What happens when a request hits KServe ?

1. 1Send a request to KServe using the KServe API
2. 2Configure the KServe ingress to receive the request
3. 3Test the request flow using a sample LLM model
4. 4Apply logging and monitoring to track the request journey
5. 5Compare the performance of different LLM models in KServe

Machine learning engineers and developers working with KServe and LLMs can benefit from understanding the request flow to optimize and troubleshoot their models

💡 Understanding the request flow in KServe is crucial for optimizing and troubleshooting LLM models

💡 Discover the journey of an LLM inference request in KServe #KServe #LLM