Editor’s note: This is the 62nd article in the “Real Words or Buzzwords?” series about how real words become empty words and stifle technology progress.
“Autonomous compute infrastructure” refers to IT infrastructure (compute, network and data storage) that manages itself with minimal to no human action throughout its lifecycle.
This is the current state of information technology advancement and is highly relevant to organizations deploying electronic physical security systems, especially critical infrastructure organizations.
I’ll be speaking about this at the Converge Security Conference on Friday, September 30, 2022 in my 4 p.m. session titled, “Lessons Learned from the Front Lines of Security Convergence” at the at the Marriott Hotel near the Anaheim, Calif. Convention Center.
This and related topics are also part of the 3- to 5-year look ahead at the future of security leadership and physical security technology at the Global Security Operations event (GSO 2025) on November 2 & 3, 2022 at the Vari (formerly VariDesk) global headquarters in Irving, Texas.
This article is about automating the management of compute infrastructure itself, not about the automation of applications that reside on it. That’s a separate subject and will have its own article.
The Growth of Computing Virtualization
For over a decade cloud data centers, as well as on-premises data centers, have been utilizing virtualized computing environments whose management software takes any number of separate hardware resources (servers, networks and data storage) and aggregates them to create virtual resource pools – virtual servers, virtual networks, and virtual storage.
The virtualized resource pools are much easier to manage than individual hardware elements. As explained in this TechTarget article, the approach eventually became known as software-defined data center (SDDC), a term coined by former VMware CTO Steve Herrod around 2012.
The Resulting Data Center Explosion
In the 10 years following, continuing advances in computing hardware and virtualization software have given us the ability to create very large pools of virtual CPUs and GPUs, virtual RAM, as well as software-defined networking (SDN) and software-defined storage (SDS) all connectable at gigabit speeds.
These can be assembled as large clusters of connected high performance virtualization appliances, providing highly scalable pools of each type of computing resource.
The evolution of software to automate and orchestrate the complex configuration and management for the vast amount of hardware resources being virtualized has made it possible to manage the elements of large virtual systems via a single pane of glass (same computer screen).
These continuing advances in computing have helped fuel the data center explosive growth required to support the ever-growing number of software applications and systems of increasingly greater size and complexity.
However, in spite of advances in data center automation and orchestration, data center staff continue to be overloaded, exponentially increasing the possibilities for human errors, system failures, and the security vulnerabilities that result from them.
Fortunately, these very computing advances have made possible the development and use of artificial intelligence software capable of managing vast amounts of virtualized IT infrastructure with minimal involvement by IT staff, eliminating traditional staff errors and reducing deployment times to a fractions of what they have been.
Autonomous Compute Infrastructure
Autonomous compute infrastructure is the IT world’s equivalent of the self-driving vehicle. It is the intelligent (i.e., AI-based) automation of IT infrastructure management workflow that used to require highly skilled and specialized IT personnel.
“Autonomous compute infrastructure is a continuum”, says Dell Technologies in its highly insightful point of view paper introducing the concept in February of 2021, which it explained further six months later in a white paper titled, “An Introduction to the Autonomous Framework by Dell Technologies.”
This paper describes a six-level Autonomous Framework for IT operations, from no automation to full autonomy. It also provides background information, expands upon each level of this framework, and provides some considerations for the road ahead.
Autonomous Infrastructure Self-Management
Basically, autonomous compute infrastructure refers to the degree of self-management of an IT infrastructure deployment throughout its lifecycle.
This goes way beyond redundancy-based fault tolerance, self-healing networks, and so on.
It includes, for example, the ability to expand a security system deployment by adding new compute, storage, networking or security device hardware, and having the existing pools of virtual resources automatically expanded and reallocated to existing applications, without any system downtime or system performance degradation.
Thus, autonomous compute infrastructure can maintain itself at 99.9999% (“six nines”) uptime – which allows a total of 31 seconds of downtime per year.
Such infrastructure self-management could include automatically copying a virtual machine running security applications from one physical server to another to achieve higher performance from a newly added server in the resource pool, without any application interruption.
This kind of change would be based on AI predictive analysis of system performance and application utilization trends.
The automation capabilities would also report on predicted future needs for system expansion, or reallocation options for of newly developed spare capacity. Specifying the extent of self-management can be accomplished by a single IT staff person, instead of the formerly required team of IT specialists.
Pivotal Change in IT Infrastructure Management
I believe, as Dell says, “We’re on the brink of a radical new approach to technology, driven by autonomous operations (AO) that will enable businesses to radically delegate all manner of low-level, repetitive and non-strategic IT tasks to intelligent technology.”
Because we are all familiar with automobiles, Dell was able to leverage our understanding by likening the autonomous compute spectrum to the various levels of autonomous driving.
Radical New Technology Approaches
Dell very accurately makes an additional analogy relating to the vehicle industry.
Jon Siegal, senior vice president, product marketing, Dell Technologies, wrote, “The creation of the internal combustion (IC) engine changed society forevermore. At the time of its inception, most people would have been unaware that history was in the making. That it would birth a hypermobile society, opening the floodgates to all manner of cars, trains, airplanes. That it would pave the way for rapid trade and consequently greater prosperity. That it would revolutionize agriculture and transform farming, resulting in more food at lower prices. And that it would remove limits to how far we could travel through physical effort.”
Siegal continues, “Similarly, business leaders today may not realize that they’re presiding over such a key moment in time. We are on the brink of a radical new approach to technology, driven by autonomous operations (AO), that will enable businesses to finally ‘take control by inversely, letting go’.
With AO, businesses can radically delegate all manner of low-level, repetitive, and non-strategic IT tasks to intelligent technology and in the process, experience the thrill of reaching new heights, by exceeding limitations that were once out of reach. By partnering more extensively with machines, businesses can also improve employee productivity and satisfaction, and ultimately the customer experience.”
I encourage you to read the rest of the Siegal’s article, "Making history with autonomous operations" because although the discussion is around the broad business impacts of autonomous compute infrastructure, much of the article is highly relevant to our considerations of the current and near-future states of electronic physical security systems.
Utilizing the Autonomous Compute Infrastructure Framework
There many ways for physical security practitioners to use Dell’s autonomous compute infrastructure framework, such as evaluating one's own current infrastructure, evaluating vendor product roadmaps, and prioritizing specific elements and capabilities of security systems in upgrade planning.
More broadly, it provides a cross-domain perspective for digital transformation stakeholders, and a touch point for discussions relating to physical security’s participation in the organization’s digital transformation efforts and initiatives.
Ray Bernard, PSP CHS-III, is the principal consultant for Ray Bernard Consulting Services (RBCS), a firm that provides security consulting services for public and private facilities (www.go-rbcs.com). In 2018 IFSEC Global listed Ray as #12 in the world’s Top 30 Security Thought Leaders. He is the author of the Elsevier book Security Technology Convergence Insights available on Amazon. Follow Ray on Twitter: @RayBernardRBCS.
