diff --git a/src/content/docs/serverless-function-monitoring/aws-lambda-monitoring/instrument-lambda-function/containerized-images.mdx b/src/content/docs/serverless-function-monitoring/aws-lambda-monitoring/instrument-lambda-function/containerized-images.mdx
index ae3de370fd8..2d09d5cb9c3 100644
--- a/src/content/docs/serverless-function-monitoring/aws-lambda-monitoring/instrument-lambda-function/containerized-images.mdx
+++ b/src/content/docs/serverless-function-monitoring/aws-lambda-monitoring/instrument-lambda-function/containerized-images.mdx
@@ -1,5 +1,5 @@
 ---
-title: "Instrument your containerized function"
+title: "Containerized instrumentation"
 metaDescription: A guide for instrumenting your containerized image layer with New Relic.
 redirects:
   - /docs/serverless-function-monitoring/aws-lambda-monitoring/enable-containerized-function-monitoring/get-started
@@ -7,7 +7,7 @@ redirects:
 freshnessValidatedDate: never
 ---
 
-If you're using a containerized image for a Lambda function and want to monitor your application, you'll need to add New Relic to your Dockerfile. For example, suppose you're a developer for a budgeting application and you're using a Lambda function to calculate account balances every time a customer clicks **See my balance**. You want to dive deep into any potential latencies. In that case, you'll need to add New Relic to your function, so every time a customer clicks **See my balance** your function runs, and New Relic does too.
+If you're using a containerized image for a Lambda function and want to monitor your application, you'll need to add a pre-built [New Relic Lambda layer](https://gallery.ecr.aws/newrelic-lambda-layers-for-docker?page=1) to your Dockerfile that matches your function's runtime. 
 
 Here's a diagram showing the process of adding New Relic to the Dockerfile so you can monitor your function: