Update azure-monitor-agent-performance.md

Final edits on Page

Author: JeffreyWolford

articles/azure-monitor/agents/azure-monitor-agent-performance.md

@@ -1,77 +1,58 @@
 ---
 title: Performance Benchmark for forwarding Gateway using Azure Monitor Agent 
-description: enter here
+description: Performance data for the AMA running in a gateway scenario
 ms.topic: conceptual
 author: guywi-ms
 ms.author: guywild
-ms.date: 5/07/2023
+ms.date: 4/07/2023
 ms.reviewer: jeffwo
 
-#customer-intent: As a deployment engineer, I can scope the resources required to run a gateway that collects data into one stream using the Azure Monitor Agent. 
----
-
-# Performance Benchmark for forwarding Gateway using Azure Monitor Agent  
- 
+#customer-intent: As a deployment engineer, I can scope the resources required to scale my gateway data colletors the use the Azure Monitor Agent. 
 
-The agent can handle many thousands of events per second in the gateway event forwarding scenario. The exact throughput rate depends on various factors such as the size of each event, the specific instance type, and physical resources. This article will describe the Microsoft internal benchmark used for testing the agent throughput for Syslog events in the forwarder scenario. The benchmark results should provide a guide to size the resources that you will need in your environment. 
+---
+# Azure Monitor Agent Performance Benchmark
 
-
-Note: The results in this article are informational about the performance of AMA in the forwarding scenario only and do not constitute any service agreement on the part of Microsoft.   
-
+The agent can handle many thousands of events per second in the gateway event forwarding scenario. The exact throughput rate depends on various factors such as the size of each event, the specific data type, and physical hardware resources. This article will describe the Microsoft internal benchmark used for testing the agent throughput of 10k Syslog events in the forwarder scenario. The benchmark results should provide a guide to size the resources that you will need in your environment. 
 
+> [!NOTE]
+> The results in this article are informational about the performance of AMA in the forwarding scenario only and do not constitute any service agreement on the part of Microsoft.   
 
-Best practices for agent as a forwarder. 
+## Best practices for agent as a forwarder. 
 
-The forwarder should be on a dedicated system to eliminate potential interference from other workloads. 
+- The forwarder should be on a dedicated system to eliminate potential interference from other workloads. 
+- The forwarder system should be monitored for CPU, memory, and disk utilization to prevent overloads from causing data loss. 
+- Where possible use a load balancer and redundant forwarder systems to improve reliability and scalability. 
+- For other considerations for forwarders see the Log Analytics Gateway documentation. 
 
-The forwarder system should be monitored for CPU, memory, and disk utilization to prevent overloads from causing data loss. 
-
-Where possible use a load balancer and redundant forwarder systems to improve reliability and scalability. 
-
-For other considerations for forwarders see the Log Analytics Gateway documentation. 
-
- 
-
-Agent Performance 
+## Agent Performance 
 
 The benchmark is run in a controlled environment to get repeatable, accurate, and statistically significant results. The resources consumed by the agent are measured under a load of 10,000 simulated Syslog events per second. The simulated load is run on the same physical hardware that the agent under test is on. Test trials are run for seven days. For each trial, performance metrics are sampled every second to collect CPU, memory, and network maximum and average usage. This approach provides the right information to help you estimate the resources needed for your environment. 
 
-Note: The results do not measure the end-to-end throughput ingested by a Log Analytics Workspace (or other telemetry sinks), as there may be end-to-end variability due to network and backend pipeline performance.   
-
-The benchmarks are run on an Azure VM Standard_F8s_v2 system using AMA Linux version 1.25.2. 10 GB of disk space is required as a data cache. 
+> [!NOTE]
+> The results do not measure the end-to-end throughput ingested by a Log Analytics Workspace (or other telemetry sinks), as there may be end-to-end variability due to network and backend pipeline performance.   
 
-vCPU’s:	8 with HyperThreading (800% CPU is possible) 
+The benchmarks are run on an Azure VM Standard_F8s_v2 system using AMA Linux version 1.25.2 and 10 GB of disk space for the event cache. 
 
-Memory: 	16 GiB 
-
-Temp Storage:	64 GiB 
-
-Max Disk IOPS:	6400 
-
-Network:	12500 Mbp Max on all 4 physical NICs 
+- vCPU’s:	8 with HyperThreading (800% CPU is possible) 
+- Memory: 	16 GiB 
+- Temp Storage:	64 GiB 
+- Max Disk IOPS:	6400 
+- Network:	12500 Mbp Max on all 4 physical NICs 
 
 
 
-Results 
-
-Perf Metric 
-
-Ave (Max) Med 
-
-CPU % 2 Cores 
-
-51 (262) 
-
-Mem RSS MB 
-
-276 (1,017) 
-
-Network KBps 
-
-338 (18,033) 
+## Results 
 
+| Perf Metric | Ave (Max) Med |
+|:---|:---:|
+| CPU %           | 51 (262)     |
+| Mem RSS MB      | 276 (1,017)  |
+| Network KBps    | 338 (18,033) |
 
 
 ## Next steps
 
+- [Connect computers without internet access by using the Log Analytics gateway in Azure Monitor](gateway.md)
+- [Install the Azure Monitor Agent](azure-monitor-agent-manage.md) on Windows and Linux virtual machines.
+- [Create a data collection rule](data-collection-rule-azure-monitor-agent.md) to collect data from the agent and send it to Azure Monitor.