Cloud has grown up. Now businesses need to grow smarter

A short time ago, the main issue in cloud computing was this: How fast could we migrate?

By Avinash Gupta, head of centre of excellence at In2IT Technologies

In every sector of the business world, moving applications and data into the cloud came to mean digital transformation. Cloud adoption became closely associated with digital transformation, and progress was commonly measured through metrics such as the number of workloads migrated, percentage reduction in on-premises infrastructure, data-centre consolidation, virtual-machine retirement and overall cloud-consumption growth.

However, many of these migrations were largely based on “lift-and-shift” strategies, in which existing applications were rehosted on cloud infrastructure without being redesigned for cloud-native architectures, automated scalability, resilience, observability or cost efficiency.

Now the conversation is different. For most organisations, migration is no longer the issue they have to deal with; rather, they are now posing much more strategic questions such as: Are we using the correct cloud platform?

Are we obtaining value from our investment? How can we support Artificial Intelligence (AI)? Should certain workloads stay private? And how can we strike a balance between innovation and security, cost and compliance?

These questions point to something that goes well beyond changes in technology priorities; they show that the cloud has reached a new stage of maturity at which business outcomes are far more important than simply where the applications are running.

**When success makes technology look ordinary **

As technologies mature, their underlying complexity becomes increasingly abstracted from users and they transition from visible innovations into essential infrastructure services. Electricity is no longer seen as something innovative, even though most businesses would not be able to function without it. The internet followed a similar path. Once revolutionary, it is now simply expected. Cloud computing is progressing along a similar maturity curve, with organisations increasingly viewing compute, storage and networking capacity as standardised, on-demand infrastructure rather than innovation in itself.

Cloud infrastructure is now starting to follow the same course.

The basic services involved – including virtual machines, storage and networking – are becoming more standardised among the major providers. With regard to many typical business workloads, the distinctions between the various platforms are narrowing, and the choices being made are increasingly based on commercial factors such as price, regional availability, the skills already in place and the support options.

That view might be taken as proof that progress in the field of cloud computing is decelerating. In fact, the contrary is true. Because of standardisation at the infrastructure level, innovation has been able to shift to the higher levels of the technology stack, where companies are now creating new value by means of AI and machine-learning platforms, advanced analytics, cybersecurity, automation and industry-specific services.

These capabilities depend on higher-level services such as managed Kubernetes, serverless computing, event-driven architectures, data lakes, API platforms, MLOps pipelines, identity governance and policy-based security. That is to say, while the infrastructure may be becoming a commodity, what organisations build on top of it is becoming more sophisticated than ever.

AI has changed the rules of the game

Nothing illustrates this shift more clearly than AI.

AI is generally referred to as just another cloud workload, but this fails to reflect the full extent of its impact. In fact, AI is altering the expectations that organisations have of cloud platforms. To run advanced AI models, it is necessary to have powerful processors, high-performance storage, low-latency networking, sophisticated data platforms and strong governance capabilities.

Supporting advanced AI models also requires capabilities such as data cataloguing, feature stores, vector databases, model registries, MLOps pipelines, observability, access control and lifecycle governance. The requirements go well beyond the simple act of provisioning more virtual machines. More importantly, AI is revealing weaknesses which many organisations had not realised that they had.

A company might decide to go ahead with an AI project only to find that its data is spread out among various systems, that its applications are unable to integrate properly, or that its security measures are no longer suitable. The technology itself is seldom the main barrier. The real problem lies in the underlying environment that lacks data readiness, architectural interoperability, scalable infrastructure and adequate security controls.

That is the reason why AI has become such a powerful driver of cloud innovation, since it is not only generating demand for new services but also prompting organisations to modernise the foundations that support them. To support AI effectively, businesses must improve data architecture, application integration, network performance, cybersecurity, governance, observability and operational resilience across the entire technology stack.

More choice doesn’t mean simpler decisions

Since cloud capabilities keep on developing, businesses currently have a greater number of choices than ever before. Various options are available, such as public cloud, private cloud, hybrid environments, edge computing, zero-trust security and energy-efficient architectures, all of which have attractive benefits, though not suitable for every organisation or every type of workload.

Edge computing provides an example of this. It can be of great value to industries such as manufacturing or healthcare, in which milliseconds are important. Yet the same method might introduce unnecessary complexity for a business whose workloads function just as well in a centralised cloud environment.

The same thing can be said of a private cloud. Today’s private-cloud platforms have developed considerably beyond traditional data centres, providing features such as automation, self-service options and operations similar to those of a cloud environment. They can offer considerable value to organisations that have predictable workloads, strict data sovereignty requirements or specific performance needs; in other cases, however, the public cloud will probably still be the more suitable choice.

The issue isn’t that one model outperforms another; it’s that cloud strategy is now much more complex than simply selecting a provider or comparing infrastructure specifications.

Strategy is becoming the real competitive advantage

It is ironic that as cloud infrastructure becomes more standardised, the need for strategic decision-making increases becomes more important.

If the basic technology is similar, competitive advantage then comes down to architecture, governance and long-term planning. Organisations must realise not only what technologies are available, but also why they should take them and what business problem these technologies are meant to solve. This is especially important since emerging technologies keep on appearing. Although quantum computing is causing considerable interest, most organisations do not currently regard the development of quantum applications as their top priority.

Instead, their focus is on preparing their cybersecurity strategies for a future in which quantum computing might undermine the present encryption standards. Similarly, organisations should base their decision to adopt zero-trust security or sustainability measures on operational needs rather than on the current trends in the industry.

Zero Trust should be implemented through identity-centric access control, least-privilege policies, continuous verification, micro-segmentation, device posture assessment and centralised monitoring, not simply adopted as a label. Similarly, sustainability initiatives should be tied to measurable outcomes such as infrastructure utilisation, workload efficiency, power consumption, carbon reporting and data-centre effectiveness.

Expertise is becoming the differentiator

Since cloud strategies have become more complicated, a great many organisations have come to the realisation that successful cloud adoption is not merely a technological undertaking but rather a business strategy which involves striking a balance between innovation, cost, resilience, cybersecurity, regulatory compliance, operational resilience, data sovereignty, application performance and future scalability. Decisions made at the architecture stage can have long-term consequences for operating costs, integration complexity, recovery capability and dependence on specific cloud providers.

It is here that experienced IT consultants are able to offer real value.

Instead of concentrating only on deployment, they assist organisations in assessing their workloads, decide upon the most appropriate use of public, private or hybrid cloud models, set up governance frameworks, optimise their cloud architecture and make sure that emerging technologies like AI are introduced in a responsible manner. Experienced consultants further reduce the risk of vendor lock-in by promoting open standards, portable architectures, containerisation, API-based integration and disciplined exit planning.

Their job is not to suggest the latest technology or trend, but to assist organisations in making better technology commercially justified and operationally sustainable technology decisions.

The future belongs to businesses that choose wisely

Cloud is no longer competing on infrastructure capabilities alone, and organisations should not be making decisions on infrastructure alone either. Sustainable value comes from understanding how infrastructure, data platforms, cybersecurity, automation, application services and operating models can be combined to achieve specific business outcomes.

As the technology develops, achieving success will become increasingly based on understanding how various cloud capabilities can be combined to support business objectives. Although AI, hybrid architectures, edge computing and future technologies such as quantum computing will all have a role to play, this will only be the case when they are used with a clear purpose.

The companies that will achieve the biggest competitive advantage won’t definitely be the ones that spend the most money on cloud; rather, they will be those who take well-informed decisions regarding where cloud can generate the greatest value, backed by the expertise required to deal with the landscape’s growing complexity.

Cloud has matured from a migration destination into a strategic technology platform. The businesses that succeed in its next phase will be those that develop the governance, expertise and decision-making maturity required to use it deliberately.

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