Autonomic Computing: is a self-managing computing model named after, and patterned on, the human body’s autonomic nervous system. An autonomic computing system would control the functioning of a system including the underlying infrastructure and application sets with minimal manual input from the user, in the same way that the autonomic nervous system regulates human body systems without conscious input from the individual. The goal of autonomic computing is to create autonomous systems that run by themselves, capable of high-level functioning while keeping the system’s complexity invisible to the user.
Our innovative and turnkey solution architecture, the Autonomic Computing Platform (ACP) enables rapid buildup, teardown, deployment and operation of scalable and self-healing infrastructure, containerized applications and solutions across the multi and hybrid clouds; – in a repeatable and turnkey manner using Cloud, Al, and Automation. The platform leverages a plug-n-play architecture, Infrastructure and Security as Code, Kubernetes, Agentic AI and Generative AI (powered by Google Gemini and Agent Development Kit), and AIOps technologies for high availability, full-stack observability and resiliency across distributed and hybrid cloud architectures.
The infrastructure and applications deployed using the ACP are Interoperable, Autonomic and Distributed Intelligent Systems that continuously learn, evolve, and optimize for increased efficiency through situational awareness and contextual adaptation. The ACP includes the MAPE-K Reference Model – Monitor, Analyze, Plan, Execute, and Knowledge, an Agentic AI control-loop that enables the ACP Agents to act autonomously by using a combination of Large Language Models, toolsets and orchestration that transforms cloud infrastructure, applications and solutions into self-manageable Autonomic Systems.
Autonomic computing is one of the building blocks of pervasive computing, an anticipated future computing model in which tiny – even invisible – computers will be all around us, communicating through increasingly interconnected networks. Our frameworks and platforms enable Autonomic Computing through features like Self-Configure, Self-Heal, Self-Optimize and Self-Protect the system.
The benefits include reduction in operations and maintenance costs, Total Cost of Ownership and improvement in the overall security posture and operational resilience of systems. The system will
- Know itself in terms of what resources it has access to, what its capabilities and limitations are and how and why it is connected to other systems
- Be able to automatically configure and reconfigure itself depending on the changing computing environment
- Be able to optimize its performance to ensure the most efficient computing process
- Be able to work around encountered problems by either repairing itself or routing functions away from the trouble
- Detect, identify and protect itself against various types of attacks to maintain overall system security and integrity
- Adapt to its environment as it changes, interacting with neighboring systems and establishing communication protocols
- Rely on open standards and anticipate the demand on its resources while staying transparent to users
Every autonomic system should be able to exhibit a minimum set of properties to achieve its purpose:
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Automatic: This essentially means being able to self-control its internal functions and operations. As such, an autonomic system must be self-contained and able to start-up and operate without any manual intervention or external help. Again, the knowledge required to bootstrap the system (Know-how) must be inherent to the system.
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Adaptive: An autonomic system must be able to change its operation (i.e., its configuration, state and functions). This will allow the system to cope with temporal and spatial changes in its operational context either long term (environment customization/optimization) or short term (exceptional conditions such as malicious attacks, faults, etc.).
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Aware: An autonomic system must be able to monitor (sense) its operational context as well as its internal state in order to be able to assess if its current operation serves its purpose. Awareness will control adaptation of its operational behavior in response to context or state changes.