Performance Budgets in the Modern Web

What is web performance?

Why does it matter?

The amount of  time

it takes for a website to look and feel usable

of mobile site visits are abandoned if pages take longer than 3 seconds to load

53%

Google DoubleClick (2016)

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Sites loading within 5 seconds have

70

Google DoubleClick (2016)

longer sessions

%

53

lower bounce rates

%

25

higher ad viewability

%

to those loading in 15 seconds

15 seconds?!
Do websites actually load that slowly?

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15 seconds is the load time of

Yes!

MEDIAN

PHONE

NETWORK

WEBSITE

{

Google Research (2018)

Every 100ms decrease in load speed worked out to a 1.11% increase in session-based conversion

Mobify Insights Report (Q2 2016)

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How do we improve it?

Developing a performance budget

Step 1:

Research

Research 

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April 2018 Traffic

Research 

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April 2018 Mobile Traffic

Deeper Research 

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Network speeds comparable to our 3G speeds

Median phone is $200 Android (Samsung Galaxy J7 Prime)

We should be targeting these criteria:

The State of LTE, Open Signal (2017)

Let's start making a budget

⚡️ 3G speeds

⚡️ $200 Android Phone

⚡️ 5 Second Time to Interactive

- 300 ms RTT

- 1.6  Mbps Download

- 768 Kbps Upload

- Moto G (Gen 4)

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Step 2:

Working Backwards

Subtract network overhead

300ms     DNS lookup

1200ms     Network overhead

300ms     TCP handshake

600ms     TLS handshake

300ms     HTTP request

+

High Performance Browser Networking, Ilya Grigorik (2013)

5000ms Performance budget

1200ms Network overhead

-

3800ms Remaining budget

Assuming RTT = 300ms

Determine amount of data we can transfer

3G Speeds

⬇️ 1.6  Mbps Download

⬆️ 768 Kbps Upload

1.6 Mbps = 200 KB/s

Remaining Budget

⏱ 3800ms / 3.8s

200 KB/s * 3.8 = 760KB

📦 760KB Bundle Size

What about compression?

Gzip will typically compress JavaScript by a factor of 5x to 7x

Our 760 KB of uncompressed JS can then be somewhere in the range of 3.75MB to 5.32MB

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3.75 MB

Not so fast!! What about parse/eval?

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1500 ms

JavaScript Start-up Performance, Addy Osmani (2017)

parse / eval time per 1MB of JS

So here's all the data we have

We have 3.8s load time remaining

It takes 1.5s per 1MB of JS to parse & eval

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We receive 200 KB (0.2 MB) per second

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We have a gzip compression factor of 5x

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Now let's start punching numbers

⚙️ gzipFactor = 5x

🛬 connectionSpeed = 0.2 MB

⏱️ budgetAvailable = 3.8s

😵 parseEvalFactor = 1.5s / MB

Constants

budgetAvailable = transferTime + parseEvalTime

Formulae

transferTime = compressedJsSize / connectionSpeed

parseEvalTime = fullJsSize x parseEvalFactor

fullJsSize = compressedJsSize x gzipFactor

budgetAvailable = transferTime + parseEvalTime

⚙️ gzipFactor = 5

🛬 connectionSpeed = 0.2 MB

⏱️ budgetAvailable = 3.8s

😵 parseEvalFactor = 1.5s / MB

Constants

transferTime = compressedJsSize / connectionSpeed

parseEvalTime = fullJsSize x parseEvalFactor

budgetAvailable = transferTime + parseEvalTime

Formulae

⏱️ 3.8s = transferTime + parseEvalTime

⏱️ 3.8s = (compressedJsSize / connectionSpeed) + parseEvalTime

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + parseEvalTime

⏱️ 3.8s = (compressedJsSize / 0.2) + fullJsSize x parseEvalFactor

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + fullJsSize x 😵 1.5

fullJsSize = compressedJsSize x gzipFactor

⚙️ gzipFactor = 5

🛬 connectionSpeed = 0.2 MB

⏱️ budgetAvailable = 3.8s

😵 parseEvalFactor = 1.5s / MB

Constants

transferTime = compressedJsSize / connectionSpeed

parseEvalTime = fullJsSize x parseEvalFactor

budgetAvailable = transferTime + parseEvalTime

Formulae

fullJsSize = compressedJsSize x gzipFactor

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + (compressedJsSize x gzipFactor) x 😵 1.5

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + fullJsSize x 😵 1.5

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + (compressedJsSize x gzipRatio) x 😵 1.5

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + (compressedJsSize x ⚙️ 5) x 😵 1.5

Solve for compressedJsSize!

304 KB x 5 = 1502 KB

Our compressed JS bundle budget is 304 KB

⏱️ 3.8s = (compressedJsSize / 🛬 0.2) + (compressedJsSize x ⚙️ 5) x 😵 1.5

Our JS bundle budget is 1.5 MB

Under ideal conditions, the budget for critical-path resources (HTML, CSS, JS, etc.) comes out to be:

3.75 MB for sites without much JS

1.5 MB for sites built with JS frameworks

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Thank you for listening!

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