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AWS Auto Scaling VS AWS Deep Learning AMIs

Compare AWS Auto Scaling VS AWS Deep Learning AMIs and see what are their differences

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NinjaOne (Formerly NinjaRMM) provides remote monitoring and management software that combines powerful functionality with a fast, modern UI. Easily remediate IT issues, automate common tasks, and support end-users with powerful IT management tools. featured
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AWS Auto Scaling logo AWS Auto Scaling

Learn how AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.

AWS Deep Learning AMIs logo AWS Deep Learning AMIs

The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at any scale.
  • AWS Auto Scaling Landing page
    Landing page //
    2023-02-26
  • AWS Deep Learning AMIs Landing page
    Landing page //
    2023-04-30

Category Popularity

0-100% (relative to AWS Auto Scaling and AWS Deep Learning AMIs)

AWS Auto Scaling

AWS Deep Learning AMIs

Development
54 54%
Development
46% 46
Diagnostics Software
53 53%
Diagnostics Software
47% 47
Domains
55 55%
Domains
45% 45
Monitoring Tools
59 59%
Monitoring Tools
41% 41

User comments

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Social recommendations and mentions

Based on our record, AWS Auto Scaling should be more popular than AWS Deep Learning AMIs. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AWS Auto Scaling mentions (11)

  • Building a Greener Cloud: The Role of an Architect for Sustainability in AWS
    AWS Auto-Scaling is a service that automatically adjusts the capacity of an application in response to changing demand. It monitors resource utilization and scales resources up or down as necessary. By using AWS Auto Scaling, businesses can ensure that their applications are always running at optimal performance levels, without wasting resources or energy. - Source: dev.to / about 1 year ago
  • AWS vs Digital Ocean cost comparison in 2022
    Auto scaling lets you scale in/out your servers based on various conditions. So, you could choose to have a minimum capacity as default and let AWS scale it up automatically when needed. You could also schedule the scaling events based on time (For ex: scale to 2x servers during peak times and back to normal during normal hours) There are also other benefits that come with AWS like better eco-system of tools and... - Source: dev.to / over 1 year ago
  • Hidden, absolutely broken, mechanics
    Guys, whats this? Sounds kinda OP if you ask me Https://aws.amazon.com/autoscaling/. Source: about 2 years ago
  • A first impression of AWS App Runner
    AWS Auto Scaling – Makes sure that the application scales based on the number of concurrent requests. - Source: dev.to / over 2 years ago
  • .NET Applications with Linux Containers
    Many customers start their cloud journey with a lift-and-shift approach, running their NTier .NET Framework applications on EC2 without any code changes. It’s common for these deployments to have more than one EC2 Windows instance with an Application Load Balancer (ALB), routing the user requests to one of the EC2 instances. A stateful application can have session affinity (sticky sessions) enabled at the ALB... - Source: dev.to / over 2 years ago
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AWS Deep Learning AMIs mentions (3)

  • Machine Learning Best Practices for Public Sector Organizations
    AWS Deep Learning AMIs can be used to accelerate deep learning by quickly launching Amazon EC2 instances. - Source: dev.to / over 2 years ago
  • Unable to host a Flask App consisting of an Image Classification Model coded in Pytorch to a free tier EC2 instance. The issue occurs at requirements installation i.e The torch v1.8.1 installation gets stuck at 94%.
    Ok a bit more on topic of your question. Set up a docker locally on your computer, pick a relevant image with all the python stuff and then do pip install -r requirements -t ./dependencies zip it up, upload to S3 and then get it from there and use on the EC2 instance. Or look into using Deep Learning AMIs they should have pytorch installed: https://aws.amazon.com/machine-learning/amis/. Source: almost 3 years ago
  • Is Sagemaker supposed to replace Keras or PyTorch? Or Tensorflow?
    Literally nothing stops you from running EC2 instance with GPU and configuring it yourself. There are even AMIs specialized for ML workloads with everything preconfigured and ready to use - https://aws.amazon.com/machine-learning/amis/. Source: almost 3 years ago

What are some alternatives?

When comparing AWS Auto Scaling and AWS Deep Learning AMIs, you can also consider the following products

IBM Cloud Bare Metal Servers - IBM Cloud Bare Metal Servers is a single-tenant server management service that provides dedicated servers with maximum performance.

Amazon Elastic Inference - Utilities, Application Utilities, and Machine Learning as a Service

Amazon Simple Workflow Service (SWF) - Amazon SWF helps developers build, run, and scale background jobs that have parallel or sequential steps.

Faronics Deep Freeze - Faronics Deep Freeze provides the ultimate workstation protection by preserving the desired computer configuration and settings.

Zing - The worry-freeinternational money app

MxToolBox - All of your MX record, DNS, blacklist and SMTP diagnostics in one integrated tool.

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