Violation of known coding Capacity Advanced PostMortem Fu and Human Error 101 (Velocity 2011)

AdvancedPostMortem Fu& Human Error 101 John Allspaw VP, Tech Ops Velocity 2011

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Resilience EngineeringDr. Erik Hollnagel Dr. David Woods Dr. Sidney Dekker Dr. Richard Cook

Complex, Dynamic

Fundamental Surprises

E.T.T.O. Eﬃciency Thoroughness

Organizations, Policies, Procedures, Regulations BLUNT Resources & Constraints

Organizations, Policies, Procedures, Regulations BLUNT Resources & Constraints Slips Adjustments OperatorsCompensations Mistakes Lapses Recoveries Violations Improvisations SHARP

FUTURE +PAST

Why Do Them?

Why?Understand the failure

Why?Understand the system

Where “System” = Networks Servers Applications Processes People

People

(Anticipation) Knowing What To Expect

(Anticipation) Knowing Knowing What What To Expect To Look For (Monitoring)

(Anticipation) (Response) Knowing Knowing Knowing What What What To Expect To Look For To Do (Monitoring)

(Anticipation) (Response) Knowing Knowing Knowing Knowing What What What What To Expect To Look For To Do Has Happened (Monitoring) (Learning)

Microphones are ON?

Event AwarenessCode Deploys

TIMELINE IRC logging = Rich Data

TIMELINE Traces of Data IRC logging = Rich Data

IRC Logs Fed Into Solr

Status BlogTwitter Feed

Flight Data Recorder

Annotation Traces

Investigation Basics

Start?

TTDHow?

TTR

Stable(“all clear”)

Impact Time = TTR - Start

SEVERITY

Severity 1A. Total loss of serviceB. Severe degradation, eﬀectively unusableC. Loss of a critical feature

Severity 2A. Major degradation/feature loss for SUBSET of membersB. Minor degradation/feature loss for ALL members

Severity 3Noticeable non-critical feature loss or degradation

Severity 4No visible impact, loss of redundancy or capacityheadroom

Severity 5No-impact but unexpected failure

5/11/2011 - Payments/Checkout system issue Start 4:10pm TTD 4:15pm TTR 4:30pm Stable 4:35pm Total Impact 20 min Severity 1

• Basic metrics• Timeline with details• Remediations/Observations

“normal” Incident PostMortemoperation Time

How?Why?Prevention?

How

Crisis PatternsProblem Starts PostMortem Time

Crisis PatternsProblem Starts Detection PostMortem Time

Crisis PatternsProblem Starts Detection Evaluation PostMortem Time

Crisis PatternsProblem Starts Detection Evaluation Response PostMortem Time

Crisis PatternsProblem Starts Detection Evaluation Response Stable PostMortem Time

Crisis PatternsProblem Starts Detection Evaluation Response Stable PostMortem Conﬁrmation Time

Crisis PatternsProblem Starts Detection Evaluation Response Stable PostMortem Conﬁrmation All Clear Time

Crisis PatternsProblem Starts Stress Detection Evaluation Response Stable PostMortem Conﬁrmation All Clear Time

Problem Starts Detection Evaluation Response Stable PostMortem Conﬁrmation All Clear Time

Problem Starts Detection Evaluation Response Stable PostMortem Conﬁrmation All Clear Time Internal and External Update Communications

Crisis PatternsProblem Starts Detection Evaluation Response Stable Conﬁrmation All Clear Time

Crisis Patterns

Crisis PatternsForced beyond learned roles

Crisis PatternsForced beyond learned rolesActions whose consequences are both important anddiﬃcult to see

Crisis PatternsForced beyond learned rolesActions whose consequences are both important anddiﬃcult to seeCognitively and perceptively noisy

Crisis PatternsForced beyond learned rolesActions whose consequences are both important anddiﬃcult to seeCognitively and perceptively noisyCoordinative load increases exponentially

Thematic Vagabonding“butterﬂy minds” NOT STUCK ENOUGH

Goal Fixation (encystment)TOO STUCK

HeroismNon-communicating lone wolf-isms

DistractionIrrelevant noise in comm channels

IMPROVISATIONREQUIREMENT for troubleshootingcomplex systems

IMPROVISATION

Why?

Root Cause Analysis“With the unknown, one is confronted with danger,discomfort, and care; the ﬁrst instinct is to abolishthese painful states.First principle: any explanation is better thannone.” Friedrich Nietzsche Twilight of the Idols, or How to Philosophize with a Hammer

Hindsight BiasKnowledge of the outcome inﬂuences theanalysis of the processMakes steps towards failure appearforeseeable and obvious

After The Fact

Reality: Before and During

Hindsight Bias“Should have known better”“All the signs were there, you just needed topay attention”

Hindsight BiasBEFORE accident: The future seems implausibleAFTER accident: Obviously clear: “how could they not see what mistake they were about to make”

Hindsight Bias“...people’s need to be rightis stronger than their abilityto be objective.” N. Crawford American Psychological Association

Outcome BiasJudging a past decisionbased on its outcome.

