Amazon Deep Learning AMIs vs. AWS CloudFormation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Deep Learning AMIs
Score 8.7 out of 10
N/A
AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep learning frameworks and interfaces such as TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new…N/A
AWS CloudFormation
Score 8.7 out of 10
N/A
AWS CloudFormation gives developers and systems administrators a way to create and manage a collection of related AWS resources, provisioning and updating them in a predictable fashion. Use AWS CloudFormation’s sample templates or create templates to describe the AWS resources, and any associated dependencies or runtime parameters, required to run an application. Users don’t need to figure out the order for provisioning AWS services or the subtleties of making those dependencies work.…
$0
Pricing
Amazon Deep Learning AMIsAWS CloudFormation
Editions & Modules
No answers on this topic
Free Tier - 1,000 Handler Operations per Month per Account
$0.00
Handler Operation
$0.0009
per handler operation
Offerings
Pricing Offerings
Amazon Deep Learning AMIsAWS CloudFormation
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsThere is no additional charge for using AWS CloudFormation with resource providers in the following namespaces: AWS::*, Alexa::*, and Custom::*. In this case you pay for AWS resources (such as Amazon EC2 instances, Elastic Load Balancing load balancers, etc.) created using AWS CloudFormation as if you created them manually. You only pay for what you use, as you use it; there are no minimum fees and no required upfront commitments. When you use resource providers with AWS CloudFormation outside the namespaces mentioned above, you incur charges per handler operation. Handler operations are create, update, delete, read, or list actions on a resource.
More Pricing Information
Community Pulse
Amazon Deep Learning AMIsAWS CloudFormation
Top Pros
Top Cons
Best Alternatives
Amazon Deep Learning AMIsAWS CloudFormation
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
HashiCorp Terraform
HashiCorp Terraform
Score 8.6 out of 10
Medium-sized Companies
Posit
Posit
Score 9.1 out of 10
Ansible
Ansible
Score 9.0 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Ansible
Ansible
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon Deep Learning AMIsAWS CloudFormation
Likelihood to Recommend
10.0
(2 ratings)
7.6
(5 ratings)
User Testimonials
Amazon Deep Learning AMIsAWS CloudFormation
Likelihood to Recommend
Amazon AWS
Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.
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Amazon AWS
AWS CloudFormation is well suited for scenarios where all of your resources need to be provisioned on AWS but it is not suited for hybrid cloud deployments. It's very easy for someone new to learn. The level of customization offered as part of the template specifically for AWS services is great. There is also a UI tool where we can drag and drop the services we want and it generates an yaml file which is very easy to use. The visibility of stacks and its resources and one place where we can track and identify the issues in deployment is great.
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Pros
Amazon AWS
  • Setting up environment
  • Support for different types of machines
  • Perfect for Machine Learning / Deep Learning use cases
  • Nvidia / Cuda / Conda support easily
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Amazon AWS
  • SaaS
  • Paas
  • Iaas
  • On promises
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Cons
Amazon AWS
  • Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
  • It can be a bit confusing to switch between frameworks for novice users
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Amazon AWS
  • Error Description upon Failure Needs to be Improved.
  • Slow to create, delete or update.
  • Need to delete resources manually. It can ask before starting deletion whether to skip those resources or delete them.
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Alternatives Considered
Amazon AWS
Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.
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Amazon AWS
We didn't look into anything else as Cloudformation was "built-in" for AWS, it just kind of made sense to go with that. Terraform was something that we briefly looked into Terraform but decides to stick with Cloudformation because our task was relatively "simple". Apparently if it's a bit more complex, Terraform might be the way to go.
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Return on Investment
Amazon AWS
  • Saves a lot of Infra Costs
  • Saves a lot of time in handling environment issues
  • Easy to start a new instance
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Amazon AWS
  • It has a positive ROI
  • Less time inverted in bugs
  • More stable source code
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ScreenShots

AWS CloudFormation Screenshots

Screenshot of CloudFormation - How it works overviewScreenshot of CloudFormation - High level how it worksScreenshot of CloudFormation - Template exampleScreenshot of CloudFormation - Template inputs overview