Platform engineering has unlocked speed, scale, and self-service—but it’s also quietly driving a surge in observability costs that many teams can no longer ignore. As telemetry volumes explode across microservices, edge, and AI workloads, legacy approaches are breaking under the pressure—forcing teams into trade-offs that slow performance, increase risk, and inflate spend.
This session unpacks why observability costs are accelerating faster than infrastructure—and what modern teams are doing to regain control.
What you’ll learn:
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Why observability costs are now a CFO-level concern, not just an engineering problem
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How sampling, tiered storage, and blind spots directly increase downtime and resolution time
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What modern, stream-first architectures do differently to scale visibility without runaway costs
AI, microservices, and edge computing aren’t slowing down—and neither is your telemetry.
Watch now to understand the real cost of observability—and how to build a platform that scales without breaking your budget.
