Lock in $30 Savings on PRO—Offer Ends Soon! ⏳
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Site-Speed That Sticks
Search
Harry Roberts
November 14, 2024
Technology
13
980
Site-Speed That Sticks
Harry Roberts
November 14, 2024
Tweet
Share
More Decks by Harry Roberts
See All by Harry Roberts
How to Think Like a Performance Engineer
csswizardry
28
2.3k
cache rules everything
csswizardry
5
3.6k
My Website Is Slow! Where Do I Start?
csswizardry
5
520
Optimising Largest Contentful Paint
csswizardry
37
3.5k
Get Your Head Straight
csswizardry
15
21k
From Milliseconds to Millions: A Look at the Numbers Powering Web Performance
csswizardry
1
2.6k
More Than You Ever Wanted to Know About Resource Hints
csswizardry
6
9.6k
It’s My (Third) Party, and I’ll Cry if I Want To
csswizardry
13
5.6k
FaCSSt: CSS & Performance
csswizardry
26
4.2k
Other Decks in Technology
See All in Technology
2025 DORA Reportから読み解く!AIが映し出す、成果を出し続ける組織の共通点 #開発生産性_findy
takabow
2
970
"'TSのAPI型安全”の対価は誰が払う?不公平なスキーマ駆動に終止符を打つハイブリッド戦略
hal_spidernight
0
220
Introduction to Bill One Development Engineer
sansan33
PRO
0
320
MCP・A2A概要 〜Google Cloudで構築するなら〜
shukob
0
120
DGX SparkでローカルLLMをLangChainで動かした話
ruzia
1
240
インフラ室事例集
mixi_engineers
PRO
2
190
Bakuraku Engineering Team Deck
layerx
PRO
10
3.1k
生成AIシステムとAIエージェントに関する性能や安全性の評価
shibuiwilliam
2
310
Kill the Vibe?Architecture in the age of AI
stoth
1
160
.NET 10 のパフォーマンス改善
nenonaninu
2
4.3k
TypeScript×CASLでつくるSaaSの認可 / Authz with CASL
saka2jp
2
210
OpenShiftのBGPサポート - MetalLB+FRR-k8s編
orimanabu
0
130
Featured
See All Featured
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
46
2.6k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
46
7.8k
VelocityConf: Rendering Performance Case Studies
addyosmani
333
24k
Faster Mobile Websites
deanohume
310
31k
Bash Introduction
62gerente
615
210k
Java REST API Framework Comparison - PWX 2021
mraible
34
9k
Navigating Team Friction
lara
191
16k
Fireside Chat
paigeccino
41
3.7k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
5.7k
Typedesign – Prime Four
hannesfritz
42
2.9k
Code Review Best Practice
trishagee
73
19k
KATA
mclloyd
PRO
32
15k
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
None
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
None
csswz.it/perfnow25
one weird trick…
None
// plugins/delay.server.ts export default defineNuxtPlugin(async () => { await new
Promise(resolve => setTimeout(resolve, 900)) })
None
None
<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
None
None
1
1 2
1 2 3
1 2 3
None
None
1
1 2
1 2 3
1 2 3
external: 1842ms inlined: 1250ms
None
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
None
predictors as tripwires
None
budgets versus targets
budgets are backstops; targets are ambitions
target == kpi
None
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
None
🎉
?
None
None
None
None
it’s the exact same file
None
you’re monitoring variation in tests
None
only alert on your kpis
None
None
0.9952409649
None
None
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
None
None
None
None
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