The earliest results available in the HTTP Archive are from Nov 15 2010, so in a sense this week is our three year anniversary. Three years! This was on my mind during breakfast as I thought back on how the HTTP Archive came about.
The idea came to me in 2007. I spent years evangelizing the idea which I called “the Internet Performance Archive”. The amount of work seemed large so instead of building it myself I met with various companies and encouraged them to build it, but to no avail. I knew it was worthwhile to record performance metrics aggregated across top websites. Each year that passed without this archive meant data that we’d never be able to reclaim. I felt a sense of urgency around getting the archive going.
Then, in September 2010 a confluence of events made me realize I could build it myself. The HTTP Archive file format, an effort I coordinated with Jan Odvarko (Firebug) and Simon Perkins (HttpWatch), had been announced the year before and was gaining wider support. There were more tools available that supported the HAR file format.
But the key factor was the work Pat Meenan was doing on WebPagetest. At this time Pat was working still at AOL. He was expanding the features of WebPagetest significantly and it was becoming one of the most important performance tools in the industry. On September 29 2010 I sent him this email:
Do you have time to talk today about an idea? I’m open 10:30am-12:30pm and after 3:30pm PT.
The project is the Internet Performance Archive (I mention it here) – a data warehouse of web performance stats. I’ve been talking about this for years, and I’d like to put up a first version now that would have stats for Fortune 500, Global 500, Alexa 1000 and perhaps other major lists. I’d like to get your thoughts and figure out a way to generate the HAR files as easily as possible (ie, it doesn’t take any of your time ;-).
In the ensuing discussion I suggested that Pat create an API for WebPagetest, so that I could build the HTTP Archive as a layer on top of it. In usual fashion, Pat informed me that the feature I wanted was already implemented. We proceeded to iterate on the initial LAMP prototype and started recording data less than two months later. After gathering six months of data the HTTP Archive was announced in March 2011.
There was one part of that initial concept that I was UNable to achieve – doing it without taking any of Pat’s time. Just the opposite, Pat has put in a ton of time to make the HTTP Archive possible. All of the tests are done on a private instance of WebPagetest (which Pat setup). When our load became too costly to run on AWS, Pat helped buy our own hardware and get it setup in our data center, Internet Systems Consortium. When we merged with the Internet Archive, Pat integrated our systems to use their S3-like storage system. He has built special widgets, added stats, and customized the data in the HAR file to make the HTTP Archive work better.
At this three year mark I’m thankful that the HTTP Archive has grown to be a popular source for performance and other stats about how the Web works. It’s a successful project. There’s a lot more to do (most importantly moving to Github to promote more contributions so I’m less of a bottleneck) but we’ve accomplished a lot and the future is bright.
I’m thankful for our sponsors: Google, Mozilla, New Relic, O’Reilly Media, Etsy, Radware, dynaTrace Software, and Torbit (now Walmart). Their support allowed us to move to our own hardware and purchase mobile devices for the HTTP Archive Mobile.
And I’m especially thankful for Pat’s help in creating the HTTP Archive from day one. WebPagetest is awesome, as is its creator.
A favorite character from the MASH TV series is Corporal Walter Eugene O’Reilly, fondly referred to as “Radar” for his knack of anticipating events before they happen. Radar was a rare example of efficiency because he was able to carry out Lt. Col. Blake’s wishes before Blake had even issued the orders.
What if the browser could do the same thing? What if it anticipated the requests the user was going to need, and could complete those requests ahead of time? If this was possible, the performance impact would be significant. Even if just the few critical resources needed were already downloaded, pages would render much faster.
Browser cache isn’t enough
You might ask, “isn’t this what the cache is for?” Yes! In many cases when you visit a website the browser avoids making costly HTTP requests and just reads the necessary resources from disk cache. But there are many situations when the cache offers no help:
- first visit – The cache only comes into play on subsequent visits to a site. The first time you visit a site it hasn’t had time to cache any resources.
- cleared – The cache gets cleared more than you think. In addition to occasional clearing by the user, the cache can also be cleared by anti-virus software and browser bugs. (19% of Chrome users have their cache cleared at least once a week due to a bug.)
- purged – Since the cache is shared by every website the user visits, it’s possible for one website’s resources to get purged from the cache to make room for another’s.
- expired – 69% of resources don’t have any caching headers or are cacheable for less than one day. If the user revisits these pages and the browser determines the resource is expired, an HTTP request is needed to check for updates. Even if the response indicates the cached resource is still valid, these network delays still make pages load more slowly, especially on mobile.
- revved – Even if the website’s resources are in the cache from a previous visit, the website might have changed and uses different resources.
Something more is needed.
In their quest to make websites faster, today’s browsers offer a number of features for doing work ahead of time. These “prebrowsing” (short for “predictive browsing” – a word I made up and a domain I own) techniques include:
<link rel="dns-prefetch" ...>
<link rel="prefetch" ...>
<link rel="prerender" ...>
- DNS pre-resolution
- TCP pre-connect
- the preloader
These features come into play at different times while navigating web pages. I break them into these three phases:
- previous page – If a web developer has high confidence about which page you’ll go to next, they can use LINK REL dns-prefetch, prefetch or prerender on the previous page to finish some work needed for the next page.
- transition – Once you navigate away from the previous page there’s a transition period after the previous page is unloaded but before the first byte of the next page arrives. During this time the web developer doesn’t have any control, but the browser can work in anticipation of the next page by doing DNS pre-resolution and TCP pre-connects, and perhaps even prefreshing resources.
- current page – As the current page is loading, browsers have a preloader that scans the HTML for downloads that can be started before they’re needed.
Let’s look at each of the prebrowsing techniques in the context of each phase.
Phase 1 – Previous page
As with any of this anticipatory work, there’s a risk that the prediction is wrong. If the anticipatory work is expensive (e.g., steals CPU from other processes, consumes battery, or wastes bandwidth) then caution is warranted. It would seem difficult to anticipate which page users will go to next, but high confidence scenarios do exist:
- If the user has done a search with an obvious result, that result page is likely to be loaded next.
- If the user navigated to a login page, the logged-in page is probably coming next.
