By Ari Weil, Chief Cloud Evangelist, Akamai
Current cloud architectures were built during a simpler time when cheap, readily available compute, storage and networking were accessible via a credit card, giving rise to an entirely new paradigm for how IT infrastructure is provisioned, deployed, and managed. But with rapid innovation in AI, multiplayer gaming, connected vehicles, streaming media and more, our industry is being asked to deliver a level of experience that the original model was not designed to deliver.
Research documents this shift away from the first architectural model of cloud to something new. A recent study by ClearPath Strategies illuminates a pivotal shift: two-thirds of IT decision-makers anticipate increasing their use of distributed cloud services within the next year. This isn’t just a trend; it’s a reflection of the critical need for a new kind of cloud architecture that aligns with the demands of modern applications: higher performance, lower latency, and true global scalability. As we move through this transformation, the distinction between cloud computing and edge computing becomes increasingly critical, signaling the need for a more integrated approach.
The need for such a shift is underscored by the projected growth in enterprise edge infrastructure spending, estimated to reach $57.9 billion by 2026, growing at a compound annual growth rate of 22.3%. This contrasts sharply with the more moderate growth in core infrastructure spending, which is slowing to a CAGR of 6.0%. These figures aren’t just numbers; they represent a fundamental reevaluation of where and how we deploy computing power.
Modern applications – from multiplayer gaming and streaming services to AI-driven analytics – are pushing the boundaries of what’s possible, driving the need for an edge development platform that simplifies app infrastructure complexity. By moving computing closer to the edge of the network, businesses can enhance performance, adhere to data compliance regulations more effectively, and reduce infrastructure costs, maintaining competitiveness in fast-changing markets.
Nearly two decades ago, cloud companies invested massive amounts of capital to build centralized data centers to enable massive scale. Next, cloud computing streamlined and accelerated value creation for businesses going from monolithic applications to microservices. Today, those same companies are pouring capital onto the fires of AI. But for all of the power and promise of AI, value creation and realization is happening at the edge-where the users and devices are. Businesses and their developers need a way to capitalize on the enormous potential that connected vehicles, augmented reality, and interactive media experiences represent, which necessitates a shift from cloud microservices to an edge-native architecture.
Cloud native tools and the CNCF community have done a fantastic job of empowering developers to create these applications, but the infrastructure underpinning them struggles to provide the responsiveness and reliability that users demand. Cloud service providers are attempting to close the gap by forging new relationships with network providers, but the build-outs are slow, fraught with challenges, and result in complex architectures that are difficult and massively expensive to deploy and manage at scale. It’s a frantic attempt to retrofit an old architecture to support an entirely different use case. The growth of AI inference at the edge, for example, is a testament to the potential of a more distributed cloud computing model to power generative AI tools at a global scale, enabling businesses to leverage large language models more efficiently. This signals the need for an edge-native platform built for today’s challenges to complement and extend the cloud computing platforms that addressed yesterday’s headaches.
However, the journey to a truly integrated cloud-edge ecosystem is not without its challenges. The old cloud model emphasized scale-up compute power at the expense of deployment reach. Smaller edge and CDN providers focused on scale-out reach, but they did this by giving up compute power. To achieve the application performance end users demand, developers need to move workloads closer to their users, and the old cloud model struggles to deliver. Typically confined to centralized data centers, that model is difficult to move close enough to the edge to meet customer needs. This dichotomy has led to a fragmented landscape, where developers must choose between building for the cloud or for the edge.
Convergence is necessary in order to unlock opportunities and let developers more easily innovate. To bring full-stack computing to hundreds of locations previously unreachable, generalized compute must be deployable on top of existing worldwide edge networks while taking advantage of existing tools, processes, and observability to provide a consistent experience from cloud to edge.
The concept of edge-native application development represents a breakthrough in this regard. Edge-native applications, optimized for field use and designed with resilience, mobility, and security in mind, herald a new era of computing. They promise reduced latency, optimized bandwidth usage, and the flexibility to control data localization, all while offering unprecedented distribution opportunities and cost savings on cloud networking.
As we embrace this emerging architectural pattern, it’s clear that the future of cloud computing lies in the convergence of cloud and edge. This convergence enables developers to leverage cloud computing capabilities in previously unreachable locations, fostering innovation across the entire compute continuum. By moving beyond the limitations of the traditional, centralized cloud model, we unlock the potential for a more distributed, agile, and scalable infrastructure.
It’s not just about bridging the gap between cloud and edge; it’s about redefining the landscape of cloud computing to better meet the needs of today’s applications and pave the way for tomorrow’s innovations.
The evolving needs of customers are steering us towards a more interconnected infrastructure, where scale is measured in reach, not just data center square footage. This transition reflects a profound shift from legacy to modern cloud design, acknowledging that the original scale-up model is ill-equipped for the demands of the next phase in cloud computing.
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ABOUT THE AUTHOR
Ari Weil is a hands-on, results-focused, growth-oriented marketing leader with a proven track record for launching successful Enterprise software products in the market from initial concept, market positioning, field training and execution and customer adoption. His experience spans public and private companies across various management and operational roles that require deep domain expertise, working with field teams, customers, and provide the leadership to enable and drive teams. His specialties are GTM strategy and planning, field enablement, pipeline generation, product strategy and management.