ID Fishbone/Ishikawa FMEA Five Whys Fault Tree CED CRT

why? OUTAGE

why?because this OUTAGE

why? why? because this OUTAGE

why? why?because because this this OUTAGE

why? why? why? because because this this OUTAGE

why? why? why?because because because this this this OUTAGE

why? why? why?because because because this this this OUTAGE but: WHY?

which causedSome Caused otherAction Some Things things OUTAGE to happen

Sequence-Of-Events

• Satisfyingly simple, easy to explain and document

• Satisfyingly simple, easy to explain and document• Solves for a speciﬁc case• Ignorant of surrounding circumstances• Too focused on components• Validates Hindsight and Outcome bias

NOT HELPFUL• Satisfyingly simple, easy to explain and document• Solves for a speciﬁc case• Ignorant of surrounding circumstances• Too focused on components• Validates Hindsight and Outcome bias

Epidemiological (adapted from Reason, 1990)

(adapted from Reason, 1990)

Holes = Active/Latent Failures,Bad Things™ Waiting to Happen (adapted from Reason, 1990)

Holes = Active/Latent Failures, Bad Things™ Waiting to HappenCheese = Safety Barriers, Layers of Defense (adapted from Reason, 1990)

(adapted from Reason, 1990)

Code Servers (adapted from Reason, 1990)

Code ServersSchedule Training (adapted from Reason, 1990)

Unmonitored Disk Space (latent condition)

Capacity Unmonitored Disk Space Miscalculation (latent condition)(latent condition)

Capacity Unmonitored Disk Space Miscalculation (latent condition)(latent condition) Unit Test In Transition

Violation of known coding Capacity standards Unmonitored Disk Space Miscalculation (latent condition) (latent condition)(latent condition) Unit Test In Transition

Violation of known coding Capacity standards Unmonitored Disk Space Miscalculation (latent condition) (latent condition)(latent condition) Unit Test In Bug Introduced Transition (active failure)

Violation of known coding Capacity standards Unmonitored Disk Space Miscalculation (latent condition) (latent condition)(latent condition) Unit Test In Bug Introduced External API call Transition (active failure) (active failure)

Violation of known coding Capacity standards Unmonitored Disk Space Miscalculation (latent condition) (latent condition)(latent condition) Unit Test In Bug Introduced External API call Transition (active failure) (active failure) FAILURE!

Capacity Miscalculation(latent condition) Unit Test In Bug Introduced External API call Transition (active failure) (active failure)

Capacity Miscalculation(latent condition) Unit Test In Bug Introduced External API call Transition (active failure) (active failure) NO FAILURE!

• Better than dominoes, but still linear layers of “defense”• Helps uncover multiple contributors and latent failures (at sharp and blunt ends)

• Better than dominoes, but still linear layers of “defense”• Helps uncover multiple contributors and latent failures (at sharp and blunt ends)• Doesn’t explain lineups or orientation of holes• Only identiﬁes defects/gaps, nothing more• Still encourages judgements of decisions

Better, but still NOT HELPFUL• Better than dominoes, but still linear layers of “defense”• Helps uncover multiple contributors and latent failures (at sharp and blunt ends)• Doesn’t explain lineups or orientation of holes• Only identiﬁes defects/gaps, nothing more• Still encourages judgements of decisions

Multiple Contributors “each necessary but only jointly suﬃcient”

Resultant Versus Emergent

Systemic DatabaseRouter Memcache Webserver

Systemic DatabaseRouter Memcache Webserver Feature Roadmap

Systemic DatabaseRouter Memcache Last Round Webserver of Funding Feature Roadmap

Systemic Dashboard Design DatabaseRouter Memcache Last Round Webserver of Funding Feature Roadmap

Systemic Dashboard Design Database Router Memcache Last Round Webserver of Funding Feature RoadmapDBA’s car

Systemic Dashboard Design Database Router Memcache Last Round Webserver of Funding Feature Roadmap No EngDBA’s car Training

Systemic Dashboard Design Database Router Memcache Last Round Webserver of Funding Feature Email is Roadmap down No EngDBA’s car Training

Systemic Dashboard Design Database Router Memcache Last Round Webserver of Funding Feature Email is Roadmap down Entire Ops Team No Eng Is AtDBA’s car Training Velocity

Systemic Dashboard Design Database Router Memcache Last Round Webserver of Funding Feature Email is Roadmap down Entire Ops Team No Eng Techcrunch Is AtDBA’s car Training Article Velocity

Systemic Hiring Dashboard Design Difﬁculties Database Router Memcache Last Round Webserver of Funding Feature Email is Roadmap down Entire Ops Team No Eng Techcrunch Is AtDBA’s car Training Article Velocity

Systemic Hiring S3 is slow Dashboard Design Difﬁculties Database Router Memcache Last Round Webserver of Funding Feature Email is Roadmap down Entire Ops Team No Eng Techcrunch Is AtDBA’s car Training Article Velocity

Systemic

Functional ResonanceIn isolation, components act within bounds.Interconnected, they produce emergingbehaviors.

