The Intelligent Data Center is Beyond Human Scale
As the IT industry has evolved over recent years, it has seen the clear and rapid movement towards software-defined infrastructure at every layer of the stack. Software-defined, API-accessible infrastructure also opened the door for the next phase of evolution with what Gartner has categorized as “AI Ops”, a further evolution beyond traditional silo-focused, human dependent, operations management.
To create a self-learning system that optimizes Data Center (DC) and cloud resources and predicts and mitigates system failures, I&O leaders should take a holistic approach by combining architectures with smart algorithms, according to a newly released research note from Gartner, “How To Build The Intelligent Data Center1”. I believe this research note explores the approach and vendor ecosystem (which includes Turbonomic) to enable an Intelligent Data Center. We can define an intelligent DC as one that encompasses algorithms, self-optimizing and self- organizing systems (including architecture and applications), operating together to produce an aggregated IQ greater than the sum of its parts.”
Data Center Challenges for I&O Leaders
The challenges highlighted will be very familiar to everyone in infrastructure and operations:
- Infrastructure and operations (I&O) leaders are constantly inundated with hype about artificial intelligence (AI) at the business level, without being offered the necessary guidance for how to raise the overall intelligence level of the data center (DC) and its operations.
- While vendors may sell AI as individual technologies to raise business expediency, there are no standards or guidelines for systems to share intelligence, preventing DC-level insights.
- Rapid rates of change and increasingly complex data centers consisting of decentralized and hybrid cloud infrastructures make it difficult for I&O leaders to select the right tools.
Read the entire article here, The Intelligent Data Center is Beyond Human Scale
via the fine folks at Turbonomic!