Automation of System Infrastructure Upgrade or Downgrade Using AI

Automation of System Infrastructure Upgrade or Downgrade Using AI

DOI: 10.4018/978-1-6684-6519-6.ch016
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Abstract

Building recommendation systems and automating their implementation for businesses is the key to a better business environment. It will be helpful to businesses to save on infrastructure costs, get better performance, and upgrade or downgrade systems automatically based on live processing data. The proposed solution is to calculate the upgrade or downgrade of CPU, RAM, disk type, network speed, etc., based on live data of usage automatically. Using cloud platforms or standalone systems and servers, the system infrastructure can be upgraded, downgraded, or customized based on application needs. Using the system alerts, one can get inputs on CPU, RAM, disk usage, network speed, etc. to run automation scripts using AI to achieve the proposed solution. It will be helpful to businesses to save on infrastructure costs, get better.
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Objectives And Key Issues

The use of automation in system infrastructure upgrades or downgrades has ability to result in huge innovations in cost savings on infrastructure, better infrastructure, and a better environment to reduce the risk of system downtime due to extra usage.

The most significant hurdle is calculating the growth or downgrade based on the latest changes to hardware. Example: The latest processor has extra threads to process more data. The hardware change information needs to be updated in the system on time, since we are not sure the system monitoring application loads accurate details to the database (Pise, Vadapalli, and Sanders, 2022). Also, newly added services and the improvement of existing services reflect hardware performance and need to be adjusted in the database configuration. When the first piece of hardware fails, the service level agreement (SLA) is broken, and there will be penalties imposed on the business every year.

Figure 1.

Automation of System Infrastructure Upgrade or Downgrade (Pise, 2021).

978-1-6684-6519-6.ch016.f01

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