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DevOps is all about how businesses must be results-oriented to meet evolving customer demand and gain greater market share. Today’s marketplace is connected, always on and increasingly competitive. Companies are adopting what we call an “as-a-service” approach to achieve better outcomes fast, consuming and leveraging leading-edge technologies such as cloud and automation.

As IT systems grow exponentially, and cloud solutions proliferate, non-automated, manual systems increasingly are becoming a major business liability.

Today’s systems are simply becoming too big and complex to run completely manually, and working without automation is largely unsustainable for many enterprises across all industries.

Automation involves a set of tools, processes and insights that allows IT environments to self-modify and adjust, and some enterprises have started using intelligent automation to drive a new, more productive relationship between people and machines. For example, IT automation is often used to auto-scale and load-balance large fleets of servers, manage global content distribution based on geographic demand, enable self-healing of IT systems and manage security mostly with limited ongoing manual intervention.

Moreover, automation enables the ability to adapt and improve the service experience without manual intervention. However, while these tools offer new strengths and capabilities, they are meant to complement and enhance human skills.

Effective automation depends on adequate insights collected from all the systems relevant to the service experience and business outcome you’re trying to augment. Insights from data is necessary to create opens paths to automated predictions and ultimately using machine learning, or artificial intelligence, as part of a full scope the as-a-service construct.

Specific insights known as telemetry allows signals to be harvested and interpreted so automation can better adjust production systems to maintain a healthy business. The insight gathered from such analytics allows automation to validate and compose modification rules. For example, sensors that detect a supply chain issue could automatically reroute or fine-tune related functions, such as dispatch or logistics, to solve or generate a workaround for the issue. The business flow can adapt and realign automatically with the ultimate goal of improving the customer experience.

Automation Creates Higher Degree of Experimentation

Automation also can provide a higher degree of experimentation and increase agility, two key attributes of as-a-service economy. Automatically provisioning a component such as a virtual machine, for example, is only a piece of the puzzle since automation is most valuable when it contributes to improving a customer experience or delivering a business outcome.

A platform that’s constantly testing, experimenting and developing allows companies to try new ideas in production quickly without fear of failure or outage. When confidence in system resiliency is high, it allows businesses to test new things directly in production (A/B testing). If an experiment fails, there is no harm done as automation returns the system to steady state. If an experiment succeeds, it is quickly absorbed into the production itself.

A fast, efficient experimentation platform enables businesses to react faster to failures and successes—and pivot accordingly without excess wasted resources.

For example, a retail company might change a shopping basket feature for 1 percent of its customers.

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