With the new architecture, we’re certainly moving to complex distributed systems. Plan now to succeed Credit: Getty Images Distributed cloud, according to Gartner, “is the distribution of public cloud services to different physical locations, while the operation, governance, updates, and evolution of the services are the responsibility of the originating public cloud provider.” That’s “analyst speak” which means we’re moving from centralized to decentralized cloud computing solutions. But we need to still maintain centralized control. If this is true—and it’s certainly a trend—then we need to be prepared for the distribution of physical processes, storage, and applications, with management, monitoring, security, and governance management layers that will make these complex distributed systems cloudops ready. By the way, this is not to be confused with multicloud, which means running more than a single public cloud brand, such as AWS and Microsoft. These architectures, while typically complex, are not necessarily distributed. There are a few reasons distribution is a trend now for most enterprises using a single or multiple public clouds. Enterprises need to support edge-based computing systems, including IoT and other specialized processing that have to occur near the data source. This means that while we spent the past several years centralizing processing storage in public clouds, now we’re finding reasons to place some cloud-connected applications and data sources near to where they can be most effective, all while still maintaining tight coupling with a public cloud provider. Companies need to incorporate traditional systems in public clouds without physical migration. If you consider the role of connected systems, such as AWS’s Outpost or Microsoft’s Azure Stack, these are really efforts to get enterprises to move to public cloud platforms without actually running physically in a public cloud. Other approaches include containers and Kubernetes that run locally and within the cloud, leveraging new types of technologies, such as Kubernetes federation. The trick is that most enterprises are ill-equipped to deal with distribution of cloud services, let alone move a critical mass of applications and data to the cloud. The challenge is not how you succeed with distributed cloud computing, but how you prepare in the first place. My best advice is to splurge on understanding centralized control mechanisms, such as management, monitoring, security management, and governance systems. This does not mean that you toss tools at the problem, but you understand the capabilities of the available tools, and that will determine how well (or not so well) you can operate your distributed cloud computing solution. The real message here is that you need to plan now if you think you’ll take advantage of distributed cloud computing. Else, it will be an epic fail that you don’t need these days. Related content analysis Strategies to navigate the pitfalls of cloud costs Cloud providers waste a lot of their customers’ cloud dollars, but enterprises can take action. By David Linthicum Nov 15, 2024 6 mins Cloud Architecture Cloud Management Cloud Computing analysis Understanding Hyperlight, Microsoft’s minimal VM manager Microsoft is making its Rust-based, functions-focused VM tool available on Azure at last, ready to help event-driven applications at scale. By Simon Bisson Nov 14, 2024 8 mins Microsoft Azure Rust Serverless Computing how-to Docker tutorial: Get started with Docker volumes Learn the ins, outs, and limits of Docker's native technology for integrating containers with local file systems. By Serdar Yegulalp Nov 13, 2024 8 mins Devops Cloud Computing Software Development news Red Hat OpenShift AI unveils model registry, data drift detection Cloud-based AI and machine learning platform also adds support for Nvidia NIM, AMD GPUs, the vLLM runtime for KServe, KServe Modelcars, and LoRA fine-tuning. By Paul Krill Nov 12, 2024 3 mins Generative AI PaaS Artificial Intelligence Resources Videos