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The APM (application performance management) market is addicted to data. Every vendor is in a race to pull the most data and slice it up in more ways. If you don’t have the buzzwords “analytics” or “big data” in your pitch you don’t have a chance. If the end goal is to optimize performance it’s rather interesting that the APM market only addresses half of the Performance Optimization Lifecycle.

performance optimization cycle

Drowning In Data

We have endless tools for measuring and pulling performance data. But, nothing to help analyze that data and turn it into actionable optimizations. It’s still an incredibly manual process. We’re not the only ones that believe this:

turning data into performance optimization gartner

Here is another quote from Steve Souders, a prominent thought leader in the performance space:

I think there’s still a lot of interest in the idea of helping people turn data into actions. Although I think that’s a bigger conversation we could have. In many ways, we’re right at that cusp again today where we’re getting better and better tools for capturing metrics and monitoring our systems, especially in terms of performance. But what’s lacking is a conversion of that data into actions. Diagnosing problems and recommending actions to fix them. I think YSlow, and also Google’s product, page speed, have atrophied from a lack of attention these past few years. I think we’re gonna see a resurgence in those kinds of tools over the next two years.

Addressing The Data Deluge

Here at Rigor, we’re always looking for ways to automate and save our users time and resources. This is why we are addressing this glaring hole in the Performance Optimization Cycle. Instead of only asking questions like:

  • What is my performance?
  • Is my performance getting better or worse?

We strive to build technology that helps answer questions like:

  • Why is this my performance?
  • What exactly do I need to do to improve it?
  • How can we learn to do this right next time?

Stan McCrystal said it best in his recent post on Big Data:

Data or intelligence without context isn’t useful. To be successful in 2016 and to move at the pace that your industry demands, you must harness the power of your network to understand the context behind the data. Simply reporting on metrics and results at meetings will not help your organization grow and learn; instead, the focus should be on reporting across and sharing context.

At Rigor we’re building an intelligence engine on top of a monitoring technology that takes performance best practices and optimization techniques from the top thought leaders in the performance space and community to provide insight against the performance data we pull.

The best way to show this is to highlight an example of a large publisher in their first two weeks of using the Rigor platform to make optimizations and measure their performance.

Performance Optimization of a Top Digital Publisher (Comparison of performance over first two weeks)

performance optimization before and after

The above picture shows two performance scans of the homepage of digital media site. One scan is of the digital property when they started monitoring their performance with Rigor and the other is a scan run 10 days later. Our initial scan found nearly 51 performance defects that could be optimized or improved to decrease the overall load time of the site and improve reliability. You can click this link to view some of the “defects” that can be found by our platform.

By diving into our list of performance defects, site administrators built a plan to improve their web performance in a prioritized and systematic fashion. After just 10 days, we can already see big improvements being made:

  • Overall page weight dropped 26%
  • Caching improved by 16%
  • Number of defects decreased by 2
  • OnLoad time decreased by nearly 4 seconds

site content by file type

If we look beyond just the homepage of the site to other key article pages we see that the load time of nearly all of the sites monitored web pages trended down over time.

average load time for the first two weeks

Actions taken based on Rigor insights decreased variability in page size and resulted in a gradual decline in overall page size.
page size over the first two weeks

The performance optimization lifecycle is a process teams are already leveraging, but to this point APM technologies have not fully aligned with this lifecycle. As we continue to build out the worlds first prescriptive monitoring platform that turns data into actions, we hope to further align with the complete performance optimization lifecycle and we’d love feedback from the web performance community! Please email us at with ideas and suggestions you have for automating the performance optimization lifecycle.


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