Why Traditional Cloud Services Can’t Handle the Load of AI Agents

Traditional cloud infrastructure was designed based on the principle “one application for many users”. The implementation of microservices orchestration systems, like Kubernetes, allowed optimization where a single service consistently handles thousands of requests. However, the agents’ architecture completely disrupts this paradigm, rigidly demanding an individual execution environment where a large language model dynamically adjusts its actions. Extrapolating this approach to real-world scales shows a critical shortage of computational resources.

According to analysts, to ensure personal assistants operate for just 100 million workers with 15% concurrent access, approximately 24 million parallel sessions would be required, demanding between 500 thousand to a million server processors. The standard approach of deploying a separate container for each task becomes economically and technically inefficient, as containers load a heavy toolset each time regardless of the operation’s scope.

The resolution of limited resource issues is increasingly associated with the transition to serverless computing based on isolates. The company Cloudflare offers a separation model that can be explained through a culinary analogy: if containers resemble a restaurant kitchen with a fixed menu, the agent acts as a personal chef selecting unique tools for each individual dish.

Isolates create a lightweight, strictly isolated space for code execution, which deploys in milliseconds. They consume only a few megabytes of memory and are automatically destroyed immediately after execution completes. As a result, the speed of environment initialization can increase approximately 100 times, and memory usage efficiency shows global improvements.

It is the transition to an isolate architecture that makes the unit economics of scaling autonomous systems practically viable for business.

During the testing phase of new systems, developers often use headless browsers to access websites that were initially intended for humans. However, for stable operation of autonomous AI, structured machine protocols are needed, such as Model Context Protocol (MCP), which allow programs to directly find and use the necessary services. In this framework, classical methods of verifying traffic via CAPTCHA or behavioral analysis completely lose their meaning.

Since the request is generated by an authorized program, the priority becomes micro-management of access rights based on the principle of Zero Trust. Security must now function as a unified environment with the development platform, where protection against prompt injections or unauthorized access to corporate APIs is built directly into the execution core.

The practical application of agent architectures today already proves the potential for automating complex corporate processes. Infrastructure engineers were the first to test these scenarios by creating specialized agents with access to file systems, git repositories, and code deployment pipelines. For such specific computational tasks, developers leave optimized container sandboxes, supporting the hybrid nature of IT systems.

Another important scenario is automation of customer support: a corporate agent can independently make several API requests to the internal database, check the user’s inquiry history, and provide a comprehensive response based on the approved logic. In this case, the isolate architecture allows the tasks to be performed and instantly frees up the server’s computing power.

Any technological transformation includes a transition phase where new approaches are integrated into existing systems. The traditional web services economy relies on user attention—through ads or subscriptions. AI agents operate differently: they don’t respond to marketing and don’t click banners.

This creates a clear need for native micropayment mechanisms designed for machine-to-machine interaction. The x402 Foundation was established to address this gap by reviving and standardizing the HTTP 402 protocol. The idea is to enable algorithms to automatically pay for access to services or consumed content.

With organizations like the Linux Foundation, IETF, and AAIF joining the initiative, the industry is starting to align around a shared set of interaction rules.

The shift toward autonomous AI requires a different approach to infrastructure. Companies need to move away from resource-heavy models and adopt more flexible architectures based on isolates, machine-oriented protocols, and Zero Trust principles applied at the level of individual micro-processes.

In this environment, the advantage will go to businesses that adapt their infrastructure early to meet new requirements for security and performance.

iIT Distribution, as a Value Added Distributor of advanced cybersecurity solutions, provides the expertise needed to design next-generation infrastructure. The iITD team supports partners throughout the entire project lifecycle—from assessing existing systems to implementing Zero Trust architectures and integrating solutions from leading global vendors, including Cloudflare.

Through technical consulting, a strong understanding of emerging industry standards, and hands-on support, iIT Distribution helps Ukrainian companies build resilient digital environments ready for secure automation.