Serverless Computing: When Ditching Servers Pays Off
Serverless computing can significantly reduce infrastructure overhead. However, it is not a one-size-fits-all solution.
Key points: Serverless technology drastically reduces infrastructure overhead but is not a panacea. Understand its strengths and limitations.
No server management, automatic scaling, pay-per-use. After five years of practical experience, a nuanced picture emerges.
From Lambda Hype to Pragmatic Use
Experienced teams are using serverless technology for event-driven workloads, variable APIs, and data processing pipelines. Container alternatives like Fargate and Cloud Run offer a middle ground.
Cost Transparency
100 Requests per Minute: Lambda costs a few Euros, EC2 at least 30 Euros. But under constant high load, Lambda is three times more expensive than EC2. Cost threshold at 30-40% utilization.
Cold Starts, Lock-in, and Pain Points
Provisioned Concurrency helps. Lock-in is stronger than with containers: Lambda with DynamoDB and SQS is not portable. Debugging is more complex. 15-minute limit.
Patterns that work
Event-Driven Processing: S3 upload triggers Lambda. API Gateway for variable REST APIs. Scheduled jobs. Step Functions for workflow orchestration.
Serverless is not a dogma, but a tool. The art lies in choosing the right one.
Frequently Asked Questions
Serverless or Containers?
Serverless for variable loads. Containers for constant loads. Often both are combined.
Avoiding lock-in?
Encapsulate business logic independently of the framework. Use the serverless framework as an abstraction layer. Functions under 100 lines of code.
For Startups?
Ideal. Pay-per-use, automatic scaling, no infrastructure management.
Translated from the German original using artificial intelligence. The German version is authoritative.
