Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Instrumenting The Rest Of The Company: Hunting ...
Search
Eric Sigler
May 23, 2017
Technology
0
370
Instrumenting The Rest Of The Company: Hunting For Metrics
Presented at Monitorama 2017, video at:
https://youtu.be/wnjCNBfH3kg?t=3h3m35s
Eric Sigler
May 23, 2017
Tweet
Share
More Decks by Eric Sigler
See All by Eric Sigler
Four years of breaking things in production, on purpose.
esigler
0
58
A Brief Introduction To DevOps
esigler
0
110
Humans are terrible compilers: A User's Guide
esigler
0
120
Do You Know If Your Service Is Working Properly? A Guide To Being Paranoid.
esigler
0
180
"Is there any strong objection?"
esigler
0
230
Fear, Uncertainty, and Continuous Deployment
esigler
1
120
3AM, a survey.
esigler
0
230
Strategies For Being On Call & Keeping Your Sanity At The Same Time
esigler
0
160
Engineering for Engineers
esigler
0
92
Other Decks in Technology
See All in Technology
関係性が駆動するアジャイル──GPTに人格を与えたら、対話を通してふりかえりを習慣化できた話
mhlyc
0
130
PLaMoの事後学習を支える技術 / PFN LLMセミナー
pfn
PRO
9
3.8k
自動テストのコストと向き合ってみた
qa
0
110
Flaky Testへの現実解をGoのプロポーザルから考える | Go Conference 2025
upamune
1
420
Pure Goで体験するWasmの未来
askua
1
180
OCI Network Firewall 概要
oracle4engineer
PRO
1
7.8k
BirdCLEF+2025 Noir 5位解法紹介
myso
0
190
o11yで育てる、強い内製開発組織
_awache
3
120
AI Agentと MCP Serverで実現する iOSアプリの 自動テスト作成の効率化
spiderplus_cb
0
490
DataOpsNight#8_Terragruntを用いたスケーラブルなSnowflakeインフラ管理
roki18d
1
340
生成AI_その前_に_マルチクラウド時代の信頼できるデータを支えるSnowflakeメタデータ活用術.pdf
cm_mikami
0
110
FastAPIの魔法をgRPC/Connect RPCへ
monotaro
PRO
1
730
Featured
See All Featured
GraphQLとの向き合い方2022年版
quramy
49
14k
XXLCSS - How to scale CSS and keep your sanity
sugarenia
248
1.3M
The World Runs on Bad Software
bkeepers
PRO
71
11k
Typedesign – Prime Four
hannesfritz
42
2.8k
A Tale of Four Properties
chriscoyier
160
23k
Designing for humans not robots
tammielis
254
25k
Stop Working from a Prison Cell
hatefulcrawdad
271
21k
We Have a Design System, Now What?
morganepeng
53
7.8k
Build The Right Thing And Hit Your Dates
maggiecrowley
37
2.9k
Music & Morning Musume
bryan
46
6.8k
Building an army of robots
kneath
306
46k
Code Review Best Practice
trishagee
72
19k
Transcript
@esigler Instrumenting The Rest Of The Company: Hunting For Useful
Metrics Eric Sigler, Head of DevOps, PagerDuty
@esigler Alternatively: ”Lies, Damn Lies, and Hacky Scripts"
@esigler
@esigler Engineer Eng Engineer Eng? Manager Mgr Manager
@esigler (No stock photos harmed in the making of this
talk.)
@esigler "We have problem $foo, so we're going to do
$bar."
@esigler "What data did you use to understand $foo? And
how will we know if $bar improved anything?”
@esigler “We can’t really measure either $foo and/or $bar.”
@esigler “Without data, you're just another person with an opinion.”
- W. Edwards Deming
@esigler
@esigler
@esigler
@esigler (Turns out other managers do this too.)
@esigler
@esigler "We have a problem with people not knowing what
the chatbot does, so we're going to write better documentation."
@esigler
@esigler ?
@esigler
@esigler “If only there was some way we could track
events, and show them over time.”
@esigler
@esigler
@esigler
@esigler Outcome: Writing a smarter help function in the chat
bot. (And simplifying some commands).
@esigler
@esigler Takeaway: Reuse existing tools when it makes sense.
@esigler
@esigler "We have slow tests in CI, so we're going
to complain a lot about it.”
@esigler “Define slow.”
@esigler Local != CI
@esigler
@esigler
@esigler
@esigler
@esigler “Tests take forever to start.”
@esigler
@esigler ?
@esigler
@esigler Outcome: More workers. (And, knowing how many to budget
for.)
@esigler Takeaway: Look for ways to reverse engineer existing metrics.
@esigler
@esigler "We have to ship code faster, so we're going
to reorganize."
@esigler
@esigler
@esigler But it doesn’t show where the bottlenecks are.
@esigler Pipe GitHub metrics into &
@esigler
@esigler
@esigler
@esigler Then start making changes.
@esigler
@esigler
@esigler Outcome: Productivity success! (With massive organizational change to enable
it.)
@esigler Takeaway: Look for proxy metrics
@esigler Potpourri: Data collection (chat, email, calendars) Cross-validation of metrics
(“Sniff test”) Cognitive biases around metrics Plotting against organization events
@esigler Takeaways: Useful metrics are everywhere You aren’t alone in
digging for metrics Existing tools can be repurposed Look to reverse engineer your way to a metric Look for proxy metrics (but choose wisely)
@esigler Thank you!
@esigler Image credits: https://commons.wikimedia.org/wiki/File:Staff_meeting.jpg https://blogs-images.forbes.com/kellyallan/files/2015/06/Deming-in-Tuxedo-DEM-1078-Dr.-Deming2-1940x1130.jpg (Wherever I grabbed that
screenshot from Pulp Fiction, my apologies I am a terrible person for not capturing the URL)