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Co-authored-by: Austin Lai <76412946+alai97@users.noreply.github.com>
DataDog · Sep 24, 2024 · e377c37 · e377c37
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diff --git a/anyscale/README.md b/anyscale/README.md
@@ -6,11 +6,11 @@ This check monitors [Anyscale][1]. Anyscale is a compute platform that hosts [Ra
 
 ## Setup
 
-To install and configure the Datadog Agent with the Ray integration on Anyscale, follow [this documentation][6].
+To install and configure the Datadog Agent with the Ray integration on Anyscale, see the [official Anyscale documentation][6].
 
 ## Data Collected
 
-See the [Data Collected by Ray][4].
+See the [Ray integration's Data Collected section][4].
 
 ## Troubleshooting
 

diff --git a/anyscale/assets/monitors/failed_task.json b/anyscale/assets/monitors/failed_task.json
@@ -2,11 +2,11 @@
     "version": 2,
     "created_at": "2023-12-13",
     "last_updated_at": "2023-12-13",
-    "title": "High Number of Failed Tasks on anyscale Node",
+    "title": "High Number of Failed Tasks on Anyscale Node",
     "description": "Tasks are scheduled to workers by the Anyscale scheduler. This monitor alerts when there are too many scheduling failures within a specified time period due to a particular reason.",
     "definition": {
         "id": 136348417,
-        "name": "High Number of Failed Tasks on anyscale Node",
+        "name": "High Number of Failed Tasks on Anyscale Node",
         "type": "query alert",
         "query": "avg(last_5m):avg:ray.scheduler.failed_worker_startup{*} by {reason,nodeaddress} > 25",
         "message": "{{#is_alert}}\nThere are {{value}} tasks that failed to be schedule because workers were not available. This occurred on node: {{nodeaddress.name}}. The stated reason was {{reason.name}}.\n{{/is_alert}}",

diff --git a/anyscale/assets/monitors/gpu_utilization.json b/anyscale/assets/monitors/gpu_utilization.json
@@ -2,7 +2,7 @@
     "version": 2,
     "created_at": "2023-12-13",
     "last_updated_at": "2023-12-13",
-    "title": "Low GPU Utilization low on Anyscale Node",
+    "title": "GPU Utilization low on Anyscale Node",
     "description": "Ray can leverage the computing power of GPUs to perform machine learning or data processing tasks. Underutilizing available GPU can be expensive. This monitor alerts when the GPU utilization is low on a Anyscale node indicating overprovisioning.",
     "definition": {
         "id": 136350024,