PyTorch on AWS vs. Red Hat JBoss Enterprise Application Platform

JBoss EAP is subscription based/open source platform. It's very reliable and great for deploying high transaction Java based enterprise applications. It integrates well with third party components like mod_cluster and supports popular Java EE web-based frameworks such as Spring, Angular JS, jQuery Mobile, and Google Web Toolkit.

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• MOD_CLUSTER integration. JBoss EAP integrates pretty well with mod_cluster. This is an intelligent load balancer especially useful in highly clustered environments.
• Supports enterprise-grade features such as high availability clustering, distributed caching, messaging etc.
• Supports deployment in on-premise, virtual and hybrid cloud environments.

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• Difficult to replicate configuration outside of a container environment
• Still requires quite a bit of knowledge of the CLI
• Integration with deployment tools requires CLI knowledge

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We are planning to migrate away from Jboss to Tomcat as Jboss has shown not interest in supporting OSGi which is heavily used at our shop

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JBoss overall is easy to use. The installation and deployment of applications are quick. Documentations and support are also readily available.

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JBoss EAP is lightweight and doesn't really consumes much physical resources. It's high performing and suites well for high transaction Java enterprise applications. The out of box performance settings are not really great and you will have to configure the settings to suite your environment to leverage it's full benefits.

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Fast response.

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We selected JBoss because of compatibility with EJB's. We currently are trying to reduce our footprint and will highly consider using Tomcat.

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• Jboss EAP is easy to deploy and configure. This lead to lower cost and faster delivery.
• Even though we have large number of machines running JBoss, we have only two Jboss Administrators. It doesn't requires too much administration and maintenance on daily basis and reduces number of administrators required for large implementations.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info