Join Gary Gruver and Plutora as they discuss why creating a baseline of your delivery pipeline is the first step to managing and improving your application delivery. Learn Gary’s proven methodology to scale Agile and DevOps practices to the enterprise and use Plutora to measure both the speed and quality of application delivery.
2. • A Practical Approach to Large-Scale Agile
Development (2012)
• Leading the Transformation: Applying Agile
and DevOps Principles at Scale (2015)
• Starting and Scaling DevOps in the
Enterprise (2016)
3. Systematically Improving Your Delivery Pipeline
Understand Your
Deployment Pipeline
Build and Verify
Automation for a
Single Sub-Pipeline
Verify Environment
to Environment
Farming the
Build Acceptance
Tests
Improve Entire
Delivery Pipeline
as a System
4. PAGE 4
Accelerate: State of DevOps Report
Identifies key software delivery
performance metrics and highlights
correlation between IT and
organizational performance.
• Deployment Frequency
• Mean Lead Time
• Mean Time to Recovery
• Change Failure Rate
What the
industry is
talking about…
Comparing the elite group against low performers,
the report finds that elite performers have:
46xMORE FREQUENT
CODE DEPLOYS
2555xFASTER LEAD TIME FROM
COMMIT TO DEPLOY
7xLOWER RATE OF
CHANGE FAILURE
2604xTIME TO RECOVER
FROM INCIDENTS
5. PAGE 5
Cycle Time / Lead Time / Non-value Add Time
Value Stream > Code Check-in
Product
opportunity
assessment
Product
discovery
Product
planning &
estimation
Development
Final testing &
approval
Release
Value-added time
Elapsed time
3 days
1 week 10 days
1 week
3 days
10 days 7 weeks
5 days 2 days
1 week 2 hours
13. PAGE 13
Pick a stage in the DP, a stage or
gate. Take a known good
environment, rerun tests
Step 2:
Build & Verify
Automation
14. PAGE 14
Unit Test Stability
Test Case 1
Test Case 2
Test Case 3
Test Case 4
Test Case 5
Test Case 6
Test Case 7
Test Case 8
Test Case 9
Test Case 10
17. The Plutora
Platform
A combination of people, process,
and technology that maps,
optimizes, visualizes, and governs
business value flow (including epics,
stories, and work items) through
heterogeneous enterprise software
delivery pipelines
- FORRESTER
22. Subsystem I
Subsystem II
Subsystem III
Stage 3
Stage 6Stage 4
BAT
Stage 5
Regression Production
4 Hours
16 Hours
3 Hours 2 Weeks 18 Hours
1 Week
3 Days
1 Day to deploy
2 Days to test
3 Days
Cycle Time and Batch Size Map
28. PAGE 28
Step 5: Improve the Entire Delivery
Pipeline as a System
Product
opportunity
assessment
Product
discovery
Product
planning &
estimation
Development
Final testing &
approval
Release
Value-added time
Elapsed time
3 days
1 week 10 days
1 week
3 days
10 days 7 weeks
5 days 2 days
1 week 2 hours
29. PAGE 29
Understanding
the Work
RELEASE READINESS
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10 Day 11 Day 12 Day 13
0
100
200
300
600
700
0
20
100
120
140
160
40
60
80
400
500
Defects
Stories - Branch Ready
Stories - Not Ready for Branching
Daily Green Build
Test Passing Rate
No Green Build
100
97
95
85
82
79
7676
727272
79
83
#
NUMBEROFSTORIES
PERCENTPASSINGRATE
Release Branch Prod Release
#
32. PAGE 32
Transform Data
into Contextual
Insights
Powerful analytics architecture and
data discovery
• Time-based analysis
• Complex filtering of data
• Captures a wide range of delivery
metrics
• Flexible visualization
36. PAGE 36
Upcoming Webinar
Join Gary Gruver and Ted Youel
as they discuss Ted’s journey
applying the principles from
Gary’s books with his team at
Optum Technologies.
Learn from his experiences, including how to:
• Systematically remove waste and inefficiency from
the deployment pipeline
• Rally organizational support for successful transformation
• Achieve tangible business results
Gary Gruver
President
Ted Youel
Sr. Principal Engineer
38. OFFICES
Santa Clara, California
Sydney, Australia
London, United Kingdom
FOUNDED IN 2011
AWARDS
Inc. 5000
EMA DevOps 2020
Deloitte Technology Fast 500
Red Herring Top 100 Winner
WWW.PLUTORA.COM