Why AWS Lambda Pricing Has to Change for the Enterprise

Why AWS Lambda Pricing Has to Change for the Enterprise

The advantages start to disappear quickly when AWS Lambda is employed for batch processing. Enterprises can gain significantly from the scalability of FaaS - yet a price comparison between EC2, Lambda, and Fargate, the AWS-managed container service, reveals an ugly truth.

  • AWS Lambda supports 10GB of RAM and Container Images up to 10GB. This makes it comparable to container services like AWS ECS or Fargate.
  • For 2 CPUs and 4GB of RAM, AWS Lambda pricing per hour/unit is approximately 7.5 times greater than AWS Fargate Spot.
  • Enterprise batch processing workloads, such as financial modeling, require the capability to burst into 1000's of containers for daily processing.
  • Lambda can scale to 1500 containers in a second. With AWS Fargate, this can take up to 1 hour.
  • Selecting AWS Lambda for development, test, and production workloads will be challenging for enterprises performing batch processing. A cost comparison will lead customers to choose other services and lose out on Lambda's scalability and integrations.

AWS Lambda is, contrary to popular belief, ideally suited for many enterprise batch workloads like financial modelling, machine learning and big data processing. At scale, a cost comparison with instance or container-based platforms reveals that Lambda pricing and batch processing are not a perfect fit. If cost deters enterprise teams from adoption of serverless, an opportunity to increase agility and productivity is missed. In this article, I'll share thoughts on cost management and some stark pricing data.

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