Extract data from Amazon Aurora MySQL to Amazon S3 Tables in Apache Iceberg format

AWS is finally making it frictionless to move transactional data from Aurora MySQL into a lakehouse-native format, and that's a meaningful shift in how we should think about data architecture. What strikes me is the pairing of Aurora Serverless v2 with S3 Tables in Iceberg format—this removes two major pain points simultaneously: you're not managing database capacity, and you're landing data in an open format that doesn't lock you into proprietary tooling. From an operational standpoint, this means fewer custom scripts, less Lambda sprawl, and better governance through Iceberg's ACID guarantees and schema evolution. The real implication is that smaller teams can now build reliable medallion architectures without hiring DevOps specialists. However, I'd push back on assuming Glue alone scales gracefully for high-volume incremental extracts—you'll want to validate partition strategies and change data capture patterns before committing to production. The broader trend here is clear: cloud providers are abstracting away infrastructure complexity, which means our value shifts from plumbing to design. Start experimenting with this pattern if you're already running Aurora, but treat it as one tool in your extraction toolkit, not a silver bullet.