Five startup lessons for data streaming enterprises
One of the pleasures of running the Confluent for Startups program – which provides early-stage companies with up to a year of Confluent Cloud credits and access to technical mentorship for building real-time data streaming applications – is the opportunity to hear founders articulate their vision while it is still being tested against reality.
Those conversations rarely feel polished. More often, they revolve around what broke, what customers actually wanted, and where the team had unintentionally made life more complicated than it needed to be. What strikes me today is how consistent the underlying questions have become. How do you use AI without creating yet another layer of fragmentation? How do you move quickly without sacrificing reliability, security, or trust? And as startups begin exploring event-driven microservices, how far should they go in balancing the promise of greater scalability and flexibility against the complexity of operating an increasingly distributed system?
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