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Automated Resource Deployment Based on Source Code Analysis

IP.com Disclosure Number: IPCOM000248178D
Publication Date: 2016-Nov-04
Document File: 2 page(s) / 34K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method to automatically deploy assets based on static/dynamic code analytics.

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This is the abbreviated version, containing approximately 52% of the total text.

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Automated Resource Deployment Based on Source Code Analysis

Modern applications are rarely self-contained, involving assets such as databases, application servers, load balancers etc.

Application deployment implies deployment of the dependencies and then deployment of core business logic that utilizes those dependencies. Dependencies such as databases, etc., can add substantial overhead to the application deployment process. Moreover, skills to deploy these dependencies may not be readily available or may be underutilized if the application is part of a rapid prototype or proof of concept.

Current solutions involve either manually deploying dependencies or deploying based on recipes. Each method needs manual intervention, which has several drawbacks including being error prone and overly conservative(which leads to bulky deployments), less secure, and needing domain deployment skills.

The novel solution is to automatically deploy assets based on static/dynamic code analytics.

Asset(e.g., databases, etc.) usage typically involves inclusion of drivers. For example, accessing databases from Java* typically involves the use of JDBC drivers. Class signatures for JDBC are very similar. In addition, 'SQL like' code can be recognized and the database in question can be traced through code analysis. General plugins generally involve inclusion of drivers for several data sources/outputs.

To alleviate the problem of deploying everything and limit to only the service/asset that is used, user input can be sought bef...