What is Autonomic Computing and why it matters

What is Autonomic computing and why it matters

What is Autonomic Computing and why it matters

Nature has inspired most of the inventions that happened in the world. Inventors studied the flight of birds with a desire to fly like them up in the sky and now we have aeroplanes to fly. Similarly, the human body has an autonomic nervous system that regulates body processes by itself. They have the capability of self-healing. Why not apply these principles to our machines and applications? It is the same concept that we will be discussing in this blog, Autonomic Computing. It demonstrates and advocates networking computer systems that do not involve a lot of human intervention other than defining input rules.

Maintenance of computer applications adds to a major cost for most organizations. The need for cost savings and the need to remove the challenges of computer system complexity demands innovative solutions such as Autonomic Computing. IBM presented this concept back in 2001 when the IBM Research team presented a solution to the growing complexities in building and managing computer systems. The IBM solution was to build computer systems that could regulate themselves in a manner in which our nervous systems regulate and protect our bodies. Now, Autonomic Computing finds its place in Gartner Technology Trends 2022 and, Gartner predicts that by 2024, 20% of organizations that sell autonomic systems or devices will require customers to waive indemnity provisions related to their products’ learned behaviour.

Autonomic systems are self-managed systems in both physical and software form. They self-learn from their environments and dynamically modify their own algorithms in real-time to optimize their actions in various complex ecosystems. They optimize performance and defend against attacks without human intervention. While autonomic systems are mostly software-based, humanoid robots are also emerging. The basic features of an autonomic system put forth by IBM is mentioned in the illustration below.

Basic Features of an Autonomic System

5 Applications of Autonomic Systems

Let’s have a look at some of the early applications of this concept.

  1. Customer Relationship Management – The complexity that arises daily on execution of leads can be managed through a loop which is a self-optimizing component.
  2. Finance – An algorithm to manage and analyse any errors relating to budget allocation, allocation of resources, revenue generated, recurring expenses etc.
  3. Policy management – Autonomic computing helps manage pricing policies through various schemes looking at the market conditions, competition etc.
  4. Inventory management – Parameters such as stock, market information, and supplier information are checked continuously to adjust itself optimum.
  5. IT infrastructure management – Autonomic computing can also be used in server load balancing, process allocation, memory error correction, automatic upgrading of software and drivers, pre-failure notification, automated device backup and recovery, etc.


With the increase in the market for computer-based applications and systems, related issues are also growing and becoming more dynamic. This in itself will propel the need to democratize autonomic systems. With low/no-codes and autonomic computing, the time to market for applications will be quick and companies will be able to adapt to the changing needs of consumers fast.

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