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Key Performance Metrics By @GrabnerAndi | @DevOpsSummit [#APM #DevOps]

Capture and analyze the metrics from the different application tiers and components in your application

Key Performance Metrics for Load Tests Beyond Response Time | Part I

Whether it is JMeter, SoapUI, Load Runner, SilkTest, Neotys or one of the cloud-based load testing solutions such as Keynote, Dynatrace (formerly Gomez) or others, breaking an application under heavy load is easy these days. Finding the problem based on automatically generated load testing reports is not. Can you tell me what is wrong based on the following reports?

Load Testing Reports alone are showing you that there is a problem - but not necessarily where you should look next

My Key Metrics from Web Server to Database
I've helped engineering organizations over the last 10 - 15 years to either run or analyze load tests. In this blog post I share my best practices and metrics I typically look when analyzing load testing results. I am not relying on the out-of-the box load testing reports, but instead I extend them based on the tools and capabilities, or put in an APM tool such as Dynatrace to capture this type of data while the load testing tool drives the load.

Some of the technical product screenshots in this blog are taken from data users of our Dynatrace Free Trial who shared data through my Share Your PurePath program. Thanks to all of them.

Now - if a load testing task is coming up for you I hope you find most of my described steps useful as I believe it will make analyzing your results easier. Feel free to use Dynatrace (or any other APM tool if you already have such a tool) in order to capture and analyze the following metrics from the different application tiers and components in your application:

From web server to database there are key performance metrics to look at instead of spending too much time in the load testing report

Now - let me go into the details of these metrics, where to capture them from, and what they tell us. In this blog I focus on the Web Server, Application Server, Hosts and the Application Layers. The next blog will focus on the Database as well as Errors and Logging.

1. Top Web Server Metrics
On the Web Server (Apache, IIS, Nginx, ...) the following key metrics have proven extremely valuable to identify problems in your deployment:

  • Busy and Idle Threads
    • Do you need more worker threads per web server?
    • Do you need more web servers?
    • Are threads busy for too long because of application performance hotspots?
  • Throughput
    • How many transactions / minute can we handle?
    • When do we need to scale out and add more web servers?
  • Bandwidth Requirements
    • Is the network the bottleneck?
    • Are our average pages too heavy?
    • Can we offload content to CDNs?

For example below we have a Web Server Process Health Dashboard- showing all of the metrics that are key for me. They get captured through a module placed in the Web Server:

Key metrics from your web server: worker threads, throughput and bandwidth

2. Top App Server Metrics
On the application server (Java, .NET, PHP) I focus on the following key metrics to identify any deployment or configuration problems on your application servers:

  • Load Distribution
    • How many transactions are handled by each JVM/CLR/PHP engine?
    • Are they equally load balanced?
    • Do we need more application servers to handle the load?
  • CPU Hotspots
    • How much CPU is needed for this tested load?
    • Is high CPU caused by bad programming and can be fixed?
    • Or do we need more CPU power?
  • Worker Threads
    • Is the number of worker threads correctly configured?
    • Are worker threads busy because the application servers are not ready?
    • Are there any web server modules that block these threads?
  • Memory Issues
    • Do we see bad memory patterns? Do we have a memory leak?
    • What's the impact of garbage collection on CPU and transaction throughput?

The following screenshot shows my Process Health Dashboard. All data is automatically captured via an agent and injected in your Java, .NET, PHP or node.js engine:

Key metrics from your app server: worker threads, CPU, memory and throughput

For insight on hosts and the application layers click here for the full article

More Stories By Andreas Grabner

Andreas Grabner has been helping companies improve their application performance for 15+ years. He is a regular contributor within Web Performance and DevOps communities and a prolific speaker at user groups and conferences around the world. Reach him at @grabnerandi

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