Today, most of Information and Communication Technology’s (ICT) value lies in cloud computing, and we are still looking for an endless finish to that trend. Because of that, today’s R&D goes massively to public cloud-based solutions. These companies have better databases, development platforms, software and cutting-edge generative AI.

If you are “out-of-the-cloud,” it means its technology will be inferior to cloud-based ones.

The Movement Toward Cloud-Native Applications

Cloud-native applications are defined as programs designed for cloud computing architecture. They leverage the cloud’s characteristics to deliver scalable, flexible and resilient applications based on microservices, containerization, API-based communication and orchestration. They are built to provide superior performance and avoid cloud and platform lock-in. However, given the impressive features each public cloud provider offers, only some applications leave the platform they were designed for.

Designing a fully portable application requires trade-offs of costs, time and resources. On the other hand, if you use cloud-provider native features to localize the applications and databases, moving these applications to other clouds will require a multi-cloud approach.

Many existing private clouds are open source and need help to cope with public clouds’ feature explosion and parity. The truth of multi-cloud and hybrid clouds is that they require replicating tools, skills and organization across clouds, which is becoming more complex and costly.

Multi-cloud choices usually present missed opportunities for cost optimization, therefore not saving money.

In the past three years, there has been an explosion of AI software that is notorious for intensive I/O cloud computing, which incurs higher costs. Generative AI is today’s hot topic, and even with today’s cheaper pay-as-you-go models, running generative AI models in the cloud is expensive.

Evolution

The costs of public cloud providers are falling, but the costs to the enterprise continue to rise. Repatriation will take place due to the rising costs of public cloud compared to the falling costs of hardware and software, and there’s a trend to run some services like data storage in the most cost-effective places.

Traditional enterprises need the know-how to deal with current intricacies and moving to multi-clouds can increase complexity. Also, it is crucial to notice that enterprises might hire low-quality people and make significant mistakes, causing efficiency problems and ultimately affecting customer experience. Note: A lot has been written on how to overcome these shortcomings, and I highly suggest reading the multicloud strategy for cloud migration.

I believe essential services like computing, memory and storage will eventually be commoditized. Within a few years, the public cloud will look the same and possibly have cross-cloud capabilities—some experts call these superclouds or metaclouds.

Developing superclouds will require a staggering number of resources, such as R&D, and only a few selected companies can do it.

Imagine that in the future, software applications would have the capability to decide on the best cloud configuration, where it is cheaper or more efficient for its performance. Let’s name these autonomous services.

These autonomous services would be more efficient, using the optimal amount of resources, and thus less costly. Skills will shift from generalist to specialized knowledge to support super clouds and autonomous services, affecting employment trends in the cloud sector. In my opinion, another critical factor is that future cloud security will focus on proactive measures and observability, utilizing biometrics for authentication​​.

I expect cloud computing to become increasingly local and more pervasive, with computing, processing, memory and storage distributed beyond traditional large cities into midsize metropolitan centers, becoming more geographically distributed, improving performance and accessibility​​ in the form of edge clouds.

Conclusion

In the fast-evolving landscape of cloud computing, we stand at a pivotal juncture that could redefine the technological and economic paradigms of the ICT sector. As we delve into the future, the massive investments in research and development to enhance public cloud-based solutions announce a new era dominated by advanced databases, development platforms, sophisticated software and groundbreaking generative AI technologies. This transition underscores a fundamental shift where being “out-of-the-cloud” is no longer an option but a setback, given the superior capabilities of cloud-native applications.

These cloud-native applications, characterized by their scalability, flexibility and resilience, are the vanguards of a future where cloud computing is not just a choice but a necessity for achieving technological superiority. However, the journey towards a fully portable and cost-effective cloud infrastructure is fraught with challenges, including the complexities of multi-cloud strategies and the escalating costs associated with running intensive AI applications in the cloud.

As the cloud computing industry unfolds, the emergence of superclouds offers a glimpse into a future where cloud services are commoditized, and enterprises can navigate the complexities of cloud environments with unprecedented efficiency. This evolution towards autonomous services and specialized skills for managing superclouds points to a future where cloud computing is not just centralized within large urban centers but becomes a pervasive and localized force closer to the applications and their users.

In conclusion, the future of cloud computing is characterized by a relentless pursuit of innovation, cost-effectiveness and operational efficiency. As enterprises grapple with the evolving dynamics of cloud services, the development of superclouds and autonomous services will play a critical role in shaping a future where cloud computing is integral to every facet of technological advancement and economic growth.