[E&A] Creates a page for guidance on when to use EIS and when to use ML nodes

explore-analyze/elastic-inference/ml-node-vs-eis.md

@@ -0,0 +1,55 @@
+---
+navigation_title: ML-nodes vs EIS
+applies_to:
+  stack: ga
+  serverless: ga
+  deployment:
+    self: unavailable
+---
+
+# Using ML-nodes or Elastic {{infer-cap}} Service (EIS) [ml-nodes-vs-eis]
+
+## When to use EIS?
+
+The Elastic Inference Service (EIS) requires zero setup or management. It's always-on, has excellent ingest throughput, and uses simple token-based billing.
+
+Use EIS if you're getting started with [semantic search](/solutions/search/semantic-search.md) or [hybrid search](/solutions/search/hybrid-search.md) and want a smooth experience. Under the hood, EIS uses GPUs for ML {{infer}}, which are more efficient and allow a faster, more cost-effective experience for most usecases.
+
+## When to use {{ml}} nodes?
+
+ML nodes are a more configurable solution than EIS where you can set up specific nodes using CPUs to execute [ML {{infer}}](/explore-analyze/elastic-inference/inference-api.md). {{ml-cap}} nodes tend to give more fine-grained control.
+
+Use ML nodes if you want to decide how your models run, you want to run custom models, or you have a self-managed setup.
+
+## How do I switch from using ML nodes to EIS on an existing index?
+
+```{applies_to}
+stack: ga 9.3
+serverless: ga
+```
+
+```console
+PUT /my-ml-node-index/_mapping
+{
+  "properties": {
+    "text": {
+      "type": "semantic_text",
+      "inference_id": ".elser-2-elastic"
+    }
+  }
+}
+```
+
+You can also switch an EIS-based index to use ML nodes:
+
+```console
+PUT /my-eis-index/_mapping
+{
+  "properties": {
+    "text": {
+      "type": "semantic_text",
+      "inference_id": ".elser-2-elasticsearch"
+    }
+  }
+}
+```

explore-analyze/toc.yml

@@ -41,6 +41,8 @@ toc:
   - file: elastic-inference.md
     children:
       - file: elastic-inference/eis.md
+        children:
+          - hidden: elastic-inference/ml-node-vs-eis.md
       - file: elastic-inference/inference-api.md
   - file: machine-learning.md
     children: