From 11bce15787aeae723f91849a798f88d6e0243e31 Mon Sep 17 00:00:00 2001 From: May Lee Date: Tue, 17 Mar 2026 10:18:31 -0400 Subject: [PATCH] Update enrichment_table.md --- .../observability_pipelines/processors/enrichment_table.md | 5 ----- 1 file changed, 5 deletions(-) diff --git a/content/en/observability_pipelines/processors/enrichment_table.md b/content/en/observability_pipelines/processors/enrichment_table.md index 565cbe7d44f..f8f6ee9cd08 100644 --- a/content/en/observability_pipelines/processors/enrichment_table.md +++ b/content/en/observability_pipelines/processors/enrichment_table.md @@ -9,11 +9,6 @@ products: {{< product-availability >}} -{{< callout url=https://www.datadoghq.com/product-preview/use-reference-tables-in-stream-with-op-to-control-costs/ - btn_hidden="false" header="Join the Preview!">}} - The Enrichment Table processor using Reference Tables is in Preview. Use this form to request access. -{{< /callout >}} - ## Overview Logs can contain information like IP addresses, user IDs, or service names that often need additional context. With the Enrichment Table processor, you can add context to your logs, using lookup datasets stored in Datadog [Reference Tables][1], local files, or MaxMind GeoIP tables. The processor matches logs based on a specified key and appends information from your lookup file to the log. If you use Reference Tables, you can connect to and enrich logs with SaaS-based datasets directly stored in ServiceNow, Snowflake, S3, and more.