Starting and Scaling DevOps in the Enterprise

Starting and Scaling DevOps in the Enterprise Gary Gruver, Author & Consultant Andrew Phillips, VP of DevOps Strategy, XebiaLabs

2

Housekeeping

▪  This webinar is being recorded ▪  Links to the slides and the recording

will be made available after the presentation

▪  You can post questions via the GoToWebinar Control Panel

3

Meet Your Presenters

Andrew Phillips Gary Gruver

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V I S I B I L I T Y

AUTOMATION

C O N T R O L

§  Continuous Delivery and DevOps pioneer, authority and technology leader

§  Global team in US, Europe & APAC

§  Consistently recognized by leading industry analysts

Intelligence and Automation for the DevOps Enterprise

About XebiaLabs

VISIBILITY

AUTOMATION

CONTROL

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The XebiaLabs DevOps Platform

JIRA HP ALM Version1

Maven Git GitHub

Jenkins Bamboo Shippable

Selenium FitNesse Cucumber

Ms Excel Ms Project Mail Phone

ServiceNow Dynatrace New Relic

DEPLOY

PROVISION

Starting and Scaling DevOps in the Enterprise!

!!

§  FW no longer a bottleneck for the business!

§  Development costs reduced from $100M/yr. to $55M/yr.!

§  140% increase in the number of products under development!

§  Capacity for innovation increased from ~5% to ~40%

© Gruver Consulting



Gene Kim Quote

This is my personal definition: I would define DevOps by the outcomes. In my mind, DevOps is

those set of cultural norms and technology practices that enable the fast flow of planned work from, among others, development, through tests

into operations while preserving world class reliability, operation and security.

DevOps is not about what you do, but what your outcomes are. So many things that we associate

with DevOps fits underneath this very broad umbrella of beliefs and practices—which of

course, communication and culture are part of them.

“

” © Gruver Consulting


Business Ideas Developer Production

Monitoring

Environment Testing


Environment Testing Developer

Business Ideas Production

Monitoring




Monitoring


Monitoring Monitoring



Monitoring


Monitoring How Long � Frequency � Issue Source



Planning Capacity

Requirements Inventory

% Reworking

% Expected Results

Deploy Time & Effort

Source & Number of New Issues

New Issues

Cycle Time Batch Size

Repeatability

Branch Time

Approval Times


Segmenting

Tightly Coupled

Loosely Coupled

Non Business Critical


Tightly Coupled Architecture

A B C

E F G H I J

D

K

L M

Service Virtualization



Segment with SV A B C

D

E F G

H I J

K

L M

Subsystem I

Subsystem II

Subsystem III




Subsystem I Deployment Pipeline

D

C

B

A A

B

C

D

Phase 2 & 3

A B C D

Subsystem I

Subsystem II

Subsystem III

Stage 3

Stage 4

BAT

Stage 6 Stage 5

Regression Production

Full System Deployment Pipeline

Subsystem I

Subsystem II

Subsystem III

Stage 3

Stage 6 Stage 4

BAT

Stage 5


Full System Deployment Pipeline


Subsystem I

Subsystem II

Subsystem III

Stage 3

Stage 6 Stage 4

BAT

Stage 5


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


Subsystem II

Stage 5

Regression

Subsystem III

Stage 3

Stage 6 Stage 4

BAT Production

Subsystem I

Code Environment Test Deploy

§  Leadership vs Empowerment!

§  Specialization vs Generalist!

§  Push to Production!

§  Green Builds & Quality Gates


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Questions?

VISIBILITY

AUTOMATION

CONTROL

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Next Steps

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Starting and Scaling DevOps in the Enterprise