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Log Analytics in OpenSearch with PPL: Filter, Aggregate, and Correlate

· 5 min read
FoundryDB Team
Engineering @ FoundryDB

OpenSearch SQL is familiar, but Piped Processing Language (PPL) is often better for log analysis: its pipeline syntax maps naturally to how you think about filtering and aggregating event streams. Each | stage narrows or transforms the result set from the previous one. This post runs five PPL queries against a 200-document structured log dataset on a live OpenSearch 2.19.1 cluster managed by FoundryDB. Every number below is from a real query.

All commands use YOUR_OPENSEARCH_HOST and YOUR_PASSWORD as placeholders.

OpenSearch cluster, query fan-out & gather
Cluster green · search fans out to one copy per shard, then gathers
Coordinatorfan-out / gatherquery →Data nodesP0 P1 P2 · R0 R1 R2⇠ hitsCluster-managershard allocation
Cluster-managerCoordinatorData nodePrimary shardReplica shardcluster state / gather (dashed)

Query Your Database in Plain English: FoundryDB's AI Query Console

· 7 min read
FoundryDB Team
Engineering @ FoundryDB

Most database dashboards give you a SQL editor and wish you luck. That works fine when you remember the exact name of the pg_stat_user_tables view or the difference between information_schema.TABLES in MySQL versus PostgreSQL. For everyone else, there is the AI Query Console.

FoundryDB's AI Query Console lets you type a question in plain English, translates it to a database-native SQL query using Claude, and executes it against your running service. The entire flow is read-only by design. You cannot accidentally drop a table by asking a question.

NL2SQL: review before execute, read-only
SAFETY GATE review before execute · read-only
Userasks NL→ schema+question → LLM →Human reviewconfirm ✓→ execute READ-ONLY →Databaserows back
User questionDB schema (context)LLM (Claude)Human review gateRead-only executeResultsschema introspect (dashed)