At KubeCon + CloudNativeCon Europe 2025, Akamai shared insights into its evolving role as a key player in edge computing and modern AI infrastructure. As the operator of the world’s largest edge platform—with over 4,000 global locations and handling 300 million hits per second—Akamai is navigating a strategic transition. Under mounting pressure from margin challenges, the company is doubling down on simplifying edge AI deployment and platform usability for enterprises, while laying the groundwork for long-term consolidation and efficiency across inferencing workloads, software stacks, and hardware.
With its collaboration with Fermyon and recent launches focused on usability, Akamai is moving to make its edge network not just the fastest, but also the most accessible and efficient foundation for modern application delivery.
Rethinking Edge AI: From Brute Force to Smart Efficiency
Akamai’s strategy is grounded in a realistic view of the current state of AI maturity. While many enterprises are allocating large budgets to AI experimentation, the outcomes often lack efficiency or tangible ROI. Today’s AI workloads are frequently overbuilt—relying on expensive GPUs and massive memory configurations when many applications can start with more modest CPU-driven inferencing.
This is where Akamai sees opportunity. With innovations like WebAssembly (WASM), sophisticated AI applications can be deployed in lightweight, secure sandboxes directly at the edge. Instead of moving large datasets to centralized infrastructure, results can be computed at the edge and transmitted efficiently, dramatically reducing latency and cost. This “results over data” approach supports real-time use cases in gaming, media, and personalized services while preserving privacy and responsiveness.
Paradigm Shift: The New AI Stack at the Edge
The edge is no longer just about caching static content or reducing load times. It’s becoming the active execution layer for modern applications, particularly those augmented with AI. Akamai’s conversations with Fermyon reflect this shift, emphasizing secure multitenancy, intelligent routing, and real-time inferencing across thousands of regions.
As one executive put it, “If AI is the new app, then Kubernetes is the new web server.” This paradigm shift introduces complex infrastructure challenges—federation at scale, observability gaps in AI failure modes, and evolving requirements for tracing and monitoring across distributed nodes. Akamai is focused on solving these by investing in simplicity and developer experience.
GitOps, Observability, and Developer Enablement
To support an expanding user base and to reduce the complexity of managing edge deployments, Akamai is enhancing platform usability through GitOps-based workflows, integrated CI/CD pipelines, and native observability tooling (o11y). These tools aim to make the edge feel like a natural extension of existing DevOps practices, enabling faster iteration and more predictable delivery.
The launch of these capabilities near the end of 2024 marked a shift in Akamai’s strategy toward broader platform consumption. The goal is to make it easier for end users—whether developers or DevOps teams—to consume the edge as a service, abstracting away the network and infrastructure layers.
Helping Enterprises Modernize: The 12–18 Month Challenge
CIOs and IT leaders are increasingly driven by modernization agendas, but often face complexity and skill gaps when executing large-scale transformations. Akamai recognizes that successful modernization—especially with AI and edge workloads—typically spans a 12 to 18-month implementation window.
To address this, Akamai advocates for partnerships with service delivery organizations that can accelerate execution, reduce integration risk, and provide the expertise needed to translate high-level goals into technical outcomes. The company’s enterprise customer focus aligns closely with this approach, offering solutions that scale with business needs while ensuring compliance, security, and observability.
Looking Ahead: Consolidation and AI Infrastructure Maturity
Akamai predicts that over the next two to three years, the edge and AI infrastructure space will undergo significant consolidation. Software stacks, hardware requirements, and inferencing patterns will become more streamlined and efficient. As the current brute-force approach to AI gives way to intelligent, right-sized execution, Akamai wants to position itself to lead the transition.
By focusing on performance, usability, and cost-efficiency, Akamai is crafting a vision of the edge where even the most complex AI use cases can run predictably, securely, and at scale—with minimal friction.
Akamai’s edge platform is evolving to meet the demands of modern AI workloads and enterprise modernization strategies. By prioritizing efficient inferencing, developer simplicity, and robust observability, the company is helping customers navigate the challenges of today’s distributed application architectures. With its edge footprint, commitment to usability, and focus on enterprise enablement, Akamai is positioned well in the emerging AI-native internet.
The Cloud Comes Home: Oxide Reimagines On-Prem Computing
Why Enterprise Storage Is Still Stuck in 2010—And How Pure Storage Plans to Fix It
From Chaos to Clarity: HPE’s CloudOps Vision for Hybrid Control
NVIDIA’s Spectrum-X Becomes the Nervous System of Giga-Scale Data Centers
NVIDIA’s Public-Sector Push Turns AI Strategy into National Infrastructure
