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AI-Defined Infrastructure: AiDI | @CloudExpo @ReneBuest #AI #ML #SDI #AiDI
Because it’s not just about software anymore
By: Rene Buest
Mar. 5, 2017 05:15 PM
Software-defined infrastructure (SDI) is one of the most popular and ongoing trends within data centers and cloud environments leading to better infrastructure flexibility by developing the infrastructure based on scripts respectively source code. However, SDIs are becoming more and more just a means to an end since automation, sophisticated algorithms and thus intelligent systems are leading to an Artificial Intelligence defined Infrastructure (AI-defined Infrastructure - AiDI).
SDI is not dead but only a means to an end
Typical SDI environments, e.g., cloud infrastructure, are built by developing scripts or source code. The software includes all the necessary commands to configure an entire infrastructure environment, including the applications and services running on top. An SDI-based infrastructure works independent from a certain hardware environment. Thus, a complete infrastructure can be exchanged by software - regardless of the underlying hardware components. One reason why SDIs are the fundamental foundation of today's cloud infrastructure environments.
However, an SDI is everything but intelligent. It is based on static source code including hard coded commands for taking certain actions automatically.
Understanding the AI-Defined Infrastructure (AiDI)
An Artificial Intelligence defined Infrastructure (AI-defined Infrastructure - AiDI) enhances a SDI with the necessary sophisticated algorithms, machine learning and artificial intelligence - fueling the SDI with intelligence. An AiDI allows a SDI to build and run self-learning respectively self-healing infrastructure environments. Thus, without human interaction AI-defined IT infrastructure environments are capable of:
An AI-defined Infrastructure cannot be compared with classic automation software, which typically works with predefined scripts. An AI-defined Infrastructure utilizes a company's existing knowledge executing it automatically and independently. However, like every new born organism an AI-defined Infrastructure needs to be trained but afterwards can work autonomously. Thus, based on the learned knowledge, disturbances can be solved - even proactively for not expected events by connecting appropriate incidents from the past. Therefore, an AI-defined Infrastructure monitors and analyzes all responding components in real-time to identify and solve a problem based on its existing knowledge. The more incidents are solved the bigger the infrastructure knowledge gets. The core of an AI-defined Infrastructure is a knowledge-based architecture that can analyze incidents and changes and autonomously develop strategies to solve an issue.
Furthermore, an AI-defined Infrastructure embraces communities to:
All in all, an AI-defined Infrastructure is an intelligent system that - initially fueled with external knowledge - can learn and make decisions autonomously without human interaction.
The AiDI is only a single piece of the entire AI-defined enterprise stack
This autonomous way of planning, building, running and maintaining the entire infrastructure let IT operations and developers deploy IT resources like server, storage, network, databases and other ready services in the most efficient way - by using the knowledge of more than just one expert but the entire IT operations team. Furthermore, IT operations are being transformed from pure consumers of resources to orchestrators respectively managers of a completely automated and intelligent IT stack. The very foundation of an end-to-end AI-ready enterprise.
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