Modeling Your Cloud Around Operations

The benefits of the cloud have been seared into the psyche of every tech and business leader over the last couple of decades.

Fueled by promises of greater efficiencies, improved application management, lower costs, agility, scalability, and so much more, countless organizations have moved their businesses in some fashion to the cloud. Over the years, however, the cloud has grown as complicated as it has sophisticated, forcing most into a perpetual balancing act of having to determine the most effective places to run their workloads – on prem, in the cloud, at the edge, etc., or any combination thereof.

As this increasingly complex environment evolves, our reliance on it for information and communication only intensifies. So much so that we would be wise to begin viewing the cloud not as the agile IT destination it’s become known for, but rather, as a true operating model unto itself, one that is critical to driving business outcomes.

Consider the Model

We leverage the cloud to manufacture, manage, mine & refine incredible amounts of data to help guide virtually every facet of our businesses. We integrate data planes to carry information across the enterprise, fabrics to ensure successful data exchanges across multi-cloud environments, and management systems to capture, organize and authorize the data for use – all in support of the broader business model. Through it all we abstract software through software-defined technologies, divorcing it from the digital infrastructure below through a common data plane. We hide the complexities of the cloud from users while providing greater visibility and manageability to the very digital assets we shield.

From this point, all data is controlled, managed, and primed to support business units and models.

Buttressing the Business Model with Data

To be sure, managing the cloud as a new operating model is as evolutionary as it is critical in 2023. As we write this, the digital universe continues to expand, as data from everything from IoT, IIoT, social media, and now Generative AI apps and tools, swell data centers. In fact, the hunger for fresh, cleansed data to feed tools like OpenAI’s ChatGPT or Google’s Bard may never be fully satiated, as data resources – people and systems – continue to be stressed.

For our part at Hitachi Vantara, this new operating model centers on data. That’s because within this model, data is no longer confined to a single place. It’s accessible and available through a common data plane. Things like data management, storage, analysis, AI – it all becomes interwoven and ethereal to an extent – something that is greater than the technology itself.

The concept enables CIOs to orchestrate their digital environments around the utilization of information and applications specifically to buttress the business model. In the process, mining & refining data is streamlined, as data silos come down and access and availability climb. In this operating model, the right data is provided to the right people at the right time.

Beyond the Digital Infrastructure

This is a far cry from our traditional views of cloud as data centers, server racks, cables, XaaS capabilities, and more. Instead, this approach focuses on outcomes, the generation and flow of information. In fact, the concept extends to the digital infrastructure, as well, where systems are viewed as software rather than purely “hardware.” Software layered and software defined becomes the unifying piece across the hybrid multi-cloud landscapes.

Why is this important? New disruptions to the enterprise are coming quickly. From the Generative AI work that’s washing over businesses, to never-ending mounting data volumes, to the constant rise of cybercrime, the need for, and access to, data grows more critical every day.

The challenges have given rise to a new discipline, data reliability engineering. This work marries DevOps and site reliability engineering capabilities with data systems. As data reliability firm, Monte Carlo, wrote recently, the primary role of the, “…data reliability engineer is to ensure high-quality data is readily available across the organization and trustworthy at all times.”

AI, like business, is fueled by data. And in the face of rising hybrid multi-cloud complexities, organizations would be wise to begin taking a new approach to the cloud; an approach that will empower the business with always-on data and critical insights; an approach that accelerates strategic decision making and enables organizations to peer into the future with confidence.

Rather than the destination we’ve come to know, the cloud is truly the operating model of the future, today.

This story first appeared on Monica Kumar’s LinkedIn Article page.