Application Modernization: Cloud-native Applications and the path from Le gacy to Ve locity

March 8 th 2018

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1. Application Mode rnization Tre nds2. Mapping the Journe y from Le gacy to

Ve locity3. Q&A.

AGENDA

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“You have to go whole he arte d ly into anything in orde r to achie ve anything worth having .” - Frank Lloyd Wright

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Tre nd 1: App lication Mode rnizationand Dig ita l Transform ation

Application Mode rnization is part of m ost com panie s Dig ita l Transform ation Strate gy. So what is Dig ita l Transform ation?

“Dig ita l” is te chnology im proving hum an pe rform ance .

“Transform ation” is e nab ling innovation and cre ativity to d rive busine ss value , ra the r than s im ply e nhancing and supporting trad itional m e thods”

Across a ll c lie nts , and conside ring e ve ryone as a p roduce r and consum e r.Various le ve ls of m aturity across the organization and p rovid ing the lift from d ig ita l transform ation and “ge tting all b rains in the gam e ”.

Application Modernization Roadmap

D e f i n e – Launch – Acce le rate

Continuous Learning areas:• Cloud / Agile / De vOps/ Archite cture /• Data Scie nce / AI/ Low-code / RPA• De sign/ Structure d Thinking

Crucial management training:• Se rvant Le ade rship• Manag ing High Pe rform ing Te am s• Soft Skills for Dig ita l Transform ation• Application Mode rnization for Le ade rs

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Tre nd 2: Ag ile

Ag ile is an ite rative , tim e -boxe d approach to de live ring incre m e ntal busine ss value . An ag ile approach re quire s a m ove from com m and-and-control to collaborative , se lf-organizing , and cross-functional te am s. Ag ile m e thodolