# PERF01-BP06 Benchmark existing workloads
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 Benchmark the performance of an existing workload to understand how it performs on the cloud. Use the data collected from benchmarks to drive architectural decisions. 

 Use benchmarking with synthetic tests and real-user monitoring to generate data about how your workload’s components perform. Benchmarking is generally quicker to set up than load testing and is used to evaluate the technology for a particular component. Benchmarking is often used at the start of a new project, when you lack a full solution to load test. 

 You can either build your own custom benchmark tests, or you can use an industry standard test, such as [TPC-DS](http://www.tpc.org/tpcds/) to benchmark your data warehousing workloads. Industry benchmarks are helpful when comparing environments. Custom benchmarks are useful for targeting specific types of operations that you expect to make in your architecture. 

 When benchmarking, it is important to pre-warm your test environment to ensure valid results. Run the same benchmark multiple times to ensure that you’ve captured any variance over time. 

 Because benchmarks are generally faster to run than load tests, they can be used earlier in the deployment pipeline and provide faster feedback on performance deviations. When you evaluate a significant change in a component or service, a benchmark can be a quick way to see if you can justify the effort to make the change. Using benchmarking in conjunction with load testing is important because load testing informs you about how your workload will perform in production. 

 **Common anti-patterns:** 
+  You rely on common benchmarks that are not indicative of your workload characteristics. 
+  You rely on customer feedback and perceptions as your only benchmark. 

 **Benefits of establishing this best practice:** Benchmarking your current implementation allows you to measure the improvement in performance. 

 **Level of risk exposed if this best practice is not established:** Medium 

## Implementation guidance
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 Monitor performance during development: Implement processes that provide visibility into performance as your workload evolves. 

 Integrate into your delivery pipeline: Automatically run load tests in your delivery pipeline. Compare the test results against pre-defined key performance indicators (KPIs) and thresholds to ensure that you continue to meet performance requirements. 

 Test user journeys: Use synthetic or sanitized versions of production data (remove sensitive or identifying information) for load testing. Exercise your entire architecture by using replayed or pre-programmed user journeys through your application at scale. 

 Real-user monitoring: Use CloudWatch RUM to help you collect and view client-side data about your application performance. Use this data to help establish your real-user performance benchmarks. 

## Resources
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 **Related documents:** 
+  [AWS Architecture Center](https://aws.amazon.com/architecture/) 
+  [AWS Partner Network](https://aws.amazon.com/partners/) 
+  [AWS Solutions Library](https://aws.amazon.com/solutions/) 
+  [AWS Knowledge Center](https://aws.amazon.com/premiumsupport/knowledge-center/) 
+  [Amazon CloudWatch RUM](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-RUM.html) 
+  [Amazon CloudWatch Synthetics](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Synthetics_Canaries.html) 

 **Related videos:** 
+  [Introducing The Amazon Builders’ Library (DOP328)](https://www.youtube.com/watch?v=sKRdemSirDM) 
+  [This is my Architecture](https://aws.amazon.com/architecture/this-is-my-architecture/) 
+  [Optimize applications through Amazon CloudWatch RUM](https://www.youtube.com/watch?v=NMaeujY9A9Y) 
+  [Demo of Amazon CloudWatch Synthetics](https://www.youtube.com/watch?v=hF3NM9j-u7I) 

 **Related examples:** 
+  [AWS Samples](https://github.com/aws-samples) 
+  [AWS SDK Examples](https://github.com/awsdocs/aws-doc-sdk-examples) 
+  [Distributed Load Tests](https://aws.amazon.com/solutions/implementations/distributed-load-testing-on-aws/) 
+  [Measure page load time with Amazon CloudWatch Synthetics](https://github.com/aws-samples/amazon-cloudwatch-synthetics-page-performance) 
+  [Amazon CloudWatch RUM Web Client](https://github.com/aws-observability/aws-rum-web)