Large Language Models (LLMs) are increasingly used across various applications, but self-hosting them can significantly enhance control, privacy, and customization. While many still rely on external providers, potential concerns over downtime and data privacy must be addressed. A self-hosted LLM allows businesses to fine-tune models according to their needs. The article discusses building an LLM inference system, outlining challenges related to architecture design, routing, and microservices. Despite operating on a modest budget with a small team, the project successfully built a reliable and efficient system, highlighting lessons learned in the process.
Large Language Models (LLMs) enable businesses to create tailored applications, but self-hosting them raises complexity—especially regarding privacy and control.
Collection
[
|
...
]