Devops and Sigma Shifts
Business transformation goes greek
Lori MacVittie@lmacvittieSr. Product Manager, Emerging Technologies
σ
What is Devops?
@lmacvittie #DevopsSummit
Devops is a verbDev ops (v) The operationalization of application deployments.
@lmacvittie #DevopsSummit
Operations
• Error Prone Process• Difficult to Debug • Time Consuming
Manual / Scripted Configuration
Application Infrastructure
Application Security
Identity and AccessLocal Load
BalancingApplication
PerformanceApplication
ProxiesWeb & App
Servers
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Operations
• Simplifies troubleshooting & rollback • Consistent, predictable and repeatable process execution • Captures tribal knowledge
Scripting and APIs
Application Infrastructure
Application Security
Identity and AccessLocal Load
BalancingApplication
PerformanceApplication
ProxiesWeb & App
Servers
Automation and
Orchestration
@lmacvittie #DevopsSummit
Proving the Value
48% say biggest difficult in implementing devops is “its value is not understood outside my group”.
2012 DevOps Survey presented by Puppet Labs and IT Revolution Press; Indeed.com @lmacvittie #DevopsSummit
Quantifying the Value of Devops
…without doing devops
@lmacvittie #DevopsSummit
Sigma ShiftsA sigma shift is a measurable improvement in the execution of a process.
@lmacvittie #DevopsSummit
σ
Z = SL – σ
Z = sigma scoreSL = specification limit x = the mean
σ = standard deviation
Sigma Calculations
@lmacvittie #DevopsSummit
TranslationYou can improve the quality of a process by reducing variation in measurable
outcomes.
@lmacvittie #DevopsSummit
CPRConsistent Predictable Repeatable
Error Rates Time to Deploy Frequency
@lmacvittie #DevopsSummit
Baseline
1 Define the measurement and the tolerable upper and acceptable lower limits (ULS and LLS)
2 Collect the data
3 Do the maths
4 Model improvement
@lmacvittie #DevopsSummit
Predictive Powers
@lmacvittie #DevopsSummit
Time to Deploy (days) Time to Deploy (days) Time to Deploy (days)
8 4 2
16 8 4
18 9 4
20 10 5
17 8 4
15 7 3Mean 15.67 7.67 3.67StdDev 4.13 2.07 1.03USL 5 5 5LSL 3 3 3AVG-LSL 12.67 4.67 0.67USL-AVG -10.67 -2.67 1.33Sigma Level -2.58 -1.29 .65Probability of SLA failure 100% 90% 26%
Error Rate (minutes troubleshooting)
Error Rate (minutes troubleshooting)
Error Rate (minutes troubleshooting)
90 45 22
40 20 10
70 35 20
20 10 5
360 180 90
100 50 25
Mean 113.33 56.67 28.67StdDev 124.53 62.26 30.99USL 60 60 60LSL 10 10 10AVG-LSL 103.33 46.67 18.67USL-AVG -53.33 3.33 31.33Sigma Level -0.43 0.05 1.01Probability of failure 67% 48% 16%
Time to Deploy (days) Time to Deploy (days) Time to Deploy (days)
Configure Web Server 8 8 8
Configure App Server 16 8 16
Configure Firewall 18 18 1
Configure Load Balancer 20 10 20
Configure Acceleration 17 17 17
Configure Security 15 15 15Mean 15.67 12.67 12.83
StdDev 4.13 4.55 7.03
USL 5 5 5
LSL 3 3 3
AVG-LSL 12.67 9.67 9.83
USL-AVG -10.67 -7.67 -7.83
Sigma Level -2.58 -1.69 -1.11
Probability of failure 100% 95% 87%
GIGO
Automating poor processes accelerates the rate of failure@lmacvittie #DevopsSummit
@lmacvittie #DevopsSummit
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