Hey everyone! 👋 I've been neck-deep in planning a new campaign infrastructure project, and as usual, I found myself spiraling into a classic analysis paralysis over compute options. My marketing automation workflows are getting more complex, and I need a backend that can handle variable loads from our lead forms, scoring engines, and webhook integrations.
I know we often talk about features and cold starts here, but I'm the type who *needs* to see the dollars and cents laid out clearly. So, I built a pretty detailed spreadsheet to model the costs for AWS Lambda, ECS Fargate, and good old EC2 for a set of predictable and bursty workloads. I focused on the kind of traffic patterns we see in martech—think steady-state processing of overnight batch jobs, with unpredictable spikes during a big webinar or product launch.
Here’s a breakdown of what I compared in my model:
* **Workload Profiles:** I created three scenarios: a low-volume, consistent batch job (like a daily sync); a medium-volume service with daily peaks (like lead routing); and a spiky, event-driven workload (like processing webinar registrations).
* **Cost Components:** I went beyond just compute. I factored in:
* Compute time (GB-hours, vCPU-hours)
* Memory allocation (this is huge for Lambda!)
* Provisioned Concurrency (for Lambda, to combat cold starts on critical paths)
* Load Balancer costs (for ECS & EC2)
* Estimated data transfer
* Even a tiny slice of the DevOps time premium for managing EC2 instances versus serverless.
* **The "Sweet Spot" Analysis:** My goal was to find the crossover points. For example, at what request volume or duration does a constantly running Fargate task become cheaper than millions of Lambda invocations? When does it make sense to just spin up a dedicated EC2 instance for a always-on API that serves our landing pages?
My initial findings were fascinating, though not entirely surprising. Lambda absolutely crushed it for the truly sporadic, short-duration tasks. But for our core, always-on marketing automation listener that handles constant webhook traffic from our CRM, the Fargate option started looking more economical past a certain threshold. EC2, as expected, was the baseline—cheaper for predictable, heavy loads if you have the team to manage it.
I'd love to get your thoughts, especially if you've run similar comparisons for your notification systems or API endpoints. Has anyone else modeled the cost of Provisioned Concurrency for Lambda in a production martech context? Or found a clever way to mix these services (like using Lambda for event ingestion and Fargate for the heavy processing) that gave you the best of both worlds?
The spreadsheet is a bit of a mess with my notes, but I'm happy to clean up a version and share it if anyone's interested. Just let me know!
Test everything, trust nothing