Update README.md

README.md

@@ -16,16 +16,16 @@ At a high level, we will be following the steps outlined below for this solution
     Deploy application services to an Amazon ECS and register them with AWS Cloud Map
   </li>
   <li>
-    Deploy Prometheus server to Amazon ECS, configure service discovery and send metrics data to Amazon Managed Service for Prometheus
+    Deploy Prometheus server to Amazon ECS, configure service discovery and send metrics data to Amazon Managed Service for Prometheus (AMP)
   </li>
   <li>
-    Visualize metrics data using Amazon Managed Service for Grafana
+    Visualize metrics data using Amazon Managed Service for Grafana (AMG)
   </li>  
 </ul>
 
 ### Deploy
 
-Make sure you have the latest version of AWS CLI that provides support for Amazon Managed Service for Prometheus. The deployment requires an ECS cluster. For deploying the Prometheus Node Exporter, a cluster with EC2 instances is required. All deployment artifacts are under the [deploy](https://github.com/aws-samples/prometheus-for-ecs/tree/main/deploy) directory. The deployment comprises the following components:
+Make sure you have the latest version of AWS CLI that provides support for AMP. The deployment requires an ECS cluster. For deploying the Prometheus Node Exporter, a cluster with EC2 instances is required. All deployment artifacts are under the [deploy](https://github.com/aws-samples/prometheus-for-ecs/tree/main/deploy) directory. The deployment comprises the following components:
 - An ECS task comprising the Prometheus server, AWS Sig4 proxy and the service discovery application containers
 
 - A mock web application that is instrumented with [Prometheus Go client library](https://github.com/prometheus/client_golang) and exposes an HTTP endpoint */work*. The application has an internal load generator that sends client requests to the HTTP endpoint. The service exposes a [Counter](https://prometheus.io/docs/concepts/metric_types/#counter) named *http_requests_total* and a [Histogram](https://prometheus.io/docs/concepts/metric_types/#histogram) named *request_durtaion_milliseconds*
@@ -56,7 +56,7 @@ Create a service discovery namespace and service registries under AWS Cloud Map
 source cloudmap.sh
 ```
 
-Create a workspace under Amazon Managed Service for Prometheus (AMP) for ingesting Prometheus metrics scraped from ECS services. 
+Create a workspace under AMP for ingesting Prometheus metrics scraped from ECS services. 
 ```
 source amp.sh
 ```
@@ -75,7 +75,7 @@ Launch the ECS services using the task definitions created above.
 source services.sh
 ```
 
-Once the services are all up and running, the AMP workspace will start ingesting metrics collected by the Prometheus server from the web application. Use Amazon Managed Service for Grafana to query and visualize the metrics ingested into AMP. You may use the following PromQL queries to visualize the metrics collected from the web application and Prometheus Node Exporter
+Once the services are all up and running, the AMP workspace will start ingesting metrics collected by the Prometheus server from the web application. Use AMG to query and visualize the metrics ingested into AMP. You may use the following PromQL queries to visualize the metrics collected from the web application and Prometheus Node Exporter
 - HTTP request rate: *sum(rate(http_requests_total[5m]))*
 - Average response latency: *sum(rate(request_durtaion_milliseconds_sum[5m])) / sum(rate(request_durtaion_milliseconds_count[5m]))*
 - Average CPU usage:  *100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[1m])) * 100)*