Zero To Hero: Building a Developer-First Search Experience With OpenSearch
summary
A developer-centric documentation search platform that ingests repos, logs, commits and code snippets, applies language-aware parsers and custom code analyzers (preserving casing, camel/snake handling), stores KNN vector embeddings in OpenSearch for semantic code search, and runs an NLP query-understanding pipeline that classifies errors, APIs and intent. Ranking favors documents with code and recent commits, supports real-time or batch ingest, and reports a concrete 40% improvement in search success rate, demonstrating the approach meaningfully improves developer findability.
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chapters (10)
- 0:00Introduction
- 1:04Developer pain points
- 3:37Developer-first search goal
- 4:18Why OpenSearch
- 5:45Project architecture
- 7:09Ingestion pipeline
- 10:40Custom analyzers
- 12:53Semantic code search
- 14:25Developer intent with NLP
- 16:56Key takeaways and conclusion
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