This blog post has a simple conclusion: Load script asynchronously! Simple, and yet the reality is that most scripts are still loaded synchronously. Understanding the importance of loading scripts asynchronously might help increase adoption of this critical performance improvement, so we're going to walk through the evolution of async script loading starting way back in 2007. Here's what loading 14 scripts looked like in Internet Explorer 7:
The Internet really is a complicated series of tubes. As a result, any time-based metrics we capture can have variations as those tubes wobble a bit as we shove data down them. To help reduce that variation, when we do synthetic tests, we always load a page at least three times and take the median result. But even then you'll find that, over time, your charts will still show plenty of variation.
All that variation can make it difficult to see if your metrics are getting better or worse over time. We recently released a couple of new features in your Synthetic and LUX charts that make it easier for you to visualize trends and compare discrete time periods within your historical data.
To make it easier for you to see which direction your metrics are heading, we've added an option to all your charts to show a trend line which helps you visualize how a particular metric is changing over the timespan of the chart. You can hover over the legend to highlight a trend line or hover over any point on the trend to see the estimated value at that point.
JavaScript is the main cause for making websites slow. Ten years ago it was network bottlenecks, but the growth of JavaScript has outpaced network and CPU improvements on today's devices. In the chart below, based on an analysis from the HTTP Archive, we see the number of requests has increased for both first and third party JavaScript since 2011.
The number of performance metrics is large and increases every year. It's important to understand what the different metrics represent and pick metrics that are important for your site. Our Evaluating rendering metrics post was a popular (and fun) way to compare and choose rendering metrics. Recently I created this timeline of performance metric medians from the HTTP Archive for the world's top ~1.3 million sites:
This week we've made some pretty exciting new changes to your Favorites dashboards. Aside from a brand-new chart editor interface, you'll also notice that we've introduced two new chart types: histograms and correlations.
In this post, I'm going to talk through some of the features in our new chart editor. I'll also explain in detail explain why I think histograms are such an important tool in your performance toolkit, and how you can get some fascinating insights by correlating other metrics on top of a histogram.
Here at SpeedCurve, we are continually gathering detailed performance data from tens of thousands of web pages. This gives us a relatively unique opportunity to analyse and aggregate performance metrics to gain some interesting insights. In this post, I'm going to analyse some browser-based paint timing metrics: First Paint & First Contentful Paint (defined in the Paint Timing spec and implemented in Chromium). I'm also going to analyse First Meaningful Paint (defined in a draft spec and implemented as a Chromium trace metric).
The aim of almost any performance optimisation on the web is to improve the user experience. The folk at Google have been pushing this sentiment with a focus on user-centric performance metrics, which aim to answer four questions about users’ experiences:
First Paint (FP) measures the point at which pixels are first rendered to the screen after navigating to a new page. First Contentful Paint (FCP) is slightly more specific, in that it measures the point at which text or graphics are first rendered to the screen. Both of these metrics are available in Chromium browsers (Chrome, Opera, Samsung Internet, etc) via the Performance API: performance.getEntriesByType('paint')
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The paint timing metrics are important because they aim to answer the first question: is it happening? My analysis will look at performance data from some popular websites in an attempt to figure out whether the paint timing metrics really do answer that question.
One of the longest-standing items on my performance monitoring tool wishlist is an automatically-generated performance improvement checklist, with the improvements ordered by the impact that they will have on the website. In a previous life, I spent countless hours writing performance reports and conducting A/B performance tests to figure out which change would have the biggest impact on a website's performance.
So I'm understandably very excited that today we're announcing the new Improve dashboard – a prioritised performance improvement checklist that aggregates Lighthouse and Google PageSpeed results across all the URLs in your site to identify the most impactful performance changes you can make.
In the year since Google rolled out Lighthouse, it's safe to say that "Will you be adding Lighthouse scoring?" is one the most common questions we've fielded here at SpeedCurve HQ. And since Google cranked up the pressure on sites to deliver better mobile performance (or suffer the SEO consequences) earlier this month, we've been getting that question even more often.
We take a rigorous approach to adding new metrics. We think the best solution is always to give you the right data, not just more data. So we're very happy to announce that after much analysis and consideration, we've added Lighthouse scores to SpeedCurve. Here's why – as well as how you can see your scores if you're already a SpeedCurve user.
When looking to improve the performance and user experience of our sites we often start by looking at the network:
What's the time to first byte?
How many requests are we making and how long are they taking?
What's blocking the browser from rendering my precious pixels?
While these are entirely valid questions, over the last few years we've seen a growing number of web performance issues that are caused, not by the network, but by the browser's main thread getting clogged up by excessive CPU usage.
We're excited to announce the availability of the First Input Delay metric as part of LUX, SpeedCurve's RUM product.