Autonomic network
Autonomic network
(also self-managing network, self-healing network)
Autonomic network definition
An autonomic network is a self-managing network that can configure, optimize, and troubleshoot itself with minimal to no human input. It is based on artificial intelligence (AI) and machine learning (ML) algorithms that use feedback loops to identify problems and change accordingly. The end goal is to reduce the need for manual network management. It mainly revolves around minimizing the complex management process in large-scale and diverse network environments, which can be resource-intensive and prone to human error. However, considering autonomic networks heavily rely on AI and ML, they can be more vulnerable to cyberattacks.
See also: cyberattack, artificial intelligence
Autonomic network advantages
- Less human intervention and,consequently, less human error, considering that these networks can perform all activities independently.
- Improve network reliability and efficiency.
- Allow for faster problem-solving because autonomic networks can detect and resolve issues fast.
- Reduce downtime and improve network availability.
- Save time and employee costs since there is no need for manual input.
- Can improve security because these networks can quickly signal any potential security threat.
Autonomic network disadvantages
- May be complex and require special knowledge and skills.
- Heavily rely on technology, so they are susceptible to cyberattacks and bugs.
- Have limited flexibility due to their automated nature, which can impede the implementation of custom solutions or responses to unplanned events.
- Autonomic networks can be costly, especially for small- and medium-sized organizations or those with limited resources, because they require a higher degree of maintenance.