Pros and cons of microservices in genAI systems

"By breaking down monolithic AI applications into modular, independently deployable services, organizations can potentially achieve greater agility, scalability, and system resilience. This decomposed approach means each part of a generative AI system-whether data ingestion, model inference, orchestration, or post-processing-can be developed, deployed, and scaled separately. This modularity is especially appealing in a field where models, data sources, and demands change quickly."

"The corresponding surge in generative AI adoption has sparked heated debates about the most effective architectural patterns. Microservices are a popular new solution that is often assumed to be a natural fit for these cutting-edge platforms. Their appeal is obvious at first glance. However, digging into the costs, complexity, and long-term benefits is key to uncovering when microservices empower breakthrough value and when they risk draining more than they deliver."

"According to the first nationally representative US survey of generative AI adoption at work and at home, nearly 40% of the U.S. population aged 18 to 64 now uses generative AI. The survey was published by the National Bureau of Economic Research and found that 24% of workers used it at least once during the week preceding the survey. The adoption of generative AI in the workplace has been as rapid as the personal computer,"

Generative AI adoption has surged rapidly, with widespread personal and workplace use. Decomposing monolithic AI systems into microservices can enable independent development, deployment, and scaling of components such as data ingestion, model inference, orchestration, and post-processing. That modularity can improve agility, scalability, and resilience in environments with rapidly changing models and data. However, microservices bring higher operational complexity, integration overhead, and long-term costs. Starting with a monolith is often faster and cheaper. Decisions should prioritize measurable outcomes and long-term cost-benefit tradeoffs rather than following architectural trends alone.

Read at InfoWorld