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Description
AWS Auto Scaling continuously observes your applications and automatically modifies capacity to ensure consistent and reliable performance while minimizing costs. This service simplifies the process of configuring application scaling for various resources across multiple services in just a few minutes. It features an intuitive and robust user interface that enables the creation of scaling plans for a range of resources, including Amazon EC2 instances, Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, as well as Amazon Aurora Replicas. By providing actionable recommendations, AWS Auto Scaling helps you enhance performance, reduce expenses, or strike a balance between the two. If you are utilizing Amazon EC2 Auto Scaling for dynamic scaling of your EC2 instances, you can now seamlessly integrate it with AWS Auto Scaling to extend your scaling capabilities to additional AWS services. This ensures that your applications are consistently equipped with the appropriate resources precisely when they are needed, leading to improved overall efficiency. Ultimately, AWS Auto Scaling empowers businesses to optimize their resource management in a highly efficient manner.
Description
Amazon EC2 Inf1 instances are specifically designed to provide efficient, high-performance machine learning inference at a competitive cost. They offer an impressive throughput that is up to 2.3 times greater and a cost that is up to 70% lower per inference compared to other EC2 offerings. Equipped with up to 16 AWS Inferentia chips—custom ML inference accelerators developed by AWS—these instances also incorporate 2nd generation Intel Xeon Scalable processors and boast networking bandwidth of up to 100 Gbps, making them suitable for large-scale machine learning applications. Inf1 instances are particularly well-suited for a variety of applications, including search engines, recommendation systems, computer vision, speech recognition, natural language processing, personalization, and fraud detection. Developers have the advantage of deploying their ML models on Inf1 instances through the AWS Neuron SDK, which is compatible with widely-used ML frameworks such as TensorFlow, PyTorch, and Apache MXNet, enabling a smooth transition with minimal adjustments to existing code. This makes Inf1 instances not only powerful but also user-friendly for developers looking to optimize their machine learning workloads. The combination of advanced hardware and software support makes them a compelling choice for enterprises aiming to enhance their AI capabilities.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon EC2
Yes
Amazon Elastic Container Service (Amazon ECS)
Yes
Amazon Web Services (AWS)
Yes
AWS Deep Learning AMIs
No
AWS Inferentia
No
AWS Nitro System
No
AWS Trainium
No
Amazon CloudWatch
Yes
Amazon EC2 P4 Instances
No
Amazon EC2 Trn1 Instances
No
Integrations
Amazon EC2
Yes
Amazon Elastic Container Service (Amazon ECS)
Yes
Amazon Web Services (AWS)
Yes
AWS Deep Learning AMIs
Yes
AWS Inferentia
Yes
AWS Nitro System
Yes
AWS Trainium
Yes
Amazon CloudWatch
No
Amazon EC2 P4 Instances
Yes
Amazon EC2 Trn1 Instances
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Pricing Details
$0.228 per hour
Free Trial
No
Free Version
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
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
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
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
Yes
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/autoscaling/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/ec2/instance-types/inf1/
Product Features
Server Management
CPU Monitoring
No
Credential Management
No
Database Servers
No
Email Monitoring
No
Event Logs
No
History Tracking
No
Patch Management
No
Scheduling
No
User Activity Monitoring
No
Virtual Machine Monitoring
No
Server Virtualization
Audit Management
No
Health Monitoring
No
Live Machine Migration
No
Multi-OS Virtual Machines
No
Patching / Backup
No
Performance Log
No
Performance Optimization
No
Rapid Provisioning
No
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
