1.
Welcome to ServerlessToronto.org
1
Introduce Yourself ☺
- Why are you here? Where from?
- Looking or Offering work?
Fill the survey to win prises!
“SRE Topics with Charity Majors & Liz
Fong-Jones of Honeycomb.io”
will start at 6:10pm…

2.
Knowledge Sponsor
Fill the survey to win
monthly Manning Giveaways:
https://forms.gle/ANEa6j3GZnsUm7jZ7
https://www.manning.com/books/software-telemetry
GOOD LUCK!

3.
Upcoming ServerlessToronto.org Meetups
3
1) AWS re:Invent 2020 Recap –
James Beswick of AWS
2) Serverless Cloud Native Java
with Spring Cloud GCP (No
platform needed) – Ray Tsang,
Java Champion of GCP
3) Community Lightning Talks &
Updates for our 3rd Birthday
4) ??? We need you ☺
Please rate us online ☺

4.
Serverless is not just about the Tech:
4
Serverless is New Agile & Mindset
#1 Serverless Dev
(Back-end FaaS dev, but
turned into gluing APIs
and Managed Services)
#2 We're obsessed to
creating business value
(meaningful MVPs,
Products), to empower
Business users
#3 We build bridges
between Serverless
Community (“Dev leg”),
and Front-end & Voice-
First developers & User
Experience designers
(“UX leg”)
#4 Achieve agility NOT
by “sprinting” faster
(like in Scrum), but
working smarter (by
using bigger building
blocks and less Ops)

5.
“Toss It Over the Fence” SDLC principle ;)
Why DevOps topics at Serverless event?
5
My reality was: The
idea of
Dev – Ops “line”
became, not 2 but 3
silos:
Dev | DevOps | Ops

6.
Looking back, it
appears that my
obsession with
Startups/Serverless
was (in a way) an
escape from the
Corporate IT reality
Why DevOps topics at Serverless event?
6

7.
7
SLI tells when users
are happy/unhappy
SLIs, SLOs, SLAs,
oh my! (class SRE
implements
DevOps) videos
“When the student
is ready, the teacher
will appear” to help
us resolve Dev vs.
Ops conflict…
SRE shifts focus from Dev & Ops to Users!

8.
8
Feature Presentations with Charity & Liz,
Honeycomb.io

9.
@mipsytipsy
The Socio-Technical Path
to ✨High-Performing✨ Teams
Observability and the Glorious Future
@mipsytipsy

10.
@mipsytipsy
engineer/cofounder/CTO
https://charity.wtf

11.
the fundamental building block
by which we organize ourselves
and coordinate and scale our labor.
Teams.

12.
The teams you join will define your career
more than any other single factor.

13.
bad jobs can
be bad in
so, so many
different ways…
Bad Job One:
• predatory product
• praised for pulling all-nighters
• alienated from coworkers
• long commute
• neglectful manager
• the worst Silicon Valley cliches
Bad Job Two:
• aging, obsolete tech
• high operational toil
• fragile, flappy systems
• complacency
• low engineering skill level
• command-and-control
leadership

14.
autonomy, learning, high-
achieving, learned from
our mistakes, curious,
responsibility, ownership,
inspiring, camaraderie,
pride, collaboration, career
growth, rewarding,
motivating
manual labor, sacred cows,
wasted effort, stale tech,
ass-covering, fear,
fiefdoms, excessive toil,
command-and-control,
cargo culting, enervating,
discouraging, lethargy,
indifference

15.
Motivation

16.
Sociotechnical Systems
Socio- Technical Systems
Team, Tools, and Production

17.
sociotechnical (n)
“Technology is the sum of ways in which social groups construct the
material objects of their civilizations. The things made are socially
constructed just as much as technically constructed. The merging of these
two things, construction and insight, is sociotechnology” — wikipedia
if you change the tools people use,
you can change how they behave and even who they are. 😱

18.
sociotechnical (n)
Values
Practices
Tools

19.
Socio-
Technical
Systems
sociotechnical (n)
Your system is a snowflake.
hire growth-oriented people
build emotional safety
invest in good tooling, pay down tech debt
practice observability-driven development
instrument, observe, iterate, and repeat
construct and tweak virtuous feedback loops.

20.
You can’t fix what you can’t measure.
How well does YOUR team perform?
https://services.google.com/fh/files/misc/state-of-devops-2019.pdf
4
🔥key🔥
metrics.
Socio-

21.
1 — How frequently do you deploy?
2 — How long does it take for code to go live?
3 — How many of your deploys fail?
4 — How long does it take to recover from an outage?
5 — How often are you alerted after hours?
Every team lead should watch these.
Know where you stand.

22.
We waste a LOT of time.
https://stripe.com/reports/developer-coefficient-2018
42%!!!
42%!!!
42%!!!
42%!!!
42%!!!

23.
There is a wide gap between elite teams and the bottom 50%.

24.
It really, really, really,
really, really
pays off
to be on a
high performing team.

25.
Who is going to be the better engineer
two years from now?
3000 deploys/year
9 outages/year
6 hours firefighting
5 deploys/year
65 outages/year
firefighting: constant

26.
Q: What happens when an
engineer from the elite yellow
bubble joins a team in the
medium blue bubble?
A: Your productivity tends
to rise (or fall) to match that
of the team you join.

27.
“Build great teams by only hiring the best people”Great teams make great engineers. ❤

28.
Every engineering org
has a dual mandate.
The work consists of cultivating sociotechnical feedback loops
so engineers can own the full lifecycle of their code
and that begins with observability.
Happier customers, happier teams.

29.
This brings us to tools.
Technical
I don’t know exactly what you need
but I can guess :)
Observability, Progressive Deployments, Continuous Delivery, SLOs
And your weakest points in the OMM

30.
observability(n):
“In control theory, observability is a measure of how well
internal states of a system can be inferred from knowledge of
its external outputs. The observability and controllability of a
system are mathematical duals." — wikipedia

31.
Can you understand what’s happening inside your
systems, just by asking questions from the outside? Can
you debug your code and any behavior using its output?
Can you answer new questions without shipping new code?
o11y for software:

32.
• Arbitrarily-wide structured data blobs
(“canonical logs”)
• Visualize by time (“trace”)
• Gathers up full context in a single blob per
req per service
• Propagates unique request IDs and span IDs
Yes Observability:
• Unstructured, ad hoc logs
• Metrics-based tools (Prometheus,
DataDog, SignalFX, WaveFront, etc)
• Anything that requires indexes or schemas
Not Observability:
technical nitpick:

33.
o11y technical dependencies (long):
https://www.honeycomb.io/blog/so-you-want-to-build-an-observability-tool/
• High cardinality
• High dimensionality
• Exploratory, open-ended investigation based on raw events
• Service Level Objectives. No preaggregation.
• Based on arbitrarily-wide structured events with span support
• No indexes, schemas, or predefined structure
• Bundling the full context of the request across network hops
• Metrics != observability. Unstructured logs != observability.

34.
"I don't have time to invest in observability right now. Maybe later”
You can't afford not to.

35.
1. Resiliency to failure
2. High-quality code
3. Manage complexity and technical debt
4. Predictable releases
5. Understand user behavior
https://www.honeycomb.io/wp-content/uploads/2019/06/Framework-for-an-Observability-Maturity-Model.pdf
Observability Maturity Model
… find your weakest category, and tackle that first

36.
Observability is the key to making the leap
from known-unknowns to unknown-
unknowns, and
software lifecycle ownership.
unknown-unknownsknown-unknowns
monitoring observability

37.
• Ephemeral and dynamic
• Far-flung and loosely coupled
• Partitioned, sharded
• Distributed and replicated
• Containers, schedulers
• Service registries
• Polyglot persistence strategies
• Autoscaled, multiple failover
• Emergent behaviors
• ... etc
Complexity🔥
Why now?

38.
Without observability, your team will resort to
guessing and iterating blindly, without evidence,
and you will struggle to connect or debug
feedback loops.
Observability enables you to inspect cause and
effect at a granular level. Observability enables
engineers to have ownership over the lifecycle of
their software.
Example? Sure!

39.
The app tier capacity is exceeded. Maybe we
rolled out a build with a perf regression, or
maybe some app instances are down.
DB queries are slower than normal. Maybe
we deployed a bad new query, or there is
lock contention.
Errors or latency are high. We will look at
several dashboards that reflect common root
causes, and one of them will show us why.
“Photos are loading slowly for some people. Why?”
(LAMP stack)
we should
monitor these things!

40.
“Photos are loading slowly for some people. Why?”
(microservices)
Any microservices running on c2.4xlarge instances and
PIOPS storage in us-east-1b has a 1/20 chance of
running on degraded hardware, and will take 20x
longer to complete for requests that hit the disk with a
blocking call. This disproportionately impacts people
looking at older archives due to our fanout model.
Canadian users who are using the French language
pack on the iPad running iOS 9, are hitting a
firmware condition which makes it fail saving to local
cache … which is why it FEELS like photos are
loading slowly
Our newest SDK makes db queries sequentially if
the developer has enabled an optional feature flag.
Working as intended; the reporters all had debug
mode enabled. But flag should be renamed for
clarity sake.
eerrrr …
wtf do I monitor for?

41.
More Problems
"I have twenty microservices and a sharded db and
three other data stores across three regions, and
everything seems to be getting a little bit slower
over the past two weeks but nothing has changed
that we know of, and oddly, latency is usually back to
the historical norm on Tuesdays.”
“All twenty app micro services have 10% of available
nodes enter a simultaneous crash loop cycle, about
five times a day, at unpredictable intervals. They have
nothing in common afaik and it doesn’t seem to
impact the stateful services. It clears up before we
can debug it, every time.”
“Our users can compose their own queries that we
execute server-side, and we don’t surface it to them
when they are accidentally doing full table scans or
even multiple full table scans, so they blame us when
they get timeouts.”
(microservices)

42.
Still More Problems
“Several users in Romania and Eastern Europe are
complaining that all push notifications are down for
them … for days. But that’s impossible, because
pushes are in a single shared queue, and I’m
receiving pushes right now!”
“Disney is complaining that once in a while, but not
always, they don’t see the photo they expected to
see — they see someone else’s photo! When they
refresh, it’s fixed.”
“Sometimes a bot takes off, or an app is featured on
the iTunes store, and it takes us a long long time to
track down which app or user is generating
disproportionate pressure on shared components of
our system (esp databases). Everything gets slower
at once, and we can’t tell which of the slow apps
caused it (because EVERYTHING’s slow).
“We run a platform, and it’s hard to
programmatically distinguish between problems
that users are inflicting themselves and problems in
our own code, since they all manifest as the same
errors codes or timeouts."
(microservices)

43.
You have an observable system
when your team can quickly and reliably diagnose
any new behavior with no prior knowledge.
observability begins with
rich instrumentation, putting you in
constant conversation with your code
well-understood systems require
minimal time spent firefighting

44.
kick-start the virtuous cycle of you build it, you own it
instrumenting two steps in front of you as you build
never accept a PR unless you’ll know when it breaks
watch your code go out. muscle memory.
working as intended? anything else look weird?
thru the lens of your instrumentation
O.D.D.
that’s observability-driven development

45.
on call: where shit gets real.
on call is for everyone who writes code.
on call must not be terrible.
(software ownership is the only way to make it better.)
democratize production.
production is for everyone; build guard rails.
encourage curiosity, emphasize ownership. don't punish.
get up to your elbows in prod EVERY DAY
Tools

46.
invest in your deploys, instrument everything
fulfill the promise of Continuous Delivery
(don’t be scared by regulations)
feature flags,
feature flags,
feature flags.
progressive deploy $ALLTHETHINGS
✨Production First✨
test in prod
let staging take the leftovers
SLOs!

47.
engineer merges diff. hours pass, multiple other engineers merge too
someone triggers a deploy with a few days worth of merges
the deploy fails, takes down the site, and pages on call
who manually rolls back, then begins git bisecting
this eats up her day and multiple other engineers
everybody bitches about how on call sucks
insidious
loop:
time elapsed: several engineer-days 🥺💀

48.
engineer merges diff, which kicks off an automatic CI/CD and deploy
deploy fails; notifies the engineer who merged, reverts to safety
who knows exactly what she just did, and swiftly fixes it
then adds tests & instrumentation to better detect it
and promptly commits a fix
total time elapsed: 10 engineering minutes
virtuous
loop:

49.
It really, really, really,
really, really
pays off
to be on a
high performing team.
Like REALLY.

50.
In order to spend more of your time on productive activities,
instrument, observe, and iterate on the tools and processes
that gather, validate and ship your collective output as a team.
Join teams that honor and value this work and are committed to
consistently improving internal tooling — not just shipping features.
Speed is safety. Get code into production within
minutes as the best preventive medicine.

51.
Build or buy?
Focus relentlessly on your core business differentiators.
Engineering cycles are the scarcest currency in your universe.
Build reluctantly. All code is legacy. Kill your darlings.
Senior engineers: you must amplify hidden costs

52.
Promote people for successfully offloading and outsourcing.
Whatever you praise and promote people for, you will see more of.
Practice vendor engineering.
Good vendors act like they’re on your team.
Build libraries, modules, shared interfaces, examples, docs,
relationships; drive consistent internal use cases.
Tools

53.
Socio-
Technical
Systems
sociotechnical (n)
Your system is a snowflake
a unique puzzle, unlike any other
high-performing teams both contribute to and are a
consequence of a well-running sociotechnical system.

54.
for extra fun … let’s examine the sociotechnical implications of the
predominant architecture models of the past two decades:
monoliths and microservices

55.
Monolith
• THE database
• THE application
• Known-unknowns and mostly
predictable failures
• Many monitoring checks and noisy
paging alerts
• "Flip a switch" to deploy, changes are
big bang and binary (all on/all off)
• Failures to be prevented
• Production is to be feared
• Debug by intuition and scar tissue of
past outages, page bombs
• Canned dashboards, runbooks,
playbooks
• Deploys are scary
• Masochistic on-call culture
sociotechnical causes & effects
“technical” causes: “socio” effects:

56.
Monolith
• We built our systems like glass castles
— a fragile, forbidding edifice that we
could tightly control access to.
• Very hostile to exploration or
experimentation

57.
• Many storage systems, many services,
many polyglot technologies
• Unknown-unknowns dominate
• Every alert is a novel question
• Rich, flexible instrumentation
• Few paging alerts, tied to SLOs and
keying off user pain
• Failures are your friend
• A deploy is just the beginning of
gaining confidence in your code
• Debug methodically by examining the
evidence and following the crumbs
• Deploys are opportunities
• On-call must be sustainable, humane
sociotechnical causes & effectsMicroservices
“technical” causes: “socio” effects:

58.
• Software ownership -- you build it,
you run it
• Robust, resilient, built for
experimentation and testing in prod
• Human scale, with guard rails for
safety
Microservices

59.
where
are we
going?

60.
Here's the dirty little secret.
The next generation of systems won't be built and run by burned out, exhausted
people, or command-and-control teams just following orders.
It can't be done.
they've become too complicated. too hard.

61.
You can no longer model these systems in your head and
leap to the solution -- you will be readily outcompeted by
teams with better tools or sharper focus.
Our systems are emergent and unpredictable. Runbooks and
canned playbooks be damned; we need your full creative self.

62.
Your labor is a scarce and precious resource.
Lend it to those who are worthy of it.
You only get one career; seek out high-performing teams
to spend more time learning and building, not mired in
tech debt and shitty, wasteful processes

63.
we have an opportunity here to make things better
let's do it <3

64.
Charity Majors
@mipsytipsy

65.
Liz Fong-Jones
Principal Developer Advocate, Honeycomb
@lizthegrey
November 16, 2020
Detangling complex systems
with compassion & production excellence
1w/ illustrations by @emilywithcurls!

66.
@lizthegrey
2
We write code to solve problems.

67.
@lizthegrey
But our job isn't done upon commit.
3

68.
@lizthegrey
Production is increasingly complex.
4

69.
@lizthegrey
Especially with microservices.
5

70.
@lizthegrey
And with big data.
6

71.
@lizthegrey
We're adding complexity all the time.
7

72.
@lizthegrey
but can't understand or tame it.
8

73.
@lizthegrey
What does uptime mean?
9

74.
@lizthegrey
Is it measured in servers?
10

75.
@lizthegrey
Is it measured in complaints?
11

76.
@lizthegrey
How about juggling everything else?
12

77.
@lizthegrey
We're adding even more complexity.
13

78.
@lizthegrey
Our heroes are exhausted.
14

79.
@lizthegrey
Our strategies need to evolve.
15

80.
@lizthegrey
Don't "buy" DevOps.
16

81.
@lizthegrey
When we order the alphabet soup...
17

82.
@lizthegrey
Noisy alerts. Grumpy engineers.
18

83.
@lizthegrey
Walls of meaningless dashboards.
19

84.
@lizthegrey
Incidents take forever to fix.
20

85.
@lizthegrey
Everyone bugs the "expert".
21

86.
@lizthegrey
Deploys are unpredictable.
22

87.
@lizthegrey
There's no time to do projects...
23

88.
@lizthegrey
and when there's time, there's no plan.
24

89.
@lizthegrey
The team is struggling to hold on.
25

90.
@lizthegrey
What are we missing?
26

91.
@lizthegrey
We forgot who operates systems.
27

92.
@lizthegrey
Tools aren't magical.
28

93.
@lizthegrey
Invest in people, culture, & process.
29

94.
@lizthegrey
Enter the art of
Production Excellence.
30

95.
@lizthegrey
Make systems more reliable & friendly.
31

96.
@lizthegrey
ProdEx takes planning.
32

97.
@lizthegrey
Measure and act on what matters.
33

98.
@lizthegrey
Involve everyone.
34

99.
@lizthegrey
Build everyone's confidence.
Encourage asking questions.
35

100.
@lizthegrey
How do we get started?
36

101.
@lizthegrey
Know when it's too broken.
37

102.
@lizthegrey
& be able to debug, together when it is.
38

103.
@lizthegrey
Eliminate (unnecessary) complexity.
39

104.
@lizthegrey
Our systems are always failing.
40

105.
@lizthegrey
What if we measure too broken?
41

106.
@lizthegrey
We need
Service Level Indicators
42

107.
@lizthegrey
SLIs and SLOs are common language.
43

108.
@lizthegrey
Think in terms of events in context.
44

109.
@lizthegrey
45

110.
@lizthegrey
Is this event good or bad?
46

111.
@lizthegrey
Are users grumpy? Ask your PM.
47

112.
@lizthegrey
Or do chaos engineering experiments.
48

113.
@lizthegrey
What threshold buckets events?
49

114.
@lizthegrey
HTTP Code 200? Latency < 100ms?
50

115.
@lizthegrey
51

116.
@lizthegrey
How many eligible events did we see?
52

117.
@lizthegrey
53

118.
@lizthegrey
Availability: Good / Eligible Events
54

119.
@lizthegrey
Set a target Service Level Objective.
55

120.
@lizthegrey
Use a window and target percentage.
56

121.
@lizthegrey
99.9% of events good in past 30 days.
57

122.
@lizthegrey
58

123.
@lizthegrey
A good SLO barely keeps users happy.
59

124.
@lizthegrey
Drive alerting with SLOs.
60

125.
@lizthegrey
Error budget: allowed unavailability
61

126.
@lizthegrey
How long until I run out?
62

127.
@lizthegrey
Page if it's hours.
63
Ticket if it's days.

128.
@lizthegrey
64
Uh oh, better wake someone up.

129.
@lizthegrey
Data-driven business decisions.
65

130.
@lizthegrey
Is it safe to do this risky experiment?
66

131.
@lizthegrey
67

132.
@lizthegrey
Should we invest in more reliability?
68

133.
@lizthegrey
Perfect SLO > Good SLO >>> No SLO
69

134.
@lizthegrey
Measure what you can today.
70

135.
@lizthegrey
Iterate to meet user needs.
71

136.
@lizthegrey
Only alert on what matters.
72

137.
@lizthegrey
SLIs & SLOs are
only half the picture...
73

138.
@lizthegrey
Our outages are never identical.
74

139.
@lizthegrey
Failure modes can't be predicted.
75

140.
@lizthegrey
Support debugging novel cases.
In production.
76

141.
@lizthegrey
Avoid siloed data.
77

142.
@lizthegrey
Allow forming & testing hypotheses.
78

143.
@lizthegrey
79

144.
@lizthegrey
Dive into data to ask new questions.
80

145.
@lizthegrey
81

146.
@lizthegrey
Our services must be observable.
82

147.
@lizthegrey
Can you examine events in context?
83

148.
@lizthegrey
84

149.
@lizthegrey
Can you explain the variance?
85

150.
@lizthegrey
using relevant dimensions?
86

151.
@lizthegrey
Can you mitigate impact & debug later?
87

152.
@lizthegrey
Observability goes beyond break/fix.
88
OPERATIONAL
RESILIENCE
MANAGED
TECH DEBT
QUALITY
CODE
PREDICTABLE
RELEASE
USER INSIGHT

153.
@lizthegrey
Observability isn't just the data.
89
DATA
INSTRUMENT QUERY

154.
@lizthegrey
SLOs and Observability go together.
90

155.
@lizthegrey
But they alone don't
create collaboration.
91

156.
@lizthegrey
Heroism isn't sustainable.
92

157.
@lizthegrey
Debugging is not a solo activity.
93

158.
@lizthegrey
Debugging is for everyone.
94

159.
@lizthegrey
Train teams together.
95

160.
@lizthegrey
Collaboration is interpersonal.
96

161.
@lizthegrey
97

162.
@lizthegrey
Lean on your team.
98

163.
@lizthegrey
We learn better when we document.
99

164.
@lizthegrey
Fix hero culture. Share knowledge.
100

165.
@lizthegrey
Use the same platforms & tools.
101
(e.g. )

166.
@lizthegrey
Reward curiosity and teamwork.
102

167.
@lizthegrey
Learn from the past.
Reward your future self.
103

168.
@lizthegrey
104

169.
@lizthegrey
Outages don't repeat, but they rhyme.
105

170.
@lizthegrey
Risk analysis
helps us plan.
106

171.
@lizthegrey
Quantify risks by frequency & impact.
107

172.
@lizthegrey
Which risks are most significant?
108

173.
@lizthegrey
Address risks that threaten the SLO.
109

174.
@lizthegrey
Make the business case to fix them.
110

175.
@lizthegrey
And prioritize completing the work.
111

176.
@lizthegrey
Don't waste time chrome polishing.
112

177.
@lizthegrey
Lack of observability is systemic risk.
113

178.
@lizthegrey
So is lack of collaboration.
114

179.
@lizthegrey
115
Success doesn't demand heroism.

180.
@lizthegrey
A dozen engineers build Honeycomb.
116

181.
@lizthegrey
We make systems humane to run,
117

182.
@lizthegrey
by ingesting telemetry,
118

183.
@lizthegrey
enabling data exploration,
119

184.
@lizthegrey
and empowering engineers.
120

185.
@lizthegrey
Yes, we deploy on Fridays.
121

186.
@lizthegrey

187.
@lizthegrey
What's our recipe?

188.
@lizthegrey
Observability-driven Development.

189.
@lizthegrey
start with lead time. (<3 hours)
deploy frequency goes up. (hourly, >12x/day)
change fail rate goes down. (<0.1%)
time to restore goes down. (seconds to minutes)
High productivity product engineering:

190.
@lizthegrey
start with lead time.
10 min builds (x3 at worst), 1h for peer review,
hourly push train = 3 hours to deploy a change.

191.
@lizthegrey
start with lead time.
deploy frequency goes up.
Builds go out every hour if there's a change.
1-2 new commits per build artifact.

192.
@lizthegrey
start with lead time.
deploy frequency goes up.
change fail rate goes down.
Increased confidence via testing. Flag-flip or
fix-forward, not emergency rollback. 0.1% fail rate.

193.
@lizthegrey
start with lead time.
deploy frequency goes up.
change fail rate goes down.
time to restore goes down.
Flag flip takes 30 seconds. Rollback to previous
build takes <10 min. Fix-forward takes 20 min.

194.
@lizthegrey
Instrument as we code.

195.
@lizthegrey
Functional and visual testing.

196.
@lizthegrey
Design for feature flag deployment.

197.
@lizthegrey
Automated integration.

198.
@lizthegrey Honeycomb’s trace of Honeycomb build & deploy

199.
@lizthegrey
Human PR review.

200.
@lizthegrey
Automated integration.

201.
@lizthegrey
Green button merge.

202.
@lizthegrey
Auto-updates, rollbacks, & pins.

203.
@lizthegrey
Observe behavior in prod.

204.
@lizthegrey
Prod: customers observe data.

205.
@lizthegrey
Dogfood observes prod.

206.
@lizthegrey
[add observe in prod] image:
Adoption curve on SLOs

207.
@lizthegrey
Kibble observes dogfood.

208.
@lizthegrey
That's how 12 eng deploy 12x/day!

209.
@lizthegrey
Buy the right tools...
145

210.
@lizthegrey
but season your soup with ProdEx.
146

211.
@lizthegrey
Measure. Debug. Collaborate. Fix.
147
lizthegrey.com; @lizthegrey
/liz
Production Excellence &
bring teams closer together.

212.
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