From c2524284fc350c4448dba0886787f23e60a9ca56 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Wed, 18 Oct 2023 11:25:58 +0200 Subject: [PATCH] [DOCS] Documents that models with one allocation might have downtime (#2567) * [DOCS] Documents that models with one allocations might have downtime. * [DOCS] Fine-tunes wording. --- docs/en/stack/ml/nlp/ml-nlp-deploy-models.asciidoc | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/docs/en/stack/ml/nlp/ml-nlp-deploy-models.asciidoc b/docs/en/stack/ml/nlp/ml-nlp-deploy-models.asciidoc index 67c57cf72..0ce4e40a1 100644 --- a/docs/en/stack/ml/nlp/ml-nlp-deploy-models.asciidoc +++ b/docs/en/stack/ml/nlp/ml-nlp-deploy-models.asciidoc @@ -198,6 +198,11 @@ nodes. Model allocations are independent units of work for NLP tasks. To influence model performance, you can configure the number of allocations and the number of threads used by each allocation of your deployment. +IMPORTANT: If your deployed trained model has only one allocation, it's likely +that you will experience downtime in the service your trained model performs. +You can reduce or eliminate downtime by adding more allocations to your trained +models. + Throughput can be scaled by adding more allocations to the deployment; it increases the number of {infer} requests that can be performed in parallel. All allocations assigned to a node share the same copy of the model in memory. The