- If the user is reading a multi-page article or paginated set of results, the page after the current page is likely to be next.
Let’s take the example of searching for Adventure Time to illustrate how different prebrowsing techniques can be used.
If the user searched for Adventure Time then it’s likely the user will click on the result for Cartoon Network, in which case we can prefetch the DNS like this:
<link rel="dns-prefetch" href="//cartoonnetwork.com">
DNS lookups are very low cost – they only send a few hundred bytes over the network – so there’s not a lot of risk. But the upside can be significant. This study from 2008 showed a median DNS lookup time of ~87 ms and a 90th percentile of ~539 ms. DNS resolutions might be faster now. You can see your own DNS lookup times by going to chrome://histograms/DNS (in Chrome) and searching for the DNS.PrefetchResolution histogram. Across 1325 samples my median is 50 ms with an average of 236 ms – ouch!
In addition to resolving the DNS lookup, some browsers may go one step further and establish a TCP connection. In summary, using dns-prefetch can save a lot of time, especially for redirects and on mobile.
If we’re more confident that the user will navigate to the Adventure Time page and we know some of its critical resources, we can download those resources early using prefetch:
<link rel="prefetch" href="http://cartoonnetwork.com/utils.js">
This is great, but the spec is vague, so it’s not surprising that browser implementations behave differently. For example,
- Firefox downloads just one prefetch item at a time, while Chrome prefetches up to ten resources in parallel.
- Android browser, Firefox, and Firefox mobile start prefetch requests after window.onload, but Chrome and Opera start them immediately possibly stealing TCP connections from more important resources needed for the current page.
- An unexpected behavior is that all the browsers that support prefetch cancel the request when the user transitions to the next page. This is strange because the purpose of prefetch is to get resources for the next page, but there might often not be enough time to download the entire response. Canceling the request means the browser has to start over when the user navigates to the expected page. A possible workaround is to add the ”Accept-Ranges: bytes” header so that browsers can resume the request from where it left off.
It’s best to prefetch the most important resources in the page: scripts, stylesheets, and fonts. Only prefetch resources that are cacheable – which means that you probably should avoid prefetching HTML responses.
If we’re really confident the user is going to the Adventure Time page next, we can prerender the page like this:
<link rel="prerender" href="http://cartoonnetwork.com/">
Support for dns-prefetch, prefetch, and prerender is currently pretty spotty. The following table shows the results crowdsourced from my prebrowsing tests. You can see the full results here. Just as the IE team announced upcoming support for prerender, I hope other browsers will see the value of these features and add support as well.
- 1 Need to use the
- 2 My friend at Mozilla said these features have been present since version 12.
- 3 This is based on a Bing blog post. It has not been tested.
Phase 2 – Transition
When the user clicks a link the browser requests the next page’s HTML document. At this point the browser has to wait for the first byte to arrive before it can start processing the next page. The time-to-first-byte (TTFB) is fairly long – data from the HTTP Archive in BigQuery indicate a median TTFB of 561 ms and a 90th percentile of 1615 ms.
During this “transition” phase the browser is presumably idle – twiddling its thumbs waiting for the first byte of the next page. But that’s not so! Browser developers realized that this transition time is a HUGE window of opportunity for performance prebrowsing optimizations. Once the browser starts requesting a page, it doesn’t have to wait for that page to arrive to start working. Just like Radar, the browser can anticipate what will need to be done next and can start that work ahead of time.
DNS pre-resolution & TCP pre-connect
The browser doesn’t have a lot of context to go on – all it knows is the URL being requested, but that’s enough to do DNS pre-resolution and TCP pre-connect. Browsers can reference prior browsing history to find clues about the DNS and TCP work that’ll likely be needed. For example, suppose the user is navigating to http://cartoonnetwork.com/. From previous history the browser can remember what other domains were used by resources in that page. You can see this information in Chrome at chrome://dns. My history shows the following domains were seen previously:
During this transition (while it’s waiting for the first byte of Cartoon Network’s HTML document to arrive) the browser can resolve these DNS lookups. This is a low cost exercise that has significant payoffs as we saw in the earlier dns-prefetch discussion.
If the confidence is high enough, the browser can go a step further and establish a TCP connection (or two) for each domain. This will save time when the HTML document finally arrives and requires page resources. The Subresource PreConnects column in chrome://dns indicates when this occurs. For more information about dns-presolution and tcp-preconnect see DNS Prefetching.
Similar to the progression from LINK REL dns-prefetch to prefetch, the browser can progress from DNS lookups to actual fetching of resources that are likely to be needed by the page. The determination of which resources to fetch is based on prior browsing history, similar to what is done in DNS pre-resolution. This is implemented as an experimental feature in Chrome called “prefresh” that can be turned on using the
--speculative-resource-prefetching="enabled" flag. You can see the resources that are predicted to be needed for a given URL by going to chrome://predictors and clicking on the Resource Prefetch Predictor tab.
The resource history records which resources were downloaded in previous visits to the same URL, how often the resource was hit as well as missed, and a score for the likelihood that the resource will be needed again. Based on these scores the browser can start downloading critical resources while it’s waiting for the first byte of the HTML document to arrive. Prefreshed resources are thus immediately available when the HTML needs them without the delays to fetch, read, and preprocess them. The implementation of prefresh is still evolving and being tested, but it holds potential to be another prebrowsing timesaver that can be utilized during the transition phase.
Phase 3 – Current Page
Once the current page starts loading there’s not much opportunity to do prebrowsing – the user has already arrived at their destination. However, given that the average page takes 6+ seconds to load, there is a benefit in finding all the necessary resources as early as possible and downloading them in a prioritized order. This is the role of the preloader.
Most of today’s browsers utilize a preloader – also called a lookahead parser or speculative parser. The preloader is, in my opinion, the most important browser performance optimization ever made. One study found that the preloader alone improved page load times by ~20%. The invention of preloaders was in response to the old browser behavior where scripts were downloaded one-at-a-time in daisy chain fashion.
Starting with IE 8, parsing the HTML document was modified such that it forked when an external SCRIPT SRC tag was hit: the main parser is blocked waiting for the script to download and execute, but the lookahead parser continues parsing the HTML only looking for tags that might generate HTTP requests (IMG, SCRIPT, LINK, IFRAME, etc.). The lookahead parser queues these requests resulting in a high degree of parallelized downloads. Given that the average web page today has 17 external scripts, you can imagine what page load times would be like if they were downloaded sequentially. Being able to download scripts and other requests in parallel results in much faster pages.
The preloader has changed the logic of how and when resources are requested. These changes can be summarized by the goal of loading critical resources (scripts and stylesheets) early while loading less critical resources (images) later. This simple goal can produce some surprising results that web developers should keep in mind. For example:
- scripts “at the bottom” get loaded “at the top” – A rule I promoted starting in 2007 is to move scripts to the bottom of the page. In the days before preloaders this would ensure that all the requests higher in the page, including images, got downloaded first – a good thing when the scripts weren’t needed to render the page. But most preloaders give scripts a higher priority than images. This can result in a script at the bottom stealing a TCP connection from an image higher in the page causing above-the-fold rendering to take longer.
When it comes to the preloader the bottomline is that the preloader is a fantastic performance optimization for browsers, but the logic is new and still evolving so web developers should be aware of how the preloader works and watch their pages for any unexpected download behavior.
As the low hanging fruit of web performance optimization is harvested, we have to look harder to find the next big wins. Prebrowsing is an area that holds a lot of potential to deliver pages instantly. Web developers and browser developers have the tools at their disposal and some are taking advantage of them to create these instant experiences. I hope we’ll see even wider browser support for these prebrowsing features, as well as wider adoption by web developers.
With the adoption of SPDY and progress on HTTP 2.0, I hear some people referring to domain sharding as a performance anti-pattern. I disagree. Sharding resources across multiple domains is a major performance win for many websites. However, there is room for debate. Domain sharding isn’t appropriate for everyone. It may hurt performance if done incorrectly. And it’s utility might be short-lived. Is it worth sharding domains? Let’s take a look.
The HTTP Archive has a field call “maxDomainReqs”. The explanation requires a few sentences: Websites request resources from various domains. The average website today accesses 16 different domains as shown in the chart below. That number has risen from 12.5 a year ago. That’s not surprising given the rise in third party content (ads, widgets, analytics).
The HTTP Archive counts the number of requests made on each domain. The domain with the most requests is the “max domain” and the number of requests on that domain is the “maxDomainReqs”. The average maxDomainReqs value has risen from 47 to 50 over the past year. That’s not a huge increase, but the fact that the average number of requests on one domain is so high is startling.
50 is the average maxDomainReqs across the world’s top 300K URLs. But averages don’t tell the whole story. Using the HTTP Archive data in BigQuery and bigqueri.es, both created by Ilya Grigorik, it’s easy to find percentile values for maxDomainReqs: the 50th percentile is 39, the 90th percentile is 97, and the 95th percentile is 127 requests on a single domain.
This data shows that a majority of websites have 39 or more resources being downloaded from a single domain. Most browsers do six requests per hostname. If we evenly distribute these 39 requests across the connections, each connection must do 6+ sequential requests. Response times per request vary widely, but I use 500 ms as an optimistic estimate. If we use 500 ms as the typical responsive time, this introduces a 3000 ms long pole in the response time tent. In reality, requests are assigned to whatever connection is available, and 500 ms might not be the typical response time for your requests. But given the six-connections-per-hostname limit, 39 requests on one domain is a lot.
There are costs to domain sharding. You’ll have to modify your website to actually do the sharding. This is likely a one time cost; the infrastructure only has to be setup once. In terms of performance the biggest cost is the extra DNS lookup for each new domain. Another performance cost is the overhead of establishing each TCP connection and ramping up its congestion window size.
Despite these costs, domain sharding has great benefit for websites that need it and do it correctly. That first part is important – it doesn’t make sense to do domain sharding if your website has a low “maxDomainReqs” value. For example, if the maximum number of resources downloaded on a single domain is 6, then you shouldn’t deploy domain sharding. With only 6 requests on a single domain, most browsers are able to download all 6 in parallel. On the other hand, if you have 39 requests on a single domain, sharding is probably a good choice. So where’s the cutoff between 6 and 39? I don’t have data to answer this, but I would say 20 is a good cutoff. Other aspects of the page affect this decision. For example, if your page has a lot of other requests, then those 20 resources might not be the long pole in the tent.
The success of domain sharding can be mitigated if it’s done incorrectly. It’s important to keep these guidelines in mind.
- It’s best to shard across only two domains. You can test larger values, but previous tests show two to be the optimal choice.
- Make sure that the sharding logic is consistent for each resource. You don’t want a single resource, say main.js, to flip-flop between domain1 and domain2.
- You don’t need to setup different servers for each domain – just create CNAMEs. The browser doesn’t care about the final IP address – it only cares that the hostnames are different.
These and other issues are explained in more detail in Chapter 11 of Even Faster Web Sites.
Short term hack?
Perhaps the strongest argument against domain sharding is that it’s unnecessary in the world of SPDY (as well as HTTP 2.0). In fact, domain sharding probably hurts performance under SPDY. SPDY supports concurrent requests (send all the request headers early) as well as request prioritization. Sharding across multiple domains diminishes these benefits. SPDY is supported by Chrome, Firefox, Opera, and IE 11. If your traffic is dominated by those browsers, you might want to skip domain sharding. On the other hand, IE 6&7 are still somewhat popular and only support 2 connections per hostname, so domain sharding is an even bigger win in those browsers.
A middle ground is to alter domain sharding depending on the client: 1 domain for browsers that support SPDY, 2 domains for non-SPDY modern browsers, 3-4 domains for IE 6-7. This makes domain sharding harder to deploy. It also lowers the cache hit rate on intermediate proxies.
There’s no need for domain sharding in the world of HTTP 2.0 across all popular browsers. Until then, there’s no silver bullet answer. But if you’re one of the websites with 39+ resources on a single hostname, domain sharding is worth exploring.
I started working on web performance around 2003. My first major discovery was the Performance Golden Rule:
80-90% of the end-user response time is spent on the frontend. Start there.
Up until that point all of my web development experience had been on the backend – Apache, MySQL, Perl, Java, C & C++. When I saw how much time was being spent on the frontend, I knew my performance research had to focus there.
My first discussion about web performance was with Nate Koechley when we both worked at Yahoo!. (Now we’re both at Google!) I hadn’t met Nate before, but someone told me he was the person to talk to about clientside development. I don’t think YUI existed yet, but Nate and other future YUI team members were present, leading pockets of web development throughout the company.
God bless Nate and those other folks for helping me out. I was so ignorant. I was good at finding performance inefficiencies, but I hadn’t done much frontend development. They helped me translate those inefficiencies into best practices. The other thing was – this was still early days in terms of frontend development. In fact, when I was writing my first book I didn’t know what words to use to refer to my target reader. I asked Nate and he said “F2E – frontend engineer”.
Fast forward to today when most medium-to-large web companies have dedicated frontend engineers, and many have dedicated frontend engineering teams. (I just saw this at Chegg last week.) Frontend engineering has come a long way. It’s a recognized and respected discipline, acknowledged as critical by anyone with a meaningful presence on the Web.
I like to think that web performance has helped frontend engineering grow into the role that it has today. Quantifying and evangelizing how web performance is critical to creating a good user experience and improves business metrics focuses attention on the frontend. People who know the Web know that quality doesn’t stop when the bytes leave the web server. The code running in the browser has be highly optimized. To accomplish this requires skilled engineers with established best practices, and the willingness and curiosity to adapt to a constantly changing platform. Thank goodness for frontend engineers!
This reminiscing is the result of my reflecting on the state of web performance and how it needs to grow. I’ve recently written and spoken about the overall state of the Web in terms of performance. While page load times have gotten faster overall, this is primarily due to faster connection speeds and faster browsers. The performance quality of sites seems to be getting worse: pages are heavier, fewer resources are cacheable, the size of the DOM is growing, etc.
How can we improve web performance going forward?
The state of web performance today reminds me of frontend engineering back in the early days. Most companies don’t have dedicated performance engineers, let alone performance teams. Instead, the job of improving performance is tacked on to existing teams. And because web performance spans frontend, backend, ops, and QA it’s not clear which team should ride herd. I shake my head every time a new performance best practice is found. There’s so much to know already, and the body of knowledge is growing.
Asking backend developers to do frontend engineering is a mistake. Frontend engineering is an established discipline. Similarly, asking fronted|backend|ops|QA engineers to take on performance engineering is a mistake. Performance engineering is its own discipline. The problem is, not many people have realized that yet. Our performance quality degrades as we ask teams to focus on performance “just for this quarter” or for “25% of your time”. Progress is made, and then erodes when attention focuses elsewhere. Best practices are adopted, but new best practices are missed when we cycle off performance.
What’s needed are dedicated web performance engineers and dedicated performance teams. Just like frontend engineering, these teams will start small – just one person at first. But everyone will quickly see how the benefits are bigger, are reached sooner, and don’t regress. The best practices will become more widely known. And the performance quality of the Web will steadily grow.
It turns out, this is true for many websites. Each day I visit a few pages with a table that I wish was sortable. Sometimes there are so many columns I wish I could hide the less important ones. This is especially true if my 13″ screen is the only monitor available.
This problem finally became big enough that I wrote a bookmarklet to solve the problem: activetable.js
Here’s how to use it:
1. Add this ActiveTable bookmarklet link to your bookmarks. (Drag it to your Bookmarks toolbar, or right-click and add the link to your bookmarks.)
2. Go to a page with a big table. For example, Show Slow. Once that page is loaded, click on the ActiveTable bookmark. This loads activetable.js which makes the table sortable and customizable. The table’s header row is briefly highlighted in blue to indicate it’s active.
3. Hover over a column you want to sort or remove. The ActiveTable widget is displayed:
4. Click on the sort icon to toggle between ascending and descending. Click on the red “X” to hide the column. To UNhide all columns just alt+click on any TH element.
Another nice feature of ActiveTable is the columns you choose to hide are stored in localStorage. The next time you come to the same page and launch ActiveTable, you’re asked if you want to hide the same columns again.
CAVEATS: I’ve only tested the code on Chrome and Firefox. Tables with TD cells that span multiple rows or columns may not work as expected.
You can test it out on these real world pages:
- Voting Record For Feinstein – This table is 20 pages long and doesn’t have any way to sort.
- World University Rankings – This table is already sortable, but sorting the table causes the entire page to reload. ActiveTable does sorting in place, without a reload.
- Imdb All-Time USA Box office – Even though this table has 557 rows, it’s not sortable. ActiveTable allows sorting, but sorts the dollar values alphabetically.
I love having my Web my way. ActiveTable makes it more enjoyable for me to wade through the massive tables I encounter every day.
A few weeks ago I had Chrome Dev Tools open while loading my personal website and noticed the following console messages:
I have a Twitter widget in my web page. I think this notice of deprecation is interesting. I use several 3rd party widgets and have never noticed a developer-targeted warning like this. Perhaps it’s done frequently, but this was the first time I saw anything like this.
Getting consumers to update old snippet code is a challenge for snippet owners. This is why so many sites use bootstrap scripts. The downside is bootstrap scripts typically result in two script downloads resulting in a slower snippet rendering time.
An interesting study that could be done with data from the HTTP Archive would be to analyze the adoption of new snippets. For example, tracking the migration from
platform.twitter.com/widgets.js. This would require a way to identify the before and after script. Correlating this with the techniques used to motivate website owners to change their code could help identify some best practices.
Twitter’s technique of logging warnings to console worked for me, but I don’t know how long ago they offered the async snippet version. Perhaps I’ve been lagging for months. I bet we could identify other good (and bad) techniques for evangelizing a massive code upgrade for third party widgets. That would be a good thing.
I’m doing research on the perception of speed for my Ignite Velocity talk. The perception of website speed is obviously fueled by what the user sees in the browser. While the content of a website is controlled by the website owner, the browser also provides feedback to the user. This browser feedback affects user perception of website speed. Good developers need to understand how their code affects what users see, including the browser feedback that’s triggered (or not triggered).
Let’s start by enumerating the browser’s feedback mechanisms. I’ve identified six ways that browsers give feedback when they’re busy doing some action:
- tab icon – This is typically the site’s favicon. It turns to a spinner when that tab is busy.
- status bar – Some browsers display a message about outstanding requests in the status bar.
- reload icon – The reload icon (typically a circular arrow) changes to an “X” during downloads.
- progress bar – Some browsers have a progress bar. Opera shows the fraction of completed downloads:
- network busy – iOS shows a busy indicator whenever there’s network traffic. (Technically this is outside the browser but I included it since it’s a strong visual cue at the top of the screen.)
- cursor – In some situations the cursor changes to a “progress cursor”.
The browser busy indicators are triggered during normal web surfing such as clicking links. They’re also triggered by some of the dynamic behaviors popular in today’s web pages. I came up with this list of scenarios under which to measure browser busy indicators:
- click link – Click a link to another web page.
- async script – The HTML document contains
<SCRIPT ASYNC SRC="...">.
- dynamic script before onload - The HTML document loads a script using
- dynamic iframe - Clicking a button initiates the loading of an iframe using
- dynamic script – Same as dynamic iframe but with a script.
- dynamic stylesheet - Same as dynamic iframe but with a stylesheet.
- dynamic image - Same as dynamic iframe but with an image.
- dynamic background image - Same as dynamic iframe but with a CSS background image.
- XHR – Clicking a button initiates an XMLHttpRequest.
I chose these scenarios to mimic real world situations. For example, many single page web apps use XHR – do those trigger any browser busy indicators? Photo carousels often fetch images dynamically – does the user get any feedback from the browser when that happens?
Many of the test cases didn’t trigger any of the browser busy indicators: dynamic script, dynamic stylesheet, dynamic image, dynamic background image, XHR, and long JS loop. (Except on iOS the network spinner was triggered for every test that involved an HTTP request.) I didn’t include these tests in the results table. The results for click link, async script, dynamic script before onload, and dynamic iframe are shown in the following table.
|browser||click link||async script||dynamic script
|Chrome 27 (Mac OS)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Chrome 27 (Windows)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Firefox 21 (Mac OS)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Firefox 21 (Windows)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|IE 9 (Windows)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Opera 12 (Mac OS)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Opera 12 (Windows)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Safari 6 (Mac OS)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Safari 5 (Windows)||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Chrome Mobile 26||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
|Mobile Safari 6||TSCPRN||TSCPRN||TSCPRN||TSCPRN|
Each result is essentially a bitmask indicating whether the busy indicator was triggered. For example, the first result for “Chrome 27 (Mac OS)” and the “click link” test is TSCPRN. This means the Tab icon, Status bar, and Reload icon indicators were triggered; but the Cursor, Progress bar, and Network indicators were not triggered. A few notes about the indicators:
- The network indicator is only applicable for Mobile Safari.
- The progress bar indicator is only applicable for Opera, Safari, Android, Chrome Mobile, and Mobile Safari.
- Mobile browsers don’t have tabs, status bars, nor cursors (currently) so those indicators aren’t applicable.
The purpose of these tests is to see how the browser busy indicators might affect the user’s perception of speed under different scenarios. The tests themselves are contrived, but it’s easy (and necessary) to put them in the context of a web page.
For example, if a feature involves a JSON request, which technique should be used? These browser busy indicators provide some guidance. If the JSON data is asynchronous to the user experience, such as updating stock quotes or friends’ online status, then it would be better to not trigger the browser busy indicators. Doing so would make the user pause their current actions and wonder what the web page was doing. Conversely, if the feature was synchronous to the user experience, such as opening a mail folder, then it would be better to give the user feedback that the action was being performed.
In this context we note that the dynamic iframe technique triggers busy indicators in some browsers. Therefore, this would be a bad choice for background tasks. And if it was chosen for a synchronous action it should be augmented to provide feedback across all browsers (such as a progress icon or busy spinner).
One of the biggest takeaways for me was that the progress cursor is only triggered on Windows. I find this to be a primary feedback mechanism when using the mouse – especially when clicking a link. These Mozilla bug comments seem to point to this being a Mac OS design guideline. I find it distracting on Mac OS to have to move my eye away from where I’m focusing in order to get feedback that my click was “heard”.
These busy indicators have an impact on the user’s perception of website speed. Triggering busy indicators for actions that are supposed to be in the background brings them to the user’s attention making the experience feel slower. If a user’s action is synchronous but there’s no feedback, that’s frustrating and makes the experience seem longer than it actually is. We can produce better user experiences by taking these tradeoffs into consideration and avoiding them or augmenting them depending on the situation.
[Originally posted in the 2012 Performance Calendar. Reposting here for folks who missed it.]
The performance community is growing. With 17K members across 46 meetup groups it’s pretty easy to find someone else who cares about performance. But what if your company is new to the world of high performance websites? How can you make performance a priority within your organization? I don’t have a guaranteed recipe, but here are some key ingredients for creating a culture of performance where you work.
- Get Support from the Top
- If you’re lucky like me, your CEO is already on the web performance bus. It might even have been their idea to focus on performance, and you’ve been recruited to lead the charge. If this isn’t your situation, you have to start your evangelism at the top. You might start with the CEO, or perhaps COO or an SVP. The key is it has to be someone who is a leader across the different organizations within your company. The culture shift to focus on performance doesn’t happen in engineering alone. It has to happen across product management, marketing, sales, and all other parts of the company. You need to identify who the key leader or leadership team is and get them excited about web performance, and make them believe in the benefits it delivers.
- Speak the Right Vocabulary
- As an engineer you probably know how to sell to other engineers. “Optimization” makes a developer’s ears perk up. Speaking in terms of reduced regressions and fewer outages wins over folks in devops. But you also need to know how to speak across the organization both horizontally and vertically. The UX team likes hearing about better user metrics (longer sessions, more sessions per month). The folks in finance wants to hear about reduced operating costs in terms of hardware, power consumption, and data center bandwidth. Marketing and sales will light up hearing case studies about doubling unique users from search engine marketing as a result of a faster website. Make sure to use terms that resonate with your audience.
