Does new Google interconnect remain a costly, limited bridge?
This year at re:Invent, AWS seems to have finally accepted the inevitability of multi-cloud with its latest announcement of a jointly engineered interconnect with Google Cloud. It’s a sharp pivot from years of insisting customers didn’t need multi-cloud and of positioning it as unnecessary, prohibitively complex, and essentially a passing fad rather than a strategic architecture.
Year after year, industry reports show that well over 85% of organizations already run workloads across more than one cloud. And now that the world’s largest cloud provider has launched a native, multi-cloud interconnect, it marks a significant moment. Not because AWS is suddenly innovating in networking, but because it acknowledges what the rest of the industry has known for years: multi-cloud is not an odd choice or overly cautious DR — it’s the norm.
It is significant; however, beneath the headlines and hype, this two-cloud bridge is still far too little for the realities of global, enterprise-scale operations. And that’s where the conversation needs to shift now.
To give credit where it’s due, AWS and Google Cloud building a private, high-speed, managed link is definitely useful. It smooths some of the pain that enterprises have endured for years. It promises the ability to spin up multi-cloud connectivity “in minutes”, using click-and-deploy workflows instead of negotiating circuits, ordering hardware, and fiddling with routing for weeks. But the service has one defining limitation: it only connects AWS and Google Cloud at the moment, no Azure, no regional and sovereign clouds.
A bilateral interconnect - even one that’s fast to provision - doesn’t eliminate the hard part: operating a consistent network and governance model across providers, accounts, and regions, and doing it in a way that doesn’t get economically punished by data gravity.
Most enterprises aren’t building one bridge; they’re trying to build a system of roads that spans AWS, Azure, Google Cloud, plus on-prem and edge. Within this system, day-2 operations, policy drift, segmentation, observability, and cost predictability are the real sources of risk and toil.
The second part of the story is often underweighted in hyperscaler announcements but decisive in whether multi-cloud makes it to production. Hand-rolling multi-cloud networking was always possible — slow, complex, and a headache, but possible. If you really wanted AWS talking to Azure, talking to Google Cloud, talking to OVHcloud, you could make it happen.
The real killer, however, has always been the economics — the astronomically high egress fees that make cross-cloud data movement commercially insane. Being “architecturally possible” was always just one piece of the puzzle; “financially sustainable” was the other. Provisioning speed matters, yes, but not if you’re paying hundreds of thousands of dollars a month to move logs, ML datasets, or analytics workloads between clouds.
Until hyperscalers let customers combine native and non-native services without punishing them financially, their multi-cloud solutions will remain partial at best. Currently, the AWS-Google Cloud interconnect doesn’t change that.
What is changing — and what AWS’s announcement quietly validates — is how organizations think about multi-cloud. It’s no longer just about failover or “avoiding lock-in.” It’s about best-of-breed: Google’s AI stack paired with AWS databases, or maybe Azure’s identity integration alongside a sovereign cloud for compliance. Modern architectures increasingly mix and match.
So, interconnects and private lanes matter, only if they scale beyond two providers and don’t blow your budget the moment real data starts moving.
The AWS-Google Cloud announcement hints at a future where clouds interoperate more seamlessly. The vision is good, but connectivity as a native feature rather than a specialized product still means missing out on certain ingredients, like:
These are the parts hyperscalers struggle with, because solving these problems means exposing their operational risks and reducing the structural friction that keeps workloads sticky and revenue predictable.
The vision AWS and Google Cloud are now embracing, however cautiously, is exactly the vision we’ve been building towards at emma from day one. emma’s multi-cloud networking backbone already connects all major hyperscalers, and will expand with new sovereign, region-specific choices in 2026.
And because emma isn’t tied to any one provider, it can do something hyperscalers simply won’t: optimize traffic based on cost, performance, and policy, not vendor incentives. By carrying traffic over its own backbone, the platform can price data transfer at roughly one-third of standard tariff. Organizations have used emma’s intelligent network optimization to reduce egress costs by up to 80%, making previously unaffordable multi-cloud architectures viable at scale. And that includes real workloads, data, and latency requirements.
The AWS multi-cloud interconnect is a meaningful signal, as it validates the future and the direction of the cloud market, However, it remains a narrow, vendor-controlled bridge. Real-world multi-cloud organizations need a global, vendor-agnostic, and economically viable network fabric.
Despite the apparent simplicity of a native offering, specialized providers are already operating in the next phase of multi-cloud: at the very least, a global, three-hyperscaler network fabric paired with a cost structure that doesn’t penalize customers for crossing cloud boundaries. For them, the value proposition isn’t just “interconnect in minutes.” It’s whether the industry can move from pairwise connectivity to repeatable multi-cloud operations with the controls and unit economics that make it sustainable. And that’s what it takes to run multi-cloud in production, not just connect it.
Discover how emma’s networking backbone and centralized control plane is helping organizations survive the operational challenges and economics of multi-cloud: https://www.emma.ms/products/cloud-connectivity
