Cloud architects need to understand cloud technology and how the pieces fit together. They also need to understand old school process Credit: Free-Photos Cloud architecture is popping up again as a hot topic. Cloud architects are hard to find, salaries are going up, and many are seeking cloud architecture training. Most architects are really just subject matter experts on a single public cloud provider, and don’t understand other providers and how they can work and play well together. This causes some cloud deployment failures as architects become more and more myopic, using the same technology stack no matter if it’s a fit or not. I’m finding that a return to traditional architectural processes used 20 years ago may be a better fit for cloud computing in 2020. However, they need to be modernized for the way we build solutions today and the technology we use. “Paralysis through analysis” will always be a risk. Moreover, traditional sequential architectural processes (waterfall) fly in the face of the new world of agile methods, which are automated by very slick devops toolchains and processes. Cloud architects must avoid these two extremes: First is thinking that you can iterate your way to cloud architecture success in record time. The application development model (getting it wrong many times before getting it right) is an accepted process for optimizing application development and reacting quickly to changing business needs. However, the same approach won’t work for architecture, unless you plan on spending millions of dollars unnecessarily to get to the right, fully optimized architecture. You just can’t adopt expensive technology or cloud services that way without adding a tremendous amount of risk and cost. Second, those who look at cloud architecture as a slow trod, burdened by committees, selection teams, etc., where it takes a year just to pick the fundamental cloud technologies, will find that the world changes faster than they can keep up. They’ll deploy an architecture that’s out of date the day it goes into production. So, what is the best path to a successful cloud computing architecture? The best practices these days are really around “fast planning,” and that’s something I practice every day. Really, it’s old school meets new school. First, create a master, enterprisewide logical architecture to provide a foundational understanding of what the cloud architecture is, in relation to the existing enterprise architecture. Don’t assign any part of the logical architecture to a specific technology. This is the vision that you’ll build around—the macroarchitecture. Second, decompose the logical (macro) architecture down to many microarchitectures. In most Global 2000 companies this will be by department, technology platforms, data storage, security models, or all of the above. Break the macroarchitecture apart so that the microarchitectures are solvable using fast planning. Finally, leverage custom processes around each fast planning sprint for each microarchitecture. Simply put, this means time-boxing the planning cycle for each microarchitecture to a few weeks or even a few days. These should be decoupled and can be done in sequence or in parallel. It’s interesting how we need to mash up approaches from the past with what’s working now, all fueled by the need for speed. The best architects keep an open mind about technology, processes, and methods. We need to be continuously improving. Related content analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing analysis All the brilliance of AI on minimalist platforms Buy all the processing and storage you can or go with a minimum viable platform? AI developers and designers are dividing into two camps. By David Linthicum Jul 09, 2024 5 mins Generative AI Cloud Architecture Artificial Intelligence analysis The next 10 years for cloud computing Despite AI's explosive growth, the industry still needs to face facts that customers are unhappy about costs and vendor lock-in. By David Linthicum Jul 05, 2024 5 mins Amazon Web Services Google Cloud Platform Microsoft Azure analysis Serverless cloud technology fades away Serverless was a big deal for a hot minute, but now it seems old-fashioned, even though its basic elements, agility and scalability, are still relevant. By David Linthicum Jul 02, 2024 4 mins Serverless Computing Cloud Computing Software Development Resources Videos