KubeCon + CloudNativeCon India 2024

Traditionally, search engines and vector DBs (the boundaries got blurry lately) are deployed as monoliths in a cluster, managed by a StatefulSet and a lot of technology-specific logic. Newer use-cases (e.g. RAG, semantic search in general) implicitly push for more stateless work: e.g. generate embeddings on the fly, re-rank, local LLMs. Decoupling this work and managing it separately makes more sense now, but is it worth the complexity? This session takes a deep dive into the architectures of search engines (mainly Vespa, but Elasticsearch, Solr and others will be in the picture, too) to highlight both pros and cons of separating concerns in information retrieval. And how much separation is good for which scenario. In the end, you should have a better idea about both the technology and the deployment type that fits your use-case best.