In this episode of Cloud Computing with Fexingo, Lucas and Luna explore the often-overlooked cost of cloud provider lock-in — not just the financial cost, but the strategic and operational risks. They dive into a specific case: a mid-sized fintech company that built its entire data pipeline on AWS Glue and Kinesis, only to find migrating to Azure would cost over $2 million and require rewriting 70% of their code. The discussion covers how proprietary services like Amazon DynamoDB, Google Bigtable, and Azure Cosmos DB create dependencies, why the 'lift and shift' myth is dangerous, and practical steps to build a cloud-agnostic architecture without losing performance. Listeners will learn one concrete takeaway: always audit your use of proprietary services before your next cloud negotiation.

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