AWS Elastic Beanstalk vs Datatron
Overview
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Detailed Comparison
Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring. | Automate the standardized deployment, monitoring, governance, and validation of all your models to be developed in any environment. |
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;Impossible to outgrow – Elastic Beanstalk automatically scales your application up and down based on default Auto Scaling settings;Complete control – Elastic Beanstalk lets you "open the hood" and retain full control over the AWS resources powering your application;Flexible – You have the freedom to select the Amazon EC2 instance type that is optimal for your application based on CPU and memory requirements, and can choose from several available database options;Reliable – Elastic Beanstalk runs within Amazon's proven network infrastructure and datacenters, and provides an environment where developers can run applications requiring high durability and availability. | Explore models built and uploaded by your Data Science team, all from one centralized repository; Create and scale model deployments in just a few clicks. Deploy models developed in any framework or language; Make better business decisions to save your team time and money. Monitor model performance and detect model decay as it happens; Spend less time on model validation, bias detection, and internal audit processes. Go from model development to internal auditing to production faster than ever; Manage multivariate models through A/B testing for live inference and batch tasks; Apply business logic to your model prediction results. Create workflows for your models using multiple sources and languages |
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What are some alternatives to AWS Elastic Beanstalk, Datatron?
Heroku
Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling.
Clever Cloud
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Google App Engine
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Red Hat OpenShift
OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
Render
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Hasura
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TensorFlow
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Cloud 66
Cloud 66 gives you everything you need to build, deploy and maintain your applications on any cloud, without the headache of dealing with "server stuff". Frameworks: Ruby on Rails, Node.js, Jamstack, Laravel, GoLang, and more.
Jelastic
Jelastic is a Multi-Cloud DevOps PaaS for ISVs, telcos, service providers and enterprises needing to speed up development, reduce cost of IT infrastructure, improve uptime and security.
Dokku
It is an extensible, open source Platform as a Service that runs on a single server of your choice. It helps you build and manage the lifecycle of applications from building to scaling.
