Need advice about which tool to choose?Ask the StackShare community!
Add tool
AWS Elastic Beanstalk vs Google AI Platform: What are the differences?
AWS Elastic Beanstalk: Quickly deploy and manage applications in the AWS cloud. Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring; Google AI Platform: Create your AI applications once, then run them easily on both GCP and on-premises. Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.
AWS Elastic Beanstalk can be classified as a tool in the "Platform as a Service" category, while Google AI Platform is grouped under "Machine Learning as a Service".
Some of the features offered by AWS Elastic Beanstalk are:
- Elastic Beanstalk is built using familiar software stacks such as the Apache HTTP Server for Node.js, PHP and Python, Passenger for Ruby, IIS 7.5 for .NET, and Apache Tomcat for Java
- There is no additional charge for Elastic Beanstalk - you pay only for the AWS resources needed to store and run your applications.
- Easy to begin – Elastic Beanstalk is a quick and simple way to deploy your application to AWS. You simply use the AWS Management Console, Git deployment, or an integrated development environment (IDE) such as Eclipse or Visual Studio to upload your application
On the other hand, Google AI Platform provides the following key features:
- “No lock-in” flexibility
- Supports Kubeflow
- Supports TensorFlow
Manage your open source components, licenses, and vulnerabilities
Learn MorePros of AWS Elastic Beanstalk
Pros of Google AI Platform
Pros of AWS Elastic Beanstalk
- Integrates with other aws services77
- Simple deployment65
- Fast44
- Painless28
- Free16
- Well-documented4
- Independend app container3
- Postgres hosting2
- Ability to be customized2
Pros of Google AI Platform
Be the first to leave a pro
Sign up to add or upvote prosMake informed product decisions
Cons of AWS Elastic Beanstalk
Cons of Google AI Platform
Cons of AWS Elastic Beanstalk
- Charges appear automatically after exceeding free quota2
- Lots of moving parts and config1
- Slow deployments0
Cons of Google AI Platform
Be the first to leave a con
Sign up to add or upvote consMake informed product decisions
What is AWS Elastic Beanstalk?
Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
What is Google AI Platform?
Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.
Need advice about which tool to choose?Ask the StackShare community!
Jobs that mention AWS Elastic Beanstalk and Google AI Platform as a desired skillset
What companies use AWS Elastic Beanstalk?
What companies use Google AI Platform?
What companies use AWS Elastic Beanstalk?
What companies use Google AI Platform?
Manage your open source components, licenses, and vulnerabilities
Learn MoreSign up to get full access to all the companiesMake informed product decisions
What tools integrate with AWS Elastic Beanstalk?
What tools integrate with Google AI Platform?
What tools integrate with AWS Elastic Beanstalk?
What tools integrate with Google AI Platform?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
+8 6
2778
+23 12
6643
What are some alternatives to AWS Elastic Beanstalk and Google AI Platform?
Google App Engine
Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
AWS CodeDeploy
AWS CodeDeploy is a service that automates code deployments to Amazon EC2 instances. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during deployment, and handles the complexity of updating your applications.
Docker
The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere
AWS CloudFormation
You can use AWS CloudFormation’s sample templates or create your own templates to describe the AWS resources, and any associated dependencies or runtime parameters, required to run your application. You don’t need to figure out the order in which AWS services need to be provisioned or the subtleties of how to make those dependencies work.
Azure App Service
Quickly build, deploy, and scale web apps created with popular frameworks .NET, .NET Core, Node.js, Java, PHP, Ruby, or Python, in containers or running on any operating system. Meet rigorous, enterprise-grade performance, security, and compliance requirements by using the fully managed platform for your operational and monitoring tasks.