Today, we live in the golden age of innovation due to the great technological computing resources we have access to. And one of the greatest technological drivers for spurring this innovation is the public cloud. Companies like Amazon, Google, and Microsoft have invested massive capital in enabling developers and organizations to create scalable services on the fly, with little to no overhead making it extremely straightforward to meet business-critical application rollouts. This emphasis on decentralized pay-as-you-go resources has accelerated growth and technological innovation, unlike any other time in history.
In the early years of software development, a person could spend months, if not years, building the underlying infrastructure from scratch to support a new implementation or project. In great contrast, today, most of the needed underlying infrastructure required to build an application is readily available at your fingertips.
The cost of scalability has been greatly reduced due to serverless architecture in cloud computing. Today, serverless architecture services allow organizations to consume only what’s needed and don’t have to pay for idle time or infrastructure to support these critical applications. And, with these services, one can automatically scale up or down depending on demand. You don’t have to think about application or deployment in the same way you once did when designing for scale was a central concern. This is an operational revolution.
Unlocking Insights Through Cloud Technologies
The data within any given product holds significant innovation potential. Organizations are continually looking for insight and key new services from cloud providers, as these new technologies can build value in their products. Today, organizations have access to incredible insights and analytics they didn’t have access to five years ago. Thanks to cloud providers, organizations can connect a wide range of data analytics and insight services in new ways that weren’t formerly possible.
Machine learning is another example of cloud-based systems that make it easier to innovate. The learning curve for machine learning is steep and difficult because most of your time is spent exploring the data, building the models, deploying them, and refining them. However, with advancements in the public cloud, major public cloud outlets are automating away many of these challenges and, in doing so, relieve approximately 90% of the workload typically dedicated to set up and turn it into a plug-and-play system. These systems are much cheaper and easier to set up. You pick the pieces you want and get new machine learning insights right out of the box with minimal effort.
Adopt a No-Code Mindset
The one suggestion for innovators looking to leverage the cloud’s capability would be to stop creating new code. For people who have a technical background, this is not easy to do. But when you are innovating, you need to spend your time working on the value proposition and the insight you already have. The core of your innovation is not the code you write to make it happen; consider adopting the no-code mindset. Find an implementation that already exists and stitch it into your infrastructure. Save your time and your energy.
Identify what the public cloud providers can offer. These providers have very reliable, highly scalable, elastic services that are all managed, secure, and ready for you to use. If you can’t find what you need there, turn to the open-source community and look for the other pieces you need to bring in. As both the cloud service providers and the open-source communities continue to grow, minimal coding must do most of the innovation.
Start Looking for Patterns
Most innovation today is about seeing patterns. It’s no longer about inventing something radically new. In leveraging cloud capabilities, always consider what patterns already exist. Look at access patterns in your system or the ways that your systems talk to each other. Look at deployment patterns. Analyze the problems you encounter with your products, your services, or your customers. Find patterns, then apply the solutions.
What Innovators Need to Stop Doing
- Open-ended research. Set a 60-day cycle for any innovation project or problem. This keeps the process moving forward.
- Working on anything esoteric. Make sure you clearly define a question first, then set metrics to measure your success. Determine what problem exists before solving one that doesn’t.
- Aimless experimentation. Set out at least five experiments you want to execute, each with a timeline of no more than a week. Give yourself a path to follow and be vigilant.
- Ignoring the lessons. Make sure you learn from your experiments. Get the answers you need from them and use that data to decide the next steps to take.
- Analysis paralysis. Make decisions fast, even if they are the wrong decisions. When you fail fast, you can learn from it and move on. Rapid failure is better than being stuck in the same place for too long.
The Public Cloud Paradigm – Old Rules Don’t Apply
Almost everything you think about and how you think about it will undergo a metamorphosis in the public cloud. Even the standard constructs about how you write, design, deploy, monitor, and manage code are different. The traditional models don’t apply here, and if you try to use them, you’ll almost always fail.
Approach this space with an open mind. Do your research about what you can leverage from the cloud. Learn how it works and be ready to accept the differences. Then you can get all the benefits of innovating through the cloud. The public cloud platforms offer a fantastic set of capabilities, allowing innovators to solve significant problems with speed and agility.
Take advantage of this new paradigm, think differently about approaching innovation, and maximize your leverage of the cloud’s native capabilities.