The document discusses modern approaches to application lifecycle management (ALM). It notes that the way software is developed is changing, with modern applications focusing on rapid feedback, continuous delivery, and deployment on elastic infrastructure. It advocates dividing ALM tasks between those requiring algorithmic emphasis like continuous integration and those requiring heuristic emphasis like design. The goal is to support high-performance teams, revitalize architectures, and make the development process social, fun and rewarding.

1. Making Leaders Successful
Every Day

2. Modern Applications – Modern ALM
Jeffrey S. Hammond, Vice President & Principal Analyst
@jhammond
August 21, 2014

3. The best way to have a good idea…
Source: Flickr (http://profiles.nlm.nih.gov/ps/retrieve/Narrative/MM/p-nid/55/p-visuals/true)

4. Software innovation used to be expensive…
“When I built my first company in 1999 it cost $2.5
million in infrastructure just to get started and
another $2.5 million in team costs to code, launch,
manage, market and sell our software. So it’s not
surprising that typical “A rounds” of venture
capital were $5 to $10 million.”
Mark Suster, GRP Partners
…but what if innovation with software
now cost 90% less than it used to?

5. The way we develop is changing…
7 Traits of Modern Applications
1. Omni-channel clients
2. Deployed on elastic
infrastructure
3. Aggregate discrete services
4. Use managed APIs
5. Integrate open source
software
6. Employ dev-ops techniques
7. Focus on measurable
feedback
Source: Flickr http://upload.wikimedia.org/wikipedia/commons/6/65/HP_garage_front.JPG)

6. Modern applications are complex
© 2013 Forrester Research, Inc. Reproduction Prohibited 6

7. Context Is The Key To Modern Application
© 2014 Forrester Research, Inc. Reproduction Prohibited

8. We need to prioritize and modernize
the architectures we build

9. Building Modern
Applications is hard!
Are you Agile enough?
Do you collect (and incorporate)
rapid feedback?
Can you design useful, usable,
desirable experiences?
Does your infrastructure evolve?
Can you build high quality, multichannel, 5 star apps?
Source: Flickr (http://www.flickr.com/photos/kaz25/2444344463/sizes/o/in/photostream//)

10. Modern Applications shift ALM focus
Systems of
Engagement
Time to Feedback
Time to Certainty
Time to Safety
Systems of
Automation
Systems of
Record
Lifecycle Focus

11. Adapting Agile principles
› Use personas to drive insight
› Create journey maps
› Wireframes and prototypes build
backlog
› Feedback not requirements
documents
› Kanban boards to manage atomic
demand
› Analytics built into applications

12. A Multi-channel journey map
Wow
Enjoyable
Functional
Neutral
Missed It
Frustrating
Awareness Consideration Research Purchase Engagement
1
2
3
4
5
6
7 8
9
10
Describe each
step in the
journey, the
customer’s
needs and
perceptions
11
Identify
customer and
stages of
journey
Indicate
Indicate
significant
primary (and
secondary )
devices for
each step
steps
Persona:
James

13. Modern applications are complex systems
Complex
Unknowable
Probe, sense, respond
Complicated
Knowable
Sense, analyze, respond
Chaos
Turbulent and unconnected
Act, sense, respond
Simple
Known
Sense, categorize, respond
Disorder
Feedback
Established Practices
Using the Cynefin framework
Hat Tip: Simon Bennett

14. We don’t how to make Modern Applications
Complex
Unknowable
Complicated
Knowable
Chaos
Turbulent and unconnected
Simple
Known
Disorder
Feedback
Established Practices
Systems of
Engagement
Systems of
Operation
Systems
of Record

15. Modern applications evolve
Amazon deployment stats (May -2012)
› Mean time between
deployments – 11.6 seconds
› Max # deployment/hour – 1079
› Mean # of hosts simultaneously
receiving a deployment – 10K
› Max # of hosts simultaneously
receiving a deployment – 30K
Source: O’Reilly (http://assets.en.oreilly.com/1/event/60/Velocity%20Culture%20Presentation.pdf)
Pictures: http://www.flickr.com/photos/blueridgekitties/4423381216/sizes/l/

16. A typical mobile app release schedule
Features +
Defect fixes
V 1.0
(MVP)
V 2.1
V 2.0
V 1.2.2
V 1.2.1
V 1.2
Regression + Emergency
Patch
New OS
version
released
Regular Internal Sprint Cycle + Beta Testing (2 weeks)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

17. A move toward different ALM processes
› Fewer branches in SCM –
evolve toward DVCS
› Developers test
› CI becomes decentralized,
more atomic, and critical
› You must run and consume
beta
› Mocks and mocking tools help
manage multi layer
complexity

18. Running “experiments”
› Requirements are testable
hypotheses
› Multivariate testing with traffic
routing
› Services are architected for
continuous deployment (e.g. feature
flags, hot patching)
› Releases become more “organic”
› Development moves from an
engineering process model to a
scientific process model
© 2013 Forrester Research, Inc. Reproduction Prohibited 18

