serverless

Integrating AI agents within serverless architectures offers a modern approach to deploying and executing intelligent applications. Leveraging the advantages of serverless computing, AI agents can dynamically respond to varying workloads without the overhead of managing the underlying infrastructure. This article explores the concept of scalable serverless AI agents in the cloud, detailing their architecture, benefits and drawbacks, challenges, and real-world applications. The paper provides advantages and drawbacks of the serverless approach.

It has been found that achieving high quality indicators, in particular maintainability [1], is becoming an increasing problem due to the emergence of new technologies, in particular cloud technologies and serverless architecture. Despite this, requirements for the level of ease of support are only growing, and this characteristic of software quality is receiving more and more attention.

Cloud computing is emerging as a powerful computing paradigm for the efficient use of resources. However, decisions to move to cloud computing always remain risky from the customer's point of view, considering the benefits they get from it.

Serverless computing is a new and still evolving type of cloud computing, which brings a new approach to the development of information systems. The main idea of serverless is to give an approach of doing computing without dealing with a server to a user. Such approach allows to reduce the cost of the system building and system support. It allows small companies to concentrate on their own system designing instead of thinking about infrastructure building and supporting. Also, a big problem of providing the system security on high level is on cloud’s provider engineering support service.