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@nicolefv
Are we there yet?
Signposts on your journey
to AWESOME
Nicole Forsgren, PhD
CEO and Chief Scientist
DevOps Research and Assessment (DORA)
@nicolefv
Who (What?) is DORA?
@nicolefv
@nicolefv
Signposts
• Direction, not destination
• Your DevOps direction
• Moving along your journey
• Checking progress
• Measures
@nicolefv
@nicolefv
Maturity models are for CHUMPS
@nicolefv
@nicolefv
Maturity models are for CHUMPS
@nicolefv
@nicolefv
Direction,
NOT destination
Follow a Continuous
Improvement paradigm
@nicolefv
DevOps Direction?
DevOps: the use of technology,
process, and culture to deliver
value to an organization.
Is there “one metric that matters”?
@nicolefv
Our direction in DevOps
IT Performance: developing and delivering
software with both speed and stability
- Deploy frequency
- Lead Time for Changes
- Mean Time to Recover (MTTR)
- Change fail rate
More	frequent
Code	deployments
46x
That’s	the	difference	between	multiple	
times	per	day	and	once	a	week	or	less.
Faster	lead	time	from	commit	
to	deploy
440x
That’s	the	difference	between	less	than
an	hour	and	more	than	a	week.
@nicolefv
faster	mean	time	to	recover	
from	downtime
96x
That	means	high	performers	recover	in
less	than	an	hour	instead	of	several	days.
as	likely	that	changes	will	fail
1/5x
That	means	high	performers’	changes	fail	7.5%	of	the	
time	instead	of	38.5%.
@nicolefv
@nicolefv
@nicolefv
Is this the DevOps Journey?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
@nicolefv
But wait.
Tech transformations
are HARD.
@nicolefv
@nicolefv
J curve
The WORK
High speed
High stability
High innovation
High retention
Low speed
Low stability
Low innovation
Low retention
@nicolefv
Some evidence of the J curve
• 2016 State of DevOps Report: unplanned rework
• 2017 State of DevOps Report: manual work
High Medium Low
21% 32% 27%
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Why do we care?
Why even start this journey?
Why hit that dip in the J-curve?
@nicolefv
@nicolefv
High Performing organizations are twice
as likely to achieve or exceed goals
Commercial Goals
• Productivity
• Profitability
• Market Share
• # of customers
@nicolefv
High Performing organizations are twice
as likely to achieve or exceed goals
Commercial Goals
• Productivity
• Profitability
• Market Share
• # of customers
Non-Commercial Goals
• Quantity of Products or
Services
• Operating efficiency
• Customer satisfaction
• Quality of products or
services provided
• Achieving organizational
and mission goals
@nicolefv
But wait, there’s more!
• Once you’re a High Performer, there’s evidence that you can
overcome the mythical man month.
Etsy Code Deployment
What once required 6-14 hours and an “Army”
…Now takes 15 minutes and 1 person
2013 Mike Brittain, Continuous Deployment: The Dirty Details
3/2014 Daniel Schauenberg , Qcon London
4/2014 tweet @philkates
30+Deploys
per day
2013
50Deploys per day
March 2014
QCon London
80-90Deploys per day
April 2014
ChefConf
@nicolefv
High	(linear)
Low
Med
Source: Puppet Labs 2015 State Of DevOps: https://puppetlabs.com/2015-devops-report
deploys/day
# of developers
@nicolefv
#worth
@nicolefv
@nicolefv
Your DevOps Signposts
• IT Performance: Direction
• Deploy frequency
• Lead time
• MTTR
• Change fail rate
• Look for improvements in all four
• We know that all four in tandem are possible
• Watch for: sustained tradeoffs!
• Not possible to see or notice if you aren’t measuring!
@nicolefv
Your DevOps Signposts
• Waste Work: Detours (J-curve)
• Unplanned rework
• Manual work
• Quality proxies (specific to your context)
• Defect incidents, security remediation
These help you judge the depth and breadth of
your J-curve
@nicolefv
One final (important) check
•Is this sustainable?
• Deploy pain
• Burnout
@nicolefv
Microsoft Engineering: DevOps Lessons
Thiago Almeida -- DevOps Days London, 2016
Work/Life Scores
Before DevOps:
38%
After DevOps:
75%
@nicolefv
We know our signposts for our
journey.
But how do we move from
Low to Medium to High
Performance?
@nicolefv@nicolefv
@nicolefv
We know there are key capabilities
that drive IT Perf
•They fall into four categories:
•Tech and automation
•Process
•Measurement/monitoring
•Culture
@nicolefv
Tech and automation
• Version control
• Deployment automation
• Continuous integration
• Trunk-based development
• Test automation
• Test data management
• Shift left on security
• Continuous delivery
• Loosely-coupled architecture
• Architect for empowered teams
@nicolefv
Process
• Gather and implement customer feedback
• Work in small batches
• Lightweight change approval process
• Team experimentation
@nicolefv
Trunk-based development & change
approval process
By focusing on trunk-based development
and streamlining their change approval
processes, Capital One saw stunning
improvements in just two months.
@nicolefv
Measurement and Monitoring
• Visual management
• Monitoring for business decisions
• Check system health proactively
• WIP limits
• Visualizations
@nicolefv@nicolefv
@nicolefv
Culture
• Westrum organizational culture
• Climate for learning
• Collaboration among teams
• Make work meaningful
• Transformational leadership
@nicolefv
Westrum Organizational Culture
Pathological
Power-oriented
Bureaucratic
Rule-oriented
Generative
Performance-oriented
Low cooperation Modest cooperation High cooperation
Messengers shot Messengers neglected Messengers trained
Responsibilities shirked Narrow responsibilities Risks are shared
Bridging discouraged Bridging tolerated Bridging encouraged
Failure leads to scapegoating Failure leads to justice Failure leads to inquiry
Novelty crushed Novelty leads to problems Novelty implemented
@nicolefv@nicolefv
@nicolefv
The hard part
• Prioritizing work
• The quick wins part of the J-curve makes it easy to
figure this out. The growing complexity part makes
this difficult.
@nicolefv
Where should I start?
• “It depends.” Everyone is different
• Patterns I see often:
• Architecture is highest contributor to Continuous Delivery
(SODR 2017) and shows up for very many teams (DORA:
as the need for loosely-coupled architecture or trunk-
based development)
• Lightweight change approval process is a constraint for
most teams (DORA)
• Continuous integration (DORA – and its full complement)
@nicolefv
@nicolefv
So what to do?
1. Identify your constraints. Pick 1-3.
2. Work to eliminate those constraints.
3. Re-evaluate your environment and system.
4. Rinse and repeat.
@nicolefv
Maturity models are for CHUMPS
(redux)
@nicolefv
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
Can both be true?
Low speed
Low stability
Low innovation
Low retention
High speed
High stability
High innovation
High retention
Low Med High
IT Performance
IT Performance
The WORK
@nicolefv
How to measure?
• It’s important to have good metrics, wherever you
get them from
• If you know they’re sh*t, toss them and start over.
• Value a real baseline, even if it’s not encouraging.
@nicolefv
Getting a full picture of your system is
important
•Start now.
•Full system instrumentation takes time.
•Use system and survey measures to give
you coverage.
@nicolefv@nicolefv
@nicolefv
Types of measures to collect
• Data about systems and process from systems
• Data about systems and process from people
• Data about people from people
@nicolefv
Data about systems and process from
systems
• This data is good for:
• Precision
• Continuous data
• Specific data
• Volume/scale
• This data is not good for:
• A holistic view of your system
• Capturing drifts in data
• Capturing behavior outside of the system
• Cultural or perceptual measures
@nicolefv
Data about systems and process from
people
• This data is good for
• Accuracy (if collected w/validated measures)
• A holistic view of your system
• Triangulation with system data
• Capturing behavior outside of the system
• Perceptual measures related to the system (e.g., deploy pain)
• This data is not good for
• Precision (e.g., milliseconds)
• Continuous data - survey fatigue is a thing
• Measures in strained environments (where it is not safe to be honest)
• Volume - once you pass ~20 min, generally bad news
@nicolefv
An example…
Data from people and systems helps us
paint a more complete picture
@nicolefv
One or two
system
metrics might
hint at this:
@nicolefv
More complete system instrumentation
might tell us this:
This image cannot currently be
displayed.
@nicolefv
Our people might tell us this:
@nicolefv
A real world example:
DOES SF 2016, Topo Pal, Capital One
@nicolefv
Data about people from people
• This data is good for:
• Understanding your culture
• Capturing perceptual measures
• Leading indicator
• This data is not good for:
• Continuous data (survey fatigue is a thing)
• Measures in strained environments
• HR system data is only a lagging indicator of what has
already happened
@nicolefv
Employees	in	high-performing	
organizations	are	2.2	times	
more	likely	to	recommend	
their	organization	as	a	great	
place	to	work.
@nicolefv@nicolefv
@nicolefv
Leadership Necessary but not Sufficient
• Teams with the least transformational leaders (the
bottom third) were one-half as likely to be high IT
performers
• Leaders cannot do it alone! Teams with the top 10%
of transformational leaders performed no better
than the median
@nicolefv
What can you do?
• Read and share Data Driven by @dpatil and @hmason
• Ask others about metrics
• Where is metrics collection happening?
• Is it considered key to improvement?
• Think about your own metrics & signposts
• Start with outcomes: IT Performance
• Then think about what influences IT Performance:
technology, process, monitoring, culture.
• Also measure your waste work to track your j-curve
@nicolefv
What we’ve talked about
• Direction, not destination
• Your DevOps direction
• Moving along your journey
• Checking progress
• Measures
@nicolefv
@nicolefv
For more metrics and data:
• ROI whitepaper
• Case studies
• Peer-reviewed research
• 2014 – 2017 State of DevOps Reports
• Learn about assessment
devops-research.com
@nicolefv
Thank you!
@nicolefv
nicolefv.com
devops-research.com
@nicolefv

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