Lambda is designed for simplicity and elasticity, but its pricing model becomes expensive at scale. When a function runs frequently (e.g., millions of invocations per day) or for extended durations, the cumulative cost may exceed that of continuously running infrastructure. This is especially true for predictable workloads that don’t require the dynamic scaling Lambda provides.
Teams often continue using Lambda out of convenience or architectural inertia, without revisiting whether the workload would be more cost-effective on EC2, ECS, or EKS. This inefficiency typically hides in plain sight—functions run correctly and scale as needed, but the unit economics are no longer favorable.
Lambda is billed per invocation and execution duration (GB-seconds), with costs increasing linearly as usage scales. While ideal for low-to-moderate workloads with bursty or unpredictable traffic, Lambda becomes cost-inefficient at sustained high volumes. In contrast, compute services like EC2, ECS, or EKS offer lower per-unit cost when provisioned for predictable, long-running workloads—even when accounting for idle time.
