Over the last 40 years (I started young!), I’ve been lucky enough to have seen and been a part of many inflection points in the history of computing. To quickly recap:
- Starting my first software company as a teenager, at the dawn of the PC revolution.
- Working with companies as a Gartner analyst at the beginning of the Internet Economy when e-commerce and online ‘everything’ was just beginning.
- Helping Adobe during the early days of web content and the delivery of online applications (via PDF and the purchase of Macromedia and Flash).
- Supporting the SaaS transitions of legacy enterprise software companies such as Corel, Lyris, Mindjet, and Selectica.
- Learning about the new field of big data analytics and enterprise data monetization strategies at GoodData.
- Immersing myself in industrial IoT, AI/ML, and edge computing while helping Vantiq go from a 20 employee, pre-revenue company to the highly successful company it is today.
- And, finally, advising so many early-stage industrial-tech startups at Momenta, helping them to position their solutions, bring them to market, and raise the capital necessary to do it effectively.
Being there at the beginning of each of these major technology inflection points has given me a keen sense of trends – when it’s too early, when it’s too late, and when it’s ‘just right’ as Goldilocks used to say. I truly believe that the time for an intelligent edge computing and distributed cloud platform is just right.
Organizations around the world have clearly embraced the cloud (whether public, private, or hybrid) – thus the boom in cloud-based products, tools, and platforms in the last decade. Industrial IoT and AI/ML have finally made it out of the innovation labs at most large companies and are being deployed in production environments. It’s about time!
And now these same organizations are piloting systems using edge computing and distributed cloud architectures because they have learned from a series of failed ‘digital transformation’ initiatives that a monolithic, cloud-based system cannot ensure the resiliency, scalability, and security that they require for many complex use cases.
Now it’s obvious to most CTOs that edge computing and distributed systems generally are the answer to many of these issues. The unfortunate challenge is: standing up a system capable of doing that is non-trivial. Only a small handful of architects have ever designed, implemented, and tested such systems in the real world.
And that’s the challenge that I saw Pratexo addressing.