The cloud infrastructure tax ISVs are paying without noticing

‍Every hyperscaler invoice contains a line item that most ISV teams have accepted as the cost of doing business: egress fees.

Data moving out of AWS, Azure, or GCP to the internet, to users, to partners, or to on-premises systems carries a charge of $0.08–0.12 per GB, depending on region and destination.

A SaaS exporting 50 GB of data daily, not unusual for a mid-size analytics platform, pays approximately $180 per month in egress charges for that single workflow alone. Multiply that across API responses, report delivery, user uploads, backup jobs, and multi-region replication, and egress becomes a recurring five or six-figure annual cost that scales with every new customer onboarded.

Most ISVs pay this infrastructure tax simply because hyperscalers were the default choice when their architecture was first designed.

Why Hyperscalers became the default

AWS, Azure, and GCP earned their dominance. They offer the broadest service catalogues in cloud computing, the most mature managed services, and the largest developer ecosystems.

For ISVs building on machine learning pipelines, managed databases, or serverless functions tied to specific provider APIs, hyperscaler infrastructure is often the right foundation.

But "broadest catalogue" is not the same as "most cost-efficient for your workload." The hyperscaler business model is built around managed service upsell and infrastructure lock-in.

Egress pricing is a retention mechanism. The more deeply an ISV integrates proprietary services, the more expensive migration becomes, and the less price-sensitive the customer is at renewal.

AWS Reserved Instances save up to 75% but require one to three-year upfront commitments. GCP Committed Use Discounts save up to 57% but cannot be cancelled. Azure Reservations require a fee to modify. For ISVs whose infrastructure needs scale with product growth, locking capacity 12–36 months ahead introduces financial risk alongside cost savings.

How is Akamai Cloud different from hyperscalers

Most cloud providers built a network on top of data centres. Akamai built a cloud on top of a network.

That distinction is actually architectural, not marketing talk.

Akamai's edge network spans more than 4,400 points of presence globally, built over 25 years of operating the internet's largest content delivery infrastructure. When Akamai acquired Linode in 2022 and launched Akamai Connected Cloud in 2023, it did not add cloud to a CDN company. It added cloud computing to a global network that already moved a significant fraction of internet traffic.

The practical consequence for ISVs is egress pricing. Akamai can apply CDN-like economics to cloud data transfer, meaning egress costs that are significantly lower than hyperscaler equivalents.

Beyond egress, the network-first architecture provides latency advantages that centralised hyperscaler data centres cannot replicate. Compute at the edge means processing happens closer to users, reducing round-trip times for applications where latency matters.

The AI inference opportunity for ISVs

As AI shifts from experimental to operational, from model training to real-time production, the economics of where inference runs become a direct product cost.

Against traditional hyperscale infrastructure, Akamai Inference Cloud delivers:

• 3× better throughput, more inference requests per GPU per second
• 60% lower latency, critical for real-time AI features (live video, personalisation, decision engines)
• 86% lower cost, the difference between AI being an expensive experiment and a sustainable product feature

For ISVs building AI-powered features, this cost is the difference between an AI feature that compresses margin and one that does not.

Harmonic is using Akamai Inference Cloud to deliver ultra-high resolution 8K multi-language video. Monks is processing real-time multi-camera live sports feeds, identifying players, generating play summaries, and delivering coaching insights during live matches.

The performance is only possible by running inference at the edge, where round-trip latency to centralised data centres would make real-time processing impossible.

What the numbers look like in practice

An AI analytics platform migrated to Akamai Connected Cloud achieved 35%+ reduction in monthly infrastructure costs while maintaining identical performance benchmarks. The workload required compute, storage, networking, and standards-compliant Kubernetes.

Akamai provided all at a lower cost than the hyperscaler equivalent, without proprietary service dependencies that would have required rewriting application code.

The migration itself followed a workload-first assessment where we identified which components relied on hyperscaler-specific services, which could migrate to open-standard equivalents, and which required architectural changes. The migration took 8 weeks and the payback was immediate.

If you’re assessing a similar migration, look at high migration value, meaning compute-intensive workloads (AI inference, video processing, data pipelines), high-egress applications (CDN-adjacent delivery, analytics exports, API-heavy SaaS), and Kubernetes workloads with no proprietary service dependencies.

We believe the answer is not "Akamai for everything." It is "Akamai for the workloads where its architecture and economics are the right fit." For high-egress SaaS and AI-inference-heavy products, that fit is increasingly clear.

The margin question for ISVs and

The SaaS competition is intensifying. ISVs cannot afford infrastructure costs that scale faster than revenue.

Hyperscaler infrastructure was the right default when it was the only credible option. In 2026, Akamai Connected Cloud offers ISVs a production-grade alternative with network-native edge delivery, significantly lower egress costs, competitive Kubernetes infrastructure, and an AI inference platform that changes the economics of running AI in production.

The ISVs who evaluate these options now, before their next contract cycle, before their AI inference costs become significant, before their architecture becomes more deeply entangled with proprietary services, will have the most options.

If you want to check if Akamai Cloud is right for you, send us a message at https://www.maximaconsulting.com/contact-us