Originally published on the Pivot3 blog, November 6, 2018.
What can we learn about the future of IT infrastructure through understanding the levels of automation required for self-aware, self-optimizing, self-driving cars? Taking a look at the four levels of a vehicle’s autonomy and comparing it to where we need to be with infrastructure software platforms to support the mission-critical demands of the IoT and hybrid cloud, we can see some interesting parallels.
Starting at level 1, it is application-centric, which means you can tell the car where you want it to go, inform speed and other basic instructions. This is similar to how you would interact with your IT infrastructure platform in terms of what you are trying to achieve – what application workload do you want to run? What does it need to run efficiently and optimally? You set it up, and from there it does the rest, with minimal human interaction.
At level 2, self-driving cars become more policy-driven. You now tell the vehicle how to take a shortcut, go the scenic route, map trips according to petrol or charging stations, and more. For your infrastructure platform, you’re now setting service-level policies for the workloads you’re now running and indicating if they business-critical, mission-critical or non-critical and further defining them with preset performance and data protection policies.
At level 3, the vehicle has what it needs but it still can’t really drive itself without someone in the driver’s seat. It still needs some level of self-awareness to determine if it should pass a car or stay in the lane, swerve around a hazard or a cyclist, augment the trip based on fuel levels, and so on. Likewise, IT infrastructure needs to become self-aware to support the looming challenges of the IoT and hybrid cloud. Organizations are still relying on humans to navigate and manage complexity, but IT teams spend too much of their time firefighting and keeping the lights on, which will be close to impossible at the scale needed to support the new generation of data and demand for business services. In the current model, IT typically only gets involved after something has gone wrong, which for a self-driving car is too late, and the same is true for your mission-critical workloads. A self-aware system is both predictive and proactive and can immediately analyze the data in real time, process it at the edge, as close to the source of generation as possible, and deliver insight to the user.
At level 4, autonomous vehicles are both self-aware and self-optimizing. They can adjust their settings on the fly by augmenting cruise control and acceleration governing via LIDAR sensors. Similarly, a self-aware, self-optimizing agile IT infrastructure will be able to adjust operations on the fly with intelligent algorithms that detect changes in the environment and proactively adjust in real time to accommodate the needs of applications based on their level of criticality, preventing failures and catastrophic events. It will also be able to automate hybrid cloud strategies in terms of where workloads reside, how they move from on-premises to the public cloud and back. In other words, the infrastructure platform must be able to drive itself.
Organizations with digital transformation initiatives, in the context of mission-critical IoT or hybrid cloud, need to understand the looming demands on their infrastructure platform and seriously consider if their current solution is future-proofed to accommodate them.