19. How do you test? In production!
› Test like you deploy – the last
mile is beyond your control
› Issues are hard to replicate in
isolation
› Big data requires storage
› You need to harden your
services
› Delivered via a new
generation of testing tools
Pictures: http://www.flickr.com/photos/dyanna/3202542828/sizes/l/
Not Quite A Simian Army

20. Continuous Delivery Capability Is Key
Level Focus Characteristics Results
5 Hypothesis-driven
delivery
Requirements include testable metrics
Frequent use of A/B testing
Services designed for CD
DBMS changed decoupled from system
changes
Delivery enables
business
innovation
4 Release on
demand
Teams organized around services
Deployment pipeline rejects bad changes
Work delivered in small batches
Comprehensive test + release automation
Service always in
a releasable state
Capability >= Need
3 Regular
releases w/
milestones
CI and trunk-based development
Automating provisioning and testing
“Done” = tested and deployed
Regular release
cadence
Capability < Need
2 Time-boxed
releases
Clear product ownership
Change management controls
<1 mo. cycles
Some testing, release automation
Planned releases
Capability < Need
1 Heroic
individuals
Manual testing
Integration explosion
Manual provisioning
Ad-hoc releases
http://bit.ly/10hUmK3

21. 21
Shorter time-to-feedback = faster time-to-value
Feedback drives improved
customer experience and
business results
› The faster the feedback, the
less waste.
› The less waste, the lower the
cost.
› Faster feedback means better
results to customers, faster.
› Happier customers = more
customers, increased revenue.
› Increased revenue and lower
cost = better business results.
Source: November 18, 2013, “Measuring Mobile Apps” Forrester report

22. What if everything you’ve
been told about managing
developers was wrong?
22 Entire contents © 2010 Forrester Research, Inc. All rights reserved.

23. Software supply chains become social
› Use of OSS and participation in
OSS communities
› Growth of “The Forge” as a
developer’s home base
› Service composition and the death
of NIH
› From Draftsmen -> Craftsmen
› Crowdsourcing for software
innovation
› ALM data will become increasingly
federated
Picture: http://www.flickr.com/photos/mulad/200072198/sizes/l/

24. The public forge: hub of social development
• GitHub
• JazzHub
• Bitbucket
• CodePlex
• Cloudforge
• Sourceforge
Github Growth
Repositories Users
12,000,000
10,000,000
8,000,000
6,000,000
4,000,000
2,000,000
0
Feb-09
Jul-09
Jul-10
Apr-11
Sep-11
Sep-12
Dec-12
Apr-13
Dec-13

25. Competing for commissions

26. NYC Resistor

27. Hackathon culture

28. Atlassian “FedEx Day”

29. Intrinsic motivation dominates development
Source: 2013 Developer Forrsights
© 2012 Forrester Research, Inc. Reproduction Prohibited
I contribute to open source
projects
Yes,
27%
No ,
73%
N=1744
On average, how many hours a week do you spend
programming personal or side projects not related to
your day job?
N=2042
23%
35%
24%
12%
7%
I do not program or develop
on my own time outside my
day job
<5 hours a week
5-10 hours a week
11-20 hours a week
> 20 hours a week

30. What are the potential long term
implications of social development?
› Formation of developer collectives (Drupal)
› Disruption of VC/capital markets (Kickstarter)
› Disruption of sourcing industry – rise of freelancing
› Different BT org models (Holacracy, devops)
› Developer-led social movements (Mozilla vs. OK Cupid)
› Ethical hacking (Angelhack, code for America)
› Rise of alternative learning models - apprenticeship
© 2013 Forrester Research, Inc. Reproduction Prohibited 30

31. Divide ALM development tasks by intent
Algorithmic Emphasis
› Build/Continuous Integration
› Configuration management
› Regression testing
› Static analysis
› Provisioning & Deployment
› Gathering dev analytics
› Defect remediation
› Performance testing
Heuristic Emphasis
› Design
› Development
› Exploratory testing
› Scheduling demand
› Gathering requirements
› Backlog prioritization
› Refactoring
› Performance tuning
ALM Automation ALM Collaboration

32. Manage innovation and cost avoidance differently
Attack Risk
Heuristic Emphasis
$100+/HR Dev Pro
Feedback
Recovery
Innovation Predictability Cost avoidance
High variance
with limited data
Under-estimated
Medium variance
with better data Low Variance w. high confidence data
Over-estimated
Attack Cost
Algorithmic Emphasis
$20/HR Dev Pro
Process Guardrails
Prevention
Uncertainty
Chaotic/Complex/Unknown Complicated/Known Simple
Application Lifecycle
Hat Tip: David Lubanko

33. You need to rethink your approach
1. ALM that’s fit to purpose
2. Revitalize architecture
3. Horizontal, not vertical
4. Support hi-perf teams
5. “Done” is DONE
6. Federate and collaborate
7. Make it social, fun and rewarding!

34. Thank you
Jeffrey Hammond
+1 978.226.8886
jhammond@forrester.com