Just when we thought cloud computing could take a post-pandemic victory lap, we now face the largest challenge to date.
In the latest Agents of Transformation report, Agents of Transformation 2021: The Rise of Full-Stack Observability, 77% of global technicians report experiencing a higher level of complexity as a result of accelerated cloud computing initiatives during the pandemic. A further 78% cited the need to manage the legacy and cloud technology patchwork as a further source of technology spread and complexity. (Note: The sponsor of this article sells an AIops/observability tool.)
What’s behind these high percentages? A perfect storm of events that continues to fuel the rapid growth in complexity.
First, there’s the acceleration of cloud adoption and rapid migration, initially driven by the pandemic and now by business recovery. This led to a lack of planning and then the selection of too much technology to solve business problems without accounting for how everything would be operationalized.
Second, there’s the rapid growth of new types of cloud and cloud-connected technology. We now need to integrate cloud-based platforms with technology such as edge computing, Internet of Things, artificial intelligence-driven business analytics and insights, and existing traditional systems that can’t be retired.
Enterprises hit the “complexity wall” soon after deployment when they realize the cost and complexity of operating a complicated and widely distributed cloud solution outpaces its benefits. The number of moving parts quickly becomes too heterogeneous and thus too convoluted. It becomes obvious that organizations can’t keep the skills around to operate and maintain these platforms. Welcome to cloud complexity.
Many in IT blame complexity on the new array of choices developers have when they build systems within multicloud deployments. However, enterprises need to empower innovative people to build better systems in order to build a better business. Innovation is just too compelling of an opportunity to give up. If you place limits on what technologies can be employed just to avoid operational complexity, odds are you’re not the best business you can be.
Security becomes an issue as well. Security experts have long known that more vulnerabilities exist within a more complex technology solution (the more physically and logically distributed and heterogeneous). This means a significant risk of a breach or ransomware attack that staff must somehow mediate.
So, if complexity is the result of innovation and fast-moving technology to adequately support the business, how do you keep up? It’s all about working smarter with technology that can remove humans from the equation as much as possible. Clearly, IT already deals with more systems than they can effectively manage and operate. If they haven’t confronted this yet, they will soon. The solution is abstraction. You need a control panel that sits in front of all types of cloud and non-cloud systems, using automation and AI to proactively deal with the rising complexity without restricting innovation or adding security risk.
These tools are coming or are here under many types and names. They include tools that support observability, such as AIops, as well as security management, proactive monitoring, and cross-system orchestration, just to name a few. The tool stack needed to deal with complexity will be, well, complex, at least in the beginning. There is no magic bullet. Not yet. Initially, I suspect only skilled cloudops engineers will understand how to effectively use these tools.
Soon abstraction and automation won’t be an option. It’s time to research and employ new and emerging tools to address your enterprise’s cloud complexity. Do it quickly, or prepare for the business to exit the marketplace.
This article originally appeared on InfoWorld.