It's clear that cloud computing will continue to grow, but here are three less-obvious aspects to keep on your radar. Credit: Getty Images It’s that time of the year when PR folk promote their clients as somebody who can make predictions for 2021 that all should regard. I’m often taken back by the obvious nature of the assertions, such as “cloud computing will continue to grow” or “there will be an expanded need for cloud security.” Okay, that’s not at all helpful. The reality is that although we can see much of the future based on obvious past and current patterns, other portions of the cloud computing market are much tougher to forecast. Enterprises won’t see some trends until it’s too late. Here are three to at least put on your radar: First: a focus on intercloud orchestration. Today we’ve not seen a demand for the three major cloud brands to work and play well together at deeper levels. This is largely because they operate in their own self-interest, and building bridges between public clouds is bad for business. With more than 90 percent of enterprises using multicloud, there is a need for intercloud orchestration. The capability to bind resources together in a larger process that spans public cloud providers is vital. Invoking application and database APIs that span clouds in sequence can solve a specific business problem; for example, inventory reorder points based on a common process between two systems that exist in different clouds. Emerging technology has attempted to fill this gap, such as cloud management platforms and cloud service brokers. However, they have fallen short. They only provide resource management between cloud brands, typically not addressing the larger intercloud resource and process binding. This a gap that innovative startups are moving to fill. Moreover, if the public cloud providers want to truly protect their market share, they may want to address this problem as well. Second: cloudops automation with prebuilt corrective behaviors. Self-healing is a feature where a tool can take automated corrective action to restore systems to operation. However, you have to build these behaviors yourself, including automations, or wait as the tool learns over time. We’ve all seen the growth of AIops, and the future is that these behaviors will come prebuilt with pre-existing knowledge that can operate distributed or centralized. This means that from day one you can automate most of the issues that cloud and non-cloud systems will need to deal with, and knowledge will build and be shared over time. Third: renewed focus on the organization. No matter if it’s operations model changes, skills gaps, or flattening organization structures, enterprises need to renew their focus on the people aspect of cloud computing. Skills, organizational structures, and processes need to change around the use of cloud computing. Unfortunately, most organizations view these changes as “opening Pandora’s box,” as one client put it years ago. It becomes a can that leadership kicks down the road. Truthfully, you won’t get much out of cloud computing without the courage to push these changes through leadership. The alternative is good technology and bad technology usage, and that means failure. I suspect more unexpected things will happen next year than expected ones. Watch this space for a discussion of those emerging issues. 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