Sharding 2.0: Unlocking Infinite Search Scalability in OpenSearch

Sharding 2.0: Unlocking Infinite Search Scalability in OpenSearch - Vikas Bansal & Paras Jain, Amazon Web Services Search systems are hitting a wall. Static sharding causes hotspots, slow queries, and costly overprovisioning. But what if your search infrastructure could evolve in real time—splitting, scaling, and optimizing itself on the fly? We present a cutting-edge dynamic shard topology in OpenSearch that redefines how scalability and search efficiency coexist. Inspired by distributed systems principles and real-world cloud constraints, this architecture uses a root-child shard model with mutually exclusive hash ranges to enable conflict-free, high-throughput ingestion and ultra-fast targeted search. But we didn’t stop there. We embedded a playoff-style lookup algorithm—a smarter alternative to brute-force fan-out—ensuring queries scale logarithmically, not linearly. The result? 🔹 True infinite horizontal scalability without reindexing. 🔹 Near-zero latency lookups, even during shard splits. 🔹 Elastic, self-healing architecture balancing cost, performance, and reliability. This isn’t a prototype. It’s cloud-native and production-ready. If you’re building systems at scale—or aiming to—this session will change how you think about search.