5 posts tagged with "search"

Standing up a search stack usually starts the same way every time. Provision an OpenSearch cluster. Stand up Dashboards next to it. Wire Dashboards to the cluster with an endpoint and credentials you paste into a config file. Make sure the security plugin lets the two talk. Decide where Dashboards keeps its saved objects. Only then do you get to the part you actually wanted: indexing data and running a query.

The Launch a search workspace stack collapses that into one button. You get a managed OpenSearch cluster and a full OpenSearch Dashboards workspace, attached and EU-resident, in minutes, with nothing to wire by hand.

The analyzer you assign to a field determines how text is broken into tokens at index time and at query time. Choosing the wrong one produces surprising results: searches that miss obvious matches, or matches that should not have ranked at all. This post compares the built-in English and standard analyzers, then builds a custom analyzer with synonym support.

All examples were tested against OpenSearch 2.19.1 on FoundryDB staging.

With your OpenSearch cluster running on FoundryDB, the next step is putting data into it and querying it. This post covers explicit index mappings, the bulk ingestion API, full-text search with relevance scoring, fuzzy matching, bool queries, and aggregations.

All results are from real queries run against OpenSearch 2.19.1 on FoundryDB staging. Replace YOUR_HOST and YOUR_DB_PASSWORD with your cluster values throughout.

FoundryDB manages the full lifecycle of OpenSearch: VM provisioning, TLS certificates, DNS, and credentials. You get a production-ready cluster endpoint in about 6 minutes. This post covers provisioning via the API, fetching credentials, verifying TLS, and confirming cluster health.

All examples use confirmed output from OpenSearch 2.19.1 running on FoundryDB staging.

Every application eventually outgrows LIKE '%query%'. Once your product catalog, help center, or log pipeline crosses a few million documents, you need an inverted index, not a sequential scan. OpenSearch provides exactly that: full-text search with relevance scoring, custom analyzers, aggregations, and a visualization layer built in.

The hard part is running it. JVM heap tuning, cluster formation, TLS certificate management, shard rebalancing, and snapshot configuration turn a "quick search feature" into a permanent ops project. FoundryDB removes all of that. You get a managed OpenSearch 2.19 cluster with TLS, authentication, automated snapshots, and monitoring out of the box.

This guide walks through deploying OpenSearch on FoundryDB and building production-quality search: from provisioning to index design, full-text queries, custom analyzers, and aggregations.