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Site-Speed That Sticks
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Harry Roberts
November 14, 2024
Technology
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710
Site-Speed That Sticks
Harry Roberts
November 14, 2024
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Transcript
site-speed that sticks
None
hi, i’m harry
None
five key topics
1. metrics 2. localhost 3. backstops 4. monitoring 5. playbook
1. metrics 2. localhost 3. backstops 4. monitoring 5. playbook
1. metrics 2. localhost 3. backstops 4. monitoring 5. playbook
1. metrics 2. localhost 3. backstops 4. monitoring 5. playbook
1. metrics 2. localhost 3. backstops 4. monitoring 5. playbook
1. metrics 2. localhost 3. backstops 4. monitoring 5. playbook
metrics
not all metrics are born equal
different metrics for different people on different occasions with different
levels of disclosure
kpis, enablers, predictors
kpis
definition + target
what are we working toward?
of interest to the business
core web vitals
‘which number on which dashboard of which service?’
“We want a one-second improvement in Largest Contentful Paint.” —
My Client
None
None
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enablers
metrics that directly influence kpis
of interest to engineering teams
ttfb, input delay
predictors
signals of good/bad performance
highly quantitative
of interest to engineers
bundle size, long tasks, blocking css
great for root-causing and reverse engineering
localhost
localhost is: seldom live-like, pretty dang fast, un-bundled
know your tools inside out
None
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csswz.it/perfnow25
one weird trick…
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// plugins/delay.server.ts export default defineNuxtPlugin(async () => { await new
Promise(resolve => setTimeout(resolve, 900)) })
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<head> <link rel=stylesheet href=https://slowfil.es/file?type=css&delay=800> </head>
core web vitals are too big for localhost
if you’re working locally, measure locally
bare-metal metrics
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1
1 2
1 2 3
1 2 3
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1
1 2
1 2 3
1 2 3
external: 1842ms inlined: 1250ms
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these are very private metrics
backstops
…and budgets
what is the worst possible performance we will accept?
set it to the worst reading in the last release
cycle
None
this is where synthetic testing comes into it
synthetic testing; real user monitoring
when to fail a release
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predictors as tripwires
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budgets versus targets
budgets are backstops; targets are ambitions
target == kpi
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monitoring
the m in rum stands for monitoring
“Insanity is doing the same thing over and over again
and expecting different results.” — Rita Mae Brown
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🎉
?
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None
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it’s the exact same file
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you’re monitoring variation in tests
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only alert on your kpis
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0.9952409649
None
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always follow the numbers
playbook
“Fighting regressions took priority over optimizations […]” — Michelle Vu,
Pinterest
None
it’s all for nothing if you don’t have a plan
response = f(severity, duration)
severity
acceptable: <10%
moderate: 10–25%
severe: 25–50%
critical: >50%
duration
temporary: 24–48hr
sustained: >48hr
long-term: >1 release cycle
unresolved: many release cycles
a kpi regression of over 10% for one week requires
remediation in the next sprint
a kpi regression of over 100% for one hour requires
rollback immediately
a kpi regression of over 25% for one day requires
remediation in the current sprint
an enabler regression of over any% for any time needs
the team’s attention over the next sprint
a predictor regression of over any% for any time needs
my attention over the next sprint
you need a framework to fill in these blanks
early triage
who, what, when, where, and why?
what?
what has regressed?
when?
when did it start? is it still like that?
where?
is it a business-critical part of the site?
who?
who owns the problem?
why?
can you conduct early triage?
None
None
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key takeaways
increase confidence
use the right tool for the right job
have a plan of attack
agree; commit
thank you
harry.is/for-hire