Serverless computing in practice: When is the serverless principle deployed?

Serverless computing is primarily used for transient data exchanges by web and business applications in the cloud. In practice, the aim is not to process entire applications or extensive sequences of code (serverless architecture is entirely unsuited for that purpose), but to process any number of individual functions. That makes the approach interesting for several scenarios, as illustrated by the following list:

  • API proxy: Many legacy business applications have complex, unwieldy APIs (software interfaces). With serverless architecture and the right API gateway, an alternative level of abstraction can be generated to allow these applications to be addressed via a [REST API] making them easier to access for other systems.
  • Serverless backend: More and more companies are using serverless computing to build and run the entire backend for applications in the cloud. These scenarios are generally called backend-as-a-service (BaaS).
  • Processing (un)structured data: The modern business world is inconceivable without [Big Data. Serverless infrastructure is proving to be a powerful tool for processing big data, i.e. structured data (JSON, XML, etc.) or unstructured data (images, audio, etc.), including transcoding, moving, combining or manipulating.
  • Running scheduled tasks: In most cases, functions are executed not only based on events, but also based on a defined schedule. For example, you can clean up databases or auto-generate backups.
  • Implementing language assistants and chatbots: Serverless technology is ideal for integrating digital language assistants and chatbots.