"For a decade, AWS's position on multi-cloud was clear: don't. Multi-cloud meant a lowest-common-denominator architecture. Multi-cloud meant giving up the managed services, the security integrations, the features that justified the lock-in. Multi-cloud was for that indecisive tranche of companies that couldn't commit. And until 2019, mentioning other clouds at all was forbidden at AWS conferences. Then in November 2025, AWS launched AWS Interconnect with Google Cloud as a launch partner,"
"AWS has a tell: it markets hardest wherever it's losing. 2017: Machine learning. SageMaker launched with promises to "democratize ML" through "single-click model training." The keynotes were as breathless as they were incomprehensible. Meanwhile, Google's TensorFlow had already become the industry standard, and AWS was playing catch-up with a product most data scientists ignored. AWS trumpeted "250% user growth" the following year - impressive until you realize they were growing from approximately nobody."
AWS opposed multi-cloud for a decade, framing it as a lowest-common-denominator architecture that sacrificed managed services, security integrations, and differentiating features. AWS forbade mentioning other clouds at conferences until 2019. In November 2025 AWS launched AWS Interconnect with Google Cloud, with Microsoft Azure joining in 2026, enabling managed VPC-to-competitor network connections. The launch reflected customers forcing change rather than an ideological shift. AWS tends to market aggressively in areas where it is losing share, illustrated by past pushes around SageMaker in 2017 and the Bedrock AI offering in 2024–25 that faced capacity constraints and customer departures.
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