- A key skill in evangelizing to upper management is knowing how to speak hierarchically – start with the high-level stats and drill down into the details if the need arises. I see many engineers who start with the details which many folks don’t have the time or background to follow. Start by showing a median and save the logarithmic scale charts in the “more slides” section.
- Pick the Right Product
- If you’ve convinced the senior execs to focus on performance, your next step is to pick a product to focus on. You want to pick a high visibility product, so that the wins are significant. But you don’t want to pick the company’s flagship product. It’s possible you might hit a few bumps on your first forays into adopting web performance. Also, you might have to alter the release cycle as you rollout metrics and start A/B testing. That’s harder to do with a product that’s the company’s cash cow. Start with a product that’s in the top 5 or 10, but not #1.
- Pick the Right Team
- The team you choose to work with is even more important than which product you choose. It all comes down to people, and if the team is too busy, has other priorities, or simply doesn’t believe in WPO (Web Performance Optimization) then you should move on to another team. You can always come back and revisit this team in the future.
- I always have a kickoff meeting with a team that’s interested in working on performance, and I ask how many people they can dedicate to work on performance. I’m usually looking for at least two people full-time for 3 months. Sometimes teams think it’s sufficient to have someone spend 20% of their time working on performance, but this usually doesn’t have a positive outcome. If this is the company’s first engagement with web performance, you want to make sure to pick a team that has the mindset and resources to focus on the work ahead.
- Pick the Right Task
- It’s critical that the first performance optimization deployed has a significant impact. There’s nothing more frustrating than getting folks excited about WPO only to have their work show no improvement. For most websites it’s fairly straightforward to pick an optimization that will have a big impact. I’m reminded of Ismail Elshareef‘s case study about Edmunds.com getting 80% faster. He talks about how the first task they picked was making resources cacheable. After just a day of work they pushed the fix and cut their CDN traffic by 34%! This is the type of win you want to have right out of the gate – something that takes a small amount of work and makes a big improvement.
- Start with Metrics
- I’ve had several engagements where teams got so excited about the optimizations, they started deploying fixes before the metrics were in place. This is bad for two reasons. Without metrics you’re flying blind so you don’t know the actual impact of any fixes. But more importantly, it’s likely that the first fixes you deploy will have the biggest impact. If the metrics aren’t in place then you miss out on quantifying your best work! It’s best to establish the baseline when the site is at its worst. Occasionally teams don’t want to do this because they’re embarrassed by the slowness of the site. Just remind them how happy the execs will be to see a chart showing the site getting twice as fast.
- Identify Your Replacement
- Within the chosen team there needs to be someone who is aligned with you to take over your role. This is the person who keeps the team focused on performance after you’ve moved on to help the next team. He is the one who tracks the dashboards, identifies the changes that were deployed, analyzes the A/B test results, and prioritizes the next optimizations to work on.
- It’s not scalable for you to be the only performance expert in the company. You want to build a virtual performance team that spans all the products in the company. At Yahoo! we called this team the SpeedFreaks. We had regular gatherings, a mailing list, etc. It was a great way to share lessons learned across the different teams and re-energize our excitement about making things faster.
- Get Everyone on Board
- Making and keeping the website fast requires everyone to be thinking about performance. It’s important to keep the entire company involved. There are several ways of doing this. One technique I see often is having realtime dashboards deployed at large gathering spots in the company. The Wall of Fame is another good chart. Eventually teams that are always at the bottom will start wondering what they have to do to get to the top. Getting time during the company all-hands meetings to review current performance and highlight some wins is good. Adding performance (speed) to the annual performance (HR) review form makes everyone think about their contributions in the past and plan on how they can contribute in the future.
- Use Carrot over Stick
- If you follow these tips it’s likely that you’ll start off having successful engagements evangelizing and deploying performance best practices at your company. After working with the choicest teams, however, it’s also likely that you’ll run into a team that just isn’t drinking the WPO kool-aid. This is more likely to happen at larger companies where it’s more challenging to create a cultural shift. If you can’t convince this team to apply the right amount of focus, one possible reaction is to bring in a senior exec to command them to make performance a priority and do the work. This might work in the short term, but will fail in the long term and might even set you further back from where you started.
- Performance is a way of thinking. It requires vigilance. Anyone who has it forced upon them will likely not value performance and will instead look upon it as a nuisance that took them away from their desired focus. This person is now even harder to win over. It’s better to avoid taking the “stick” approach and instead use the “carrot” as motivation – t-shirts, bonuses, executive praise, shout outs at company all-hands, etc. No one enjoys the stick approach – the team doesn’t enjoy it and neither will you. Everyone comes away with negative memories. The carrot approach might not work in the short term, but it leaves the door open for a more positive re-engagement in the future.
- Be Passionate
- It’s likely you’re the “performance lead” within the company, or at least the one who cares the most about making performance a high priority. It’s not going to be easy to get everyone else on board. You can’t go about this half heartedly. You have to be passionate about it. John Rauser spoke (passionately) about this in Creating Cultural Change at Velocity 2010. He says you have to be excited, and relentless. I agree.
Creating a culture of performance at your company is about creating a culture of quality. This is especially true because best (and worst) practices propagate quickly at web companies. Code written for product A is reused by product B. And folks who worked on team A transfer over to team C. If product A is built in a high performance way, those best practices are carried forward by the code and team members. Unfortunately, bad practices spread just as easily.
Companies like Google, Etsy, and Betfair have gone so far as to publish their commitment to performance. This is a win for their customers and for their brand. It’s also a win for the performance community because these companies are more likely to share their best practices and case studies. If your company is focused on performance, please help the community by sharing your lessons learned. If your company doesn’t have a focus on performance, I hope these tips help you establish that WPO focus to create a website that has a better user experience, more traffic, greater revenue, and reduced operating expenses.
[Originally posted in the 2012 Performance Calendar. Reposting here for folks who missed it.]
