Webinar Agenda: - Benefits of Continuous Deployment in delivering engaging UX - Problems with monolithic architecture - Use of microservices and containers as a solution According to Gartner, a product’s UX is more important than its brand. Containerized microservices using Docker and orchestration tools such as Kubernetes have made it much simpler to deliver a continuous stream of small increments to the product features and functionality. However this advanced capability pays off only when used for building a better UX. Building UX is a journey of a series of experiments to validate triggers that motivate users to take certain actions and rewards that build habits.

1. www.synerzip.com
Lean UX + DevOps
Presented by Vinayak Joglekar, CTO, Synerzip

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About the Speaker
Vinayak Joglekar
Founder & CTO, Synerzip
• Hires & Mentors Agile Software Development Teams
• Over 3 decades of experience in Software Product
Development
• Hands on practitioner of Agile and Lean techniques
• Speaker at 2008 Agile Conference in Toronto
• Hands on experience in QA automation, DevOps,
UX design and CD
• Blogs about trends in software development
• Linkedin Profile: https://www.linkedin.com/in/vinayak-
joglekar-b95329/

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Agenda
• Benefits of CD in building an engaging UX
• Problems with monolithic architecture
• Use of microservices and containers as a solution
.

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Why Do You Do CD?
To be in the state
of readiness to
deploy anytime
I can get
feedback
about my MVP
Fix issues in
time
To validate
product
market fit
To validate
problem
solution fit
For quicker
time to market
To move fast
and break
things like FB

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Survey- Why Do We Do CD
• Only 20% to 30% of the deployments are “frequently
released” to the customer
• Only 70% of the times the feedback is sought
• Then why do we do CD? Because its cool? Why are
companies like Facebook or Netflix deploying so frequently?

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Does CD Really Help?
• Not useful for validating problem-solution fit. That’s
better served by low-fi prototypes
• Not useful to validate product-market fit. In fact we
need to with-hold deploying changes while
monitoring logs to reach conclusion.
• Very useful to observe changes in user behavior
& for building an engaging UX.
• CD builds the confidence to quickly deploy a
feature/change to test a newly formed hypothesis
based on validated learning.

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3 Axes of Customer Engagement
In session
(Matter of
seconds)
In expertise (Weeks)
In lifecycle (Months and years)
Trigger Action Reward Investment
Discovery
On Boarding
Habit Building
Mastery
Expansion
Launch
Beta
MVP

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In Session Engagement
• External Trigger-email, f/b
post, ad. Internal Trigger-
hunger, boredom
• Action-Order food, Open f/b
• Variable reward – see who
liked your last f/b post
(Some suspense there)
• Investment- you are tied to
f/b because of all the friends
made & pictures posted
there
Concept courtesy: Nir Eyal

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Reinforcing Core Loops
Reward has the next trigger embedded
in it. E.g. top half of next set of
recommended movies are visible on
Netflix. Makes the user want to scroll
again- habit forming.
Embedded trigger takes you to the
next level of core loop showing a new
call to action E.g. After searching an
address on Google maps you not only
see the location but icon of a car-
taking you to the next level to search
for driving directions- improving
engagement

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Engagement in Expertise Building
Concept courtesy: Amy Jo Kim

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E-commerce False Summits & Core Loop
Search gives interesting
results. User repeatedly
uses search. User profile
gets built , search history
gets built.
User profile and search
history is used to rank
the search results leading
to the user getting more
engaged and habituated
to use search more often.
Many user profiles get
built. Enough data
becomes available to
mine similar users
Recommendation engine
makes recommendations
based on what users with
similar profile are
searching and buying.
Users post reviews and
ratings of products
bought by them.
Demand forecasting
based on trends of what
users are buying and
liking enables better
availability and quicker
deliveries thus reducing
the time between action
of buying and reward of
getting to use the
product. Purchase history
of users can be mined for
building buying habits
Where can users find
interesting products?
Now that users are able
to find the products can
they compare and rank
those?
How can users get to see
other related products or
what others like them are
buying?
How can we satisfy the
demand with minimal
waiting and delivery
problems?
Every time your product solves a
problem, it adds a loop to the habit
forming core loop. But then
customers start facing the next
problem. Every summit is a false one

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Google Maps False Summits & Core Loop
Google maps gives the
exact location of the
address on the map.
Users add their business
location and other
important pins
Driving directions in text
as well as on the voice.
Options for walking and
public transport. GPS
data of users gets logged
providing traffic data
Traffic data is used to
predict travel time and
organize itinerary by
integration with Google
calendar and travel
booking portals
Integration with Uber ,
Zomato and social medial
sites for users to post
photos of places visited
How can users get a road
map of an address?
Now that users are able
to find the location how
can they reach there?
How can users plan their
itinerary providing for
travel time and meeting
time on their calendar?
How can users get a ride
or see the reviews of
restaurants or see the
pictures of places they
are visiting?
Every time your product solves a
problem, it adds a loop to the habit
forming core loop. But then
customers start facing the next
problem. Every summit is a false one

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User Engagement thru PLC
Prototyping tools->Sketch,Invision,
Axure, Balsamiq, FluidUI, Yeogurt,
Ninjamock, IFTTT, appery.io
MVP Testing-> LaunchRock,
Kickstarter, Usabilityhub, ICO
Better UX by leveraging AI/ ML/NLP BOTs,
Spark, R, Storm, Tensorflow, NLTK, UIIMA,
IBM Watson,GATE. Big data with Hadoop,
Cassandra, Mongo, Neo4j, Redis. Once a
user enters in smart contracts on a blockhain
using a cryptocurrency – its hard to switch
(Investment)
Faster,cheaper & better UX by scaling
thousands of . SpringBoot, Kafka-reactive
micoservices in docker containers
orchestrated by Kubernetes, Swarm,
Rancher, Consul, Zookeeper, lambda.
API (CDC) testing by Pacto, Swagger
Rapid Application Development->
Monolith using PHP (Code Ignitor)
Ruby on Rails or Node,js Silverlight,
Viaduct, Codesmith, Genexus,
Webmatrix, Thymeleaf,WebDynrpo
Concept courtesy: Amy Jo Kim

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Many Hypotheses to Validate
Email?
Social
Media?
Push
Notification?
Watch?
Calendar?
Hunger?
Boredom?
Guest First Visit Repeated
Visits
Contribution
Search
Results
Detailed Info Recommend
ations
Reviews
Browser
History
Personal
Details
Pictures /
Data
Training set/
Blockhain
Contract
Trigger
Action
Reward
Investment
C
o

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Lean Startup Way
• Build-Measure-Learn loop. Companies who
iterate faster do better.
• Measure & Learn parts of the loop don’t take
long. Build is the bottleneck. At times it
takes some build cycles to make results
measurable.
• We need the ability to deploy what is built
and test it in the market – as frequently as
possible.

16. Problems with Monolithic Architecture
1. Dev-Test-Production environments need to be
differently configured.
.

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Problems with Monolithic Architecture – contd.
Monolithic Application
Build
Process
Testing
Process
Build
+ test
Time
Number of changes
6 1
6 containerized microservices
Build
+ test
Time
Number of changes
6 1
Reduced time to build and test

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Microservices Facilitate Hypothesis Validation
DevOps
Dev
OpsQA
Development
Commit Stage
Compile
Basic Tests
Kubernetes
Container
Orchestration
Repository
Repository
Dockerfiles+
Configmaps
Code
Container w/Jenkins+
+Docker daemon
Test
Containers
API Contract
validation/un
it tests
Dockerhub
Docker
Images v1
Docker
Images v3
Docker
Images v2
Pods
Development Test Production
Kubernetes
rolling updates
API test
Stage
UAT Manual Test
Stage
Performance
& Security
Release test
Stage
Bugs Reports
Roll Back
Product
Market
Validation
Learning
From the
Feedback
Next
Hypothesis to
validate
Prioritized
backlog
Continuous
Delivery
Continuous
Deployment
1
2 3
4
5
6
6
7 8
9
10
11
12
13
14
Commit stage: An
automated script
would run compilation,
unit tests, , automated
code review, code
coverage analysis
before the developer
pushes the code into
the repository.
The repository consists
of the source code as
well as
dockerfiles/configmaps
that control the way the
development, test and
production clusters are
composed by
networking/scaling
docker containers.
Continuous integration server kicks a script that
compiles and runs unit tests and API contract
Validation tests on the containerized microservice
Docker files and docker
compose files are used to create
test containers by the docker
demon running in the same
container as Jenkins to create
and test docker images with the
required environment such as
nginx, tensorflow, java, play
framework, PHP etc. If the tests
succeed the images are stored
in the Nexus repository. Test
containers are deleted after
running the tests.
Container orchestration
tools such as Kubernetes
launch needed number of
container instances using
the selected versions of
docker images in
scheduled sequence
networked to communicate
with each other.
Use of container orchestration tools ensure that
instances of new version are launched one by one to
replace old versions. If health checks indicate
problems with new version the process is reversed.
Developers run the commit stage
scripts finally before promoting the
build to the test environment.
.
Testers use automatically
deployed version/build as
detailed in step 5. At this stage
automated user acceptance
tests and performance tests
are carried out in addition to
few manual tests as required.
Bugs if found in this process
are assigned to development
or the build/version is
promoted to production.
.
If the build fails in
production the
deployment is rolled
back and the previous
version stays in
production
Analytics are studied
to ascertain how the
product has fared in
the market. Actual
results are compared
with expected results
Feedback from the
market and cosumer
research is used to
learn why the users
behaved the way they
did
Next hypothesis is
formed on the basis of
the learningBacklog of feature that
will validate the
hypothesis is created.
Expected outcome is
spelt out.

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QA
Evolution of C/S Functional Team
Dev Ops
Dev QA Ops
UX
WATERFALL MODEL 1990s
PO
AGILE DEVELOPMENT 2000s
PM
AGILE+DEVOPS 2010
UX
LEAN UX+AGILE+DEVOPS 2017

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THANK YOU!

21. Subu Sankara
VP, Software Services (SFO Bay Area)
subu@synerzip.com
510.579.9673

22. Your trusted outsourcing partner for
Agile software product development.
Synerzip
• Accelerate the delivery of your product roadmap
• Address technology skill gaps
• Save at least 50% with offshore software
development
• Augment your team with optional on-site
professionals

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Synerzip Clients

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Connect with Synerzip
@Synerzip
linkedin.com/company/synerzip
facebook.com/Synerzip

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Next Webinar
Software Development Dream
Teams
Gel as a Team – Become self-organizing, communicative, collaborative;
whether co-located or distributed
January 25, 2017 at Noon CT
Webinar Presenter:
Ron Lichty, Agile Coach & Consultant

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