What are the advantages and disadvantages of microservices in generative AI systems? 2025 Update
Hi, I'm Jon. Today, in this blog, which aims to provide a simple introduction to the world of AI and technology, I'll be talking about "microservices," a concept used in generative AI systems. Generative AI is an AI technology that automatically creates text and images—think ChatGPT. Microservices, on the other hand, are a method of creating large systems by dividing them into small, independent components (services). I'll explain the advantages and disadvantages of incorporating microservices into generative AI, including the latest trends for 2025, in a way that's easy to understand even for beginners. Whenever I encounter technical terms, I'll provide a brief explanation.
Recommended for those who want to start automating with no coding!
With Make.com (formerly Integromat)...
📌 Integrate major tools like email, Slack, Google Sheets, and Notion all at once
📌 Automate complex tasks with just drag and drop
📌 A free plan is also available, so you can try it out for yourself.
If you're interested, here's the details:
What is Make.com (formerly Integromat)? How to Use It, Pricing, Reviews, and Latest Information [2025 Edition]
What are microservices? A basic explanation of their relationship with generative AI systems
First, let's briefly explain microservices. In traditional system development, everything was created as one large program (monolithic architecture), but microservices divide it into small, independent services, each of which operates independently. For example, in the case of an online shop, product search, payment, and delivery management would be treated as separate services. This makes it easier to make changes to the system, and even if a problem occurs, it is less likely to affect the entire system.
Microservices are particularly noteworthy in generative AI systems. Because generative AI processes large amounts of data and returns responses in real time, the systems can easily become complex. As of 2025, an Infoworld article (latest version as of 2025) points out that converting generative AI into microservices improves scalability (the ability to easily expand a system significantly). For example, by separating the text generation and image generation parts of the AI into separate services, each can be improved independently.
A recent trend reported by the AI Front Trends report published in September 2025 is the rapid increase in generative AI services and the use of microservice-based tools in business settings. For example, text-generative AI tools like ChatGPT are often incorporated as microservices to improve business efficiency. Octoparse's March 2025 article also introduced 31 generative AI tools, highlighting the fact that many of these tools use microservice architectures for increased flexibility.
Here, we recommend "Gamma" as the latest generative AI tool. This tool uses AI to instantly create documents, slides, and websites, and its efficient design, which takes advantage of a microservice-like modular structure, is appealing. For more information,This articleWe explain this in detail, so if you're interested, please check it out.
The benefits of using microservices in generative AI systems
Let's take a look at some specific benefits. I'll summarize them based on facts from an article in Infoworld in 2025. You'll understand why microservices are a good match for the characteristics of generative AI.
- Increased scalabilityGenerative AI can become overloaded when the number of users increases rapidly, but with microservices, it's easy to scale up just the parts you need. For example, you can simply add servers to strengthen just the text generation service. According to a survey by MM Research Institute in August 2025, the number of individual users of generative AI is estimated to reach 1,597 million, with the market size reaching 1,679 billion yen. This is the kind of scale we need.
- Flexibility and ModularityBecause each service is independent, updating one AI function doesn't affect the rest. For example, updating the image generation AI algorithm doesn't stop other parts from working. A February 2025 article by Nippon Printing Publishing noted that many free generative AI tools use this modular structure, making them easy to use even for beginners.
- Accelerating development speed: Each service can be developed by a small team, resulting in faster overall releases. The August 2025 report from Kigyo Techo compared 16 generative AI tools by purpose, and cited examples of how microservice-based tools contribute to business efficiency.
- Fault toleranceEven if one service goes down, other services continue to operate, making it difficult for the entire system to come to a halt. A September 2025 article in BIZ ROAD, featuring nine examples of companies implementing generative AI, explains how this fault tolerance is enabling business transformation.
These benefits are supported by the latest information for 2025. For example, in the X (formerly Twitter) trends, posts are showing the continued growth of generative AI and how architectures like microservices are being used in practice as "unobtrusive AI" (a way to improve existing functionality in an unobtrusive way), making generative AI more easily integrated into everyday work.
The benefits of the latest case studies in 2025
An October 2025 Nikkei xTECH article reported that more than half of companies expect to increase revenue by introducing generative AI, and that microservices are helping with reassignment and work efficiency. A September 2025 survey by Web Manager Forum also found that generative AI is being used in a variety of settings, including work and school, with tools like Grok being used in personal life and Copilot being used in business. These tools are based on microservices and offer flexible operation tailored to time, place, and occasion (TPO).
The drawbacks of using microservices in generative AI systems
However, there are drawbacks, which the Infoworld article clearly points out, and which are important to be aware of before adopting them: Microservices can add additional complexity to generative AI.
- Increased complexity: The more services you have, the harder it becomes to manage them. Communication overhead (extra processing) occurs, making overall design difficult. This may be especially difficult for beginners.
- Possible delays: As data exchange between services increases, response times can slow down. This is a major problem when real-time performance is required, such as with generative AI. According to a September 2025 survey by MM Research Institute, 21.8% of users use free services, but there is a trend toward charging for paid services to address these delays.
- Security ChallengesBecause each service is independent, security holes are more likely to occur, increasing the risk of data leaks. A September 2025 article in Kodomo to IT noted that while awareness of generative AI exceeds 80%, whether or not there is a fee for use affects adoption, and calls for improved security awareness.
- Increasing operational costs: Initial investment and maintenance costs are high. This can be a burden for small and medium-sized businesses. In X's trending posts, as the use of generative AI as a side business increases, there is discussion about finding solutions to these operational issues by creating "microapps."
These drawbacks are also highlighted in news reports from 2025. For example, a September 2025 press release from the Nihon Keizai Shimbun noted that while free services are the norm for personal use of generative AI, there is a possibility that a shift to paid versions will occur due to their complexity. Furthermore, there are also many voices in X stating that, without proper management, issues regarding copyright and terms of use will remain.
Tips to minimize drawbacks
To reduce drawbacks, start small. Refer to official announcements and guidelines from specialized media outlets to choose a reliable tool. These tips are explained in detail on a website introducing the latest generative AI tools in 2025.
Summary: Generative AI and the Future of Microservices
Introducing microservices into generative AI systems greatly improves scalability and flexibility, but also brings challenges of complexity and cost. Trends for 2025 show increased use by businesses and individuals and improved business efficiency, but it is important to carefully consider the advantages and disadvantages before adopting them.
If you're interested in tools that utilize generative AI, we recommend Gamma. It's a new standard for creating documents with ease using AI. For more information,This article .
To sum up, Jon says that microservices are a powerful tool for maximizing the potential of generative AI, but beginners should start by trying out free generative AI services. With technology evolving so rapidly, it's important to learn from trusted sources. I hope this article enriches your AI life!
Reference sources
- Infoworld: https://www.infoworld.com/article/4068388/pros-and-cons-of-microservices-in-genai-systems.html (Article as of 2025)
- AI Front Trend: https://ai-front-trend.jp/ai-service/ (released February 17, 2025)
- Octoparse: https://www.octoparse.jp/blog/top-25-artificial-intelligenceai-tools-for-2023 (released March 17, 2025)
- Japan Printing Publishing Co., Ltd.: https://jpp.co.jp/2025-ai-recommendation-10/ (Published February 13, 2025)
- Entrepreneurial Notebook: https://sogyotecho.jp/generation-ai-service/ (released August 12, 2025)
- BIZ ROAD: https://bizroad-svc.com/blog/seisei-ai-kigyou/ (released on September 1, 2025)
- Nikkei xTECH: https://xtech.nikkei.com/atcl/nxt/mag/nc/18/020800017/092501324 (1 week ago, around October 2025)
- Web Manager Forum: https://webtan.impress.co.jp/n/2025/09/25/50092 (2 weeks ago, around September 2025)
- MM Research Institute: https://nikkei.com/article/DGXZRSP696884_X10C25A9000000 (3 weeks ago, September 17, 2025)
- Children and IT: https://edu.watch.impress.co.jp/docs/news/2048145.html (3 weeks ago, around September 2025)
- MM Research Institute, Inc.: https://m2ri.jp/release/detail.html?id=691 (3 weeks ago, August 2025 survey)
- Related trending posts on X (formerly Twitter) (based on the 2024-2025 generative AI discussion)