There’s an elephant in the room that we’ve been ignoring for years:
window.onload is not the best metric for measuring website speed
We haven’t actually been “ignoring” this issue. We’ve acknowledged it, but we haven’t coordinated our efforts to come up with a better replacement. Let’s do that now.
window.onload is so Web 1.0
What we’re after is a metric that captures the user’s perception of when the page is ready. Unfortunately,
perception.ready() isn’t on any browser’s roadmap. So we need to find a metric that is a good proxy.
Ten years ago,
window.onload was close enough. Plus it had other desirable attributes:
- standard across browsers -
window.onloadmeans the same thing across all browsers. (The only exception I’m aware of is that IE 6-9 don’t wait for async scripts before firing
window.onload, while most other browsers do.)
- measurable by 3rd parties –
window.onloadis a page milestone that can be measured by someone other than the website owner, e.g., metrics services like Keynote Systems and tools like Boomerang. It doesn’t require website owners to add custom code to their pages.
- measurable for real users – Measuring
window.onloadis a lightweight operation, so it can be performed on real user traffic without harming the user experience.
Web 2.0 is more dynamic
Fast forward to today and we see that
window.onload doesn’t reflect the user perception as well as it once did.
There are some cases where a website renders quickly but
window.onload fires much later. In these situations the user perception of the page is fast, but
window.onload says the page is slow. A good example of this is Amazon product pages. Amazon has done a great job of getting content that’s above-the-fold to render quickly, but all the below-the-fold reviews and recommendations produce a high
window.onload value. Looking at these Amazon WebPagetest results we see that above-the-fold is almost completely rendered at 2.0 seconds, but
window.onload doesn’t happen until 5.2 seconds. (The relative sizes of the scrollbar thumbs shows that a lot of content was added below-the-fold.)
Amazon – 2.0 seconds (~90% rendered)
Amazon – 5.2 seconds (onload)
But the opposite is also true. Heavily dynamic websites load much of the visible page after
window.onload. For these websites,
window.onload reports a value that is faster than the user’s perception. A good example of this kind of dynamic web app is Gmail. Looking at the WebPagetest results for Gmail we see that
window.onload is 3.3 seconds, but at that point only the progress bar is visible. The above-the-fold content snaps into place at 4.8 seconds. It’s clear that in this example
window.onload is not a good approximation for the user’s perception of when the page is ready.
Gmail – 3.3 seconds (onload)
Gmail – 4.8 seconds (~90% rendered)
it’s about rendering, not downloads
The examples above aren’t meant to show that Amazon is fast and Gmail is slow. Nor is it intended to say whether all the content should be loaded before
window.onload vs. after. The point is that today’s websites are too dynamic to have their perceived speed reflected accurately by
The reason is because
window.onload and the user’s perception of website speed. In other words, this problem is just going to get worse.
The conclusion is clear: the replacement for
window.onload must focus on rendering.
what “it” feels like
This new performance metric should take rendering into consideration. It should be more than “first paint”. Instead, it should capture when the above-the-fold content is (mostly) rendered.
I’m aware of two performance metrics that exist today that are focused on rendering. Both are available in WebPagetest. Above-the-fold render time (PDF) was developed at Google. It finds the point at which the page’s content reaches its final rendering, with intelligence to adapt for animated GIFs, streaming video, rotating ads, etc. The other technique, called Speed Index and developed by Pat Meenan, gives the “average time at which visible parts of the page are displayed”. Both of these techniques use a series of screenshots to do their analysis and have the computational complexity that comes with image analysis.
In other words, it’s not feasible to perform these rendering metrics on real user traffic in their current form. That’s important because, in addition to incorporating rendering, this new metric must maintain the attributes mentioned previously that make
window.onload so appealing: standard across browsers, measurable by 3rd parties, and measurable for real users.
Another major drawback to
window.onload is that it doesn’t work for single page web apps (like Gmail). These web apps only have one
window.onload, but typically have several other Ajax-based “page loads” during the user session where some or most of the page content is rewritten. It’s important that this new metric works for Ajax apps.
I completely understand if you’re frustrated by my lack of implementation specifics. Measuring rendering is complex. The point at which the page is (mostly) rendered is so obvious when flipping through the screenshots in WebPagetest. Writing code that measures that in a consistent, non-impacting way is really hard. My officemate pointed me to this thread from the W3C Web Performance Working Group talking about measuring first paint that highlights some of the challenges.
To make matters worse, the new metric that I’m discussing is likely much more complex than measuring first paint. I believe we need to measure when the above-the-fold content is (mostly) rendered. What exactly is “above-the-fold”? What is “mostly”?
Another challenge is moving the community away from
window.onload. The primary performance metric in popular tools such as WebPagetest, Google Analytics Site Speed, Torbit Insight, SOASTA (LogNormal) mPulse, and my own HTTP Archive is
window.onload. I’ve heard that some IT folks even have their bonuses based on the
window.onload metrics reported by services like Keynote Systems and Gomez.
It’s going to take time to define, implement, and transition to a better performance metric. But we have to get the ball rolling. Relying on
window.onload as the primary performance metric doesn’t necessarily produce a faster user experience. And yet making our websites faster for users is what we’re really after. We need a metric that more accurately tracks our progress toward this ultimate goal.
I enjoy evangelizing web performance because I enjoy things that are fast (and efficient). Apparently, I’m not the only one. Recent ad campaigns, especially for mobile, tout the virtues of being fast. Comcast uses the words “speed”, “fastest”, “high-speed”, and “lightning-fast” in the Xfinity ads. AT&T’s humorous set of commercials talks about how “faster is better“. iPhone’s new A6 chip is touted as “twice as fast“.
Consumers, as a result of these campaigns selling speed, have higher expectations for the performance of websites they visit. Multiple case studies support the conclusion that a faster website is better received by users and has a positive impact on the business’s bottom line:
- Bing found that searches that were 2 seconds slower resulted in a 4.3% drop in revenue per user.
- When Mozilla shaved 2.2 seconds off their landing page, Firefox downloads increased 15.4%.
- Shopzilla saw conversion rates increase 7-12% as a result of their web performance optimization efforts.
- Making Barack Obama’s website 60% faster increased donation conversions 14%.
Vendors are pitching a faster web. Consumers are expecting a faster web. Businesses succeed with a faster web. But is the Web getting faster? Let’s take a look.
A key to a faster web experience is a faster Internet connection, but this aspect of web performance often feels like a black box. Users and developers are at the mercy of the ISPs and carrier networks. Luckily, data from Akamai’s State of the Internet shows that connection speeds are increasing.
I compiled this chart by extracting the relevant data from each quarterly report. The chart shows that global connection speeds increased 4% and US connection speeds increased 18% over the most recent year that data exists (Q3 2011 to Q3 2012). I also created an Average Mobile Connection Speed chart which tracks three mobile carrier networks. Akamai masks the carrier network name but over the last year the connection speed of these mobile networks increased 30%, 68%, and 131%.
Speed is a major feature for browsers. This focus has resulted in many performance improvements over the last few years. In my opinion browser improvements are the biggest contributor to a faster web. I’ll sidestep the contentious debate about which browser is fastest, and instead point out that, regardless of which one you choose, browsers are getting faster with each release.
The following chart shows page load times for major browsers as measured from real users. This report from Gomez is a bit dated (August 2011), but it’s the only real user data I’ve seen broken out by browser. Notice the trends for new releases – page load times improve 15-30%.
Web developers don’t have much control over connection speeds and browser optimizations, but they can control the size of their pages. Unfortunately, page weight continues to increase. The data below is from the HTTP Archive for the world’s top 1000 URLs. It shows that transfer size (number of bytes sent over the wire) increased 231K (28%) from March 2012 to March 2013. The biggest absolute increase was in images – growing 114K (23%). The biggest surprise, for me, was the growth in video by 62K (67%). This increase comes from two main factors: more sites are including video and the size of videos are increasing. Video performance is an area that we need to focus on going forward.
|Table 1. Transfer Size Year over Year|
|Mar 2012||Mar 2013||Δ|
|total||822 K||1053 K||231 K (28%)|
|images||486 K||600 K||114 K (23%)|
|JS||163 K||188 K||25 K (15%)|
|video||92 K||154 K||62 K (67%)|
|HTML||35 K||42 K||7 K (20%)|
|CSS||30 K||36 K||6 K (20%)|
|font||8 K||18 K||10 K (125%)|
|other||8 K||15 K||7 K (88%)|
Quality of Craft
There are several “performance quality” metrics tracked in the HTTP Archive. Like page weight, these metrics are something that web developers have more control over. Unfortunately, these metrics were generally flat or trending down for the world’s top 1000 URLs. These metrics are hard to digest in bulk because sometimes higher is better, and other times it’s worse. There’s more detail below but the punchline is 5 of the 7 metrics got worse, and the other two were nearly flat.
|Table 2. Quality of Craft Metrics Year over Year|
|Mar 2012||Mar 2013|
|# of Domains||15||19|
|Max Reqs on 1 Domain||40||41|
|Pages w/ Redirects||67%||71%|
Here’s a description of each of these metrics and how they impact web performance.
- PageSpeed Score – PageSpeed is a performance “lint” analysis tool that generates a score from 0 to 100, where 100 is good. YSlow is a similar tool. Year over year the PageSpeed Score increased from 82 to 84, a (small) 2% improvement.
- DOM Elements – The number of DOM elements affects the complexity of a page and has a high correlation to page load times. The number of DOM elements increased from 1215 to 1330, meaning pages are getting more complex.
- # of Domains – The average number of domains per page increased from 15 to 19. More domains means there are more DNS lookups, which slows down the page. This is likely due to the increase in 3rd party content across the Web.
- Max Reqs on 1 Domain – The average top 1000 web page today has 100 requests spread across 19 domains. That averages out to ~5 requests per domain. But the distribution of requests across domains isn’t that even. The HTTP Archive counts how many requests are made for each domain, and then records the domain that has the maximum number of requests – that’s the “Max Reqs on 1 Domain” stat. This increased from 40 to 41. This is a bad trend for performance because most browsers only issue 6 requests in parallel, so it takes seven “rounds” to get through 41 requests. These sites would be better off adopting domain sharding.
- Cacheable Resources – Pages are faster if resources are read from cache, but that requires website owners to set the appropriate caching headers. This stat measures the percentage of requests that had a cache lifetime greater than zero. Unfortunately, the percentage of cacheable resources dropped from 62% to 60%.
- Compressed Responses – The transfer size of text responses (HTML, scripts, stylesheets, etc.) can be reduced ~70% by compressing them. It doesn’t make sense to compress binary data such as images and video. This stat shows the percentage of requests that should be compressed that actually were compressed. The number increased but just slightly from 76% to 77%.
- Pages with Redirects – Redirects slow down pages because an extra roundtrip has to be made to fetch the final response. The percentage of pages with at least one redirect increased from 67% to 71%.
These drops in performance quality metrics is especially depressing to me since evangelizing performance best practices is a large part of my work. It’s especially bad since this only looks at the top 1000 sites which typically have more resources to focus on performance.
The ultimate goal isn’t to improve these metrics – it’s to improve the user experience. Unfortunately, we don’t have a way to measure that directly. The metric that’s used as a proxy for the user’s perception of website speed is “page load time” – the time from when the user initiates the request for the page to the time that window.onload fires. Many people, including myself, have pointed out that window.onload is becoming less representative of a web page’s perceived speed, but for now it’s the best we have.
Perhaps the largest repository of page load time data is in Google Analytics. In April 2013 the Google Analytics team published their second report on the speed of the web where they compare aggregate page load times to a year ago. The median page load time on desktops got ~3.5% faster, and on mobile was
~18% ~30% faster.
Web pages have gotten bigger. The adoption of performance best practices has been flat or trending down. Connection speeds and browsers have gotten faster. Overall, web pages are faster now than they were a year ago. I think browser vendors deserve most of the credit for this speed improvement. Going forward, web developers will continue to be pushed to add more content, especially 3rd party content, to their sites. Doing this in a way that follows performance best practices will help to make the Web even faster for next year.