Causes Are Constructed,Not Found WYLFIWYF Pre-conceived notions on “causes” and behaviors

Contributors, not causes

There is no root cause.

LEARNING

Quantifying ResponseTime to detect?Time for escalation, internal notiﬁcation?Time to notify the public?Time to graceful degradation? (feature oﬀ)Time to stable/resolve?Time to all clear?

Qualifying ResponseHigh signal:noise in comm channels?Troubleshooting fatigue?Troubleshooting handoﬀ?All tools on-hand?Metrics visibility?Collaborative and skillful communication?Improvised tooling or solutions?

All Together Now• Start/TTD/TTR/Stable/etc.• Severity• DATA (graphs, IRC, etc.)• Description (timeline, etc.)• Observations (motivations, latent conditions, etc.)• Actions (remediation tickets, followup)

Human Error“...knowledge and error ﬂow from thesame mental sources, only successcan tell one from the other.” Ernest Mach, 1905

Human ErrorNobody comes to work to do a bad job.

Human ErrorUseless as a label and ending point.

Human ErrorHuman error isn’t a cause, it’san eﬀect.

Why did it make senseto the personat the time?

Error Categories• Slips• Lapses• Mismatches• Violations

Error Categories

First Stories“Human error” seen as root cause.Counterfactuals: saying what they “should”have done.Prevention: be “more careful!”

Second Stories“Human error” seen as systemic vulnerabilities,deeper inside the organization.Digging into why it made sense for them to do what theydid, at the time they did it.Prevention...

Why did it make senseto the personat the time?

Substitution TestCould peers have made thesame error under the samecircumstances?

WHERE to learn from ?

Two Propositions

100 deploys6 deploy-related issues

100 > 6

Proposition #1“Ways in which things go right are special casesof the ways in which things go wrong.”

Proposition #1Successes = failures gone wrongStudy the failures, generalize from that. data sources: 6 out of 100

Proposition #2“Ways in which things go wrong are specialcases of the ways in which things go right.”

Proposition #2Failures = successes gone wrongStudy the successes, generalize from thatdata sources: 94 out of 100

94/100 ? OR6/100 ?

What and WHY Do ThingsGo RIGHT?

Not just: why did we fail?But also: why did we succeed?

Near MissesHey everybody -Don’t be like me. I tried to X, butbecause it was no good.It almost exploded everyone.So, don’t do: (details about X) Love, Joe

Taking the New ViewRecognize that human error isan attribution.

Taking the New ViewPursue Second Stories.

Taking the New ViewEscape Hindsight Bias.

Taking the New ViewUnderstand work as performedat the sharp end.

Taking the New ViewExamine how changes (at alllayers) will produce newvulnerabilities.

Taking the New ViewUse technology to support andenhance human expertise.

Taking the New ViewTame complexity through newforms of feedback.

Taking the New ViewRealize that your systems arenot inherently safe.

Taking the New ViewHuman error is an inevitableby-product of strainedcomplex systems.

Taking the New ViewHuman error isn’t at the root ofyour safety problems.

Taking the New ViewHuman error isn’t random.

Just Culture

Just CultureBalancing accountability withlearning.

Intentional Malice

Negligence Found Severity of the Outage

NameBlameShame

Name WHY? Blame#!@%$&#Shame

“Must set an example!”

“Has to be some fear that notdoing one’s job correctly couldlead to punishment.”

“Must set an example!” Punishing Deterrents is a not“Has to be some fear that Losing coulddoing one’s job correctly Propositionlead to punishment.”

Holding People Accountable != Blaming People

Accountability and Learning Punishment For Errors

No Bad ApplesOnly Bad Theories of Error

Name WHY? Blame#!@%$&#Shame

Signs Of Old View“Gross Misconduct”“Carelessness”“Negligence”“Egregious Behavior”“Willful Violations”

Discretionary Spaces

AcceptableUnacceptable

Acceptable (who draws this subjective line?)Unacceptable

Increase Accountability BySupporting Learning

Empower PeopleLet them own their own stories.Don’t make people pay penalties.Allow them to educate the organization.

Reduce UncertaintyMake it clear who deﬁnesacceptable behavior.

Organizational RootsAccountability =Responsibility + Requisite Authority

(Thanks, Fellas)Dr. Erik Hollnagel Dr. David Woods Dr. Sidney Dekker Dr. Richard Cook

Homework!

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