
Audit Management
Yes
Health Monitoring
Yes
Live Machine Migration
No
Multi-OS Virtual Machines
No
Patching / Backup
No
Performance Log
Yes
Performance Optimization
Yes
Rapid Provisioning
Yes
Security Management
No
Type 1 / Type 2 Hypervisor
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No