From Cloud First to Cloud Fit: Rethinking Where Workloads Belong
Induprakas “Indu” Keri explores why organizations are increasingly shifting from a cloud-first mindset to a cloud-fit strategy as containerized applications mature.
Indu’s take is simple: the public cloud is fantastic when you’re still figuring things out. Early in an application’s life—product-market fit, rapid experimentation, the “I need five servers and I need them now” phase—cloud wins because speed and elasticity matter more than anything else. Same thing when you hit the growth curve and need to scale fast.
But then reality shows up. Many containerized and modernized apps eventually settle into something closer to steady-state. And once usage becomes predictable, the tradeoffs get louder: cost, long-term contracts, data gravity, and the uncomfortable realization that “elasticity” doesn’t always shrink back down the way the slide decks promised.
That’s where Indu introduces the idea that sticks: cloud-fit. Not “cloud first because we want to be cool,” but “cloud where it makes sense, and somewhere else when it doesn’t.” He even puts it in everyday terms: renting a different car every day is fun when you’re experimenting—but if you’re driving for the next seven years, you probably buy something once you know what you actually want.
They also underscore that it’s not compute, it’s data. You can restart containers anywhere. Moving the data—and keeping it available when things go sideways—is what separates theory from operations.
And finally, the lesson most teams learn late: portability isn’t something you bolt on when you’re already stuck. You design for it up front… or you end up dying on the only hill you knew.
