Elasticsearch Deep Dive for System Design Interviews
When a system design problem involves search, Elasticsearch is often the first technology that comes up. From powering e-commerce product search to aggregating billions of log events, Elasticsearch has become the default choice for search-heavy applications.
But knowing that Elasticsearch exists is not enough. Interviewers want to see that you understand when it makes sense (and when it does not), how its distributed architecture works under the hood, and what trade-offs you are making by choosing it. This deeper understanding separates candidates who can recite features from those who can actually design systems.
This chapter covers the practical knowledge you need: core concepts like inverted indexes and mappings, cluster architecture and shard distribution, query optimization patterns, and scaling strategies for both reads and writes.
By the end, you will be able to confidently propose Elasticsearch when appropriate, design efficient schemas and queries, and discuss its limitations honestly.