One of the huge benefits of tracking web performance over time is the ability to see trends and compare metrics. Last year we added new functionality that makes it easy for you to bookmark and compare different synthetic tests in your test history. We recently added some additional enhancements to make comparing tests even easier.
With the 'Compare' feature, you can generate side-by-side comparisons that let you not only spot regressions, but easily identify what caused them:
Along the way, we've also made it much more intuitive for you to drill down into your detailed synthetic test results. Let's take a look...
We’ve been pretty vocal about Core Web Vitals since Google announced this initiative last spring. We love the idea of having a lean, shared set of metrics that we can all rally around – not to mention having a broader conversation about web performance that includes teams throughout an organization.
For many site owners, the increased focus on Core Web Vitals is driven by the fact that Google will be including them as a factor in search ranking in May 2021. Other folks are more interested in distilling the extremely large barrel of performance metrics into an easily digested trinity of guidelines to follow in order to provide a delightful user experience.
We’ve had some time to evaluate and explore these metrics, and we're committed to transparently discussing their pros and cons.
The purpose of this post is to explore First Input Delay (FID). This metric is unique among the three Web Vitals in that it is can only be measured using real user monitoring (RUM), while the other two (Largest Contentful Paint and Cumulative Layout Shift) can be measured using both RUM and synthetic monitoring.
In this post we'll cover:
Let's dig in!
The general consensus within the web performance community is that any JS scripting task that takes more than 50ms to execute can affect a user's experience. When the browser's main thread hits max CPU for more than 50ms, a user starts to notice that their clicks are delayed and that scrolling the page has become janky and unresponsive. Batteries drain faster. People rage click or go elsewhere.
No one plans to make a page or web app that sucks the life out of their users' devices, so it's super important to monitor the effect your JS is having. (Yes... I'm looking at you, front-end JS libraries and third-party ads!)
Getting visibility into the impact that known third parties have on the user experience has long been a focus in our community. There are some great tools out there – like 3rdParty.io from Nic Jansma and Request Map from Simon Hearne – which give us important insight into the complexity involved in tracking third-party content.
When we released our re-imagined Third Party Dashboard last year, we were excited to be providing site owners with another great tool for managing the unmanageable. Among other things, we took an approach that included:
We received a lot of feedback from our customers, who loved the new third-party functionality but REALLY wanted to see similar functionality for their "first party" content as well. We heard this message loud and clear, and today we're happy to announce a few changes to our Synthetic monitoring tool that address this need while preserving the functionality you already know and love.
For the past two years, the performance.now() conference has been the most valuable performance event I've attended. So valuable, in fact, that I've made some of the talks the cornerstone of this list of performance resolutions for 2020. I'd love to know how many – if any – of these are on your list. As always, I'd love people's feedback!
Here at SpeedCurve, the past few months have found us obsessing over how to define and measure user happiness. We've also been scrutinizing JS performance, particularly as it applies to third parties. And as always, we're constantly working to find ways to improve your experience with using our tools. See below for exciting updates on all these fronts.
As always, we love hearing from you, so please send your feedback and suggestions our way!
A while back, our friends at Shopify published this great case study, showing how they optimized one of their newer themes from the ground up – and how they worked to keep it fast. Inspired by that post, I wanted to dig a bit deeper into a few of the best practices they mentioned, which fall loosely into these three buckets:
Keep reading to learn how you can apply these best practices to your own site and give your pages a speed boost.
To help focus our attention on CPU, several new performance metrics have been defined and evangelized over the last year or three. In this post I'm going to focus on these:
Here's a figure to help visualize these metrics.
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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 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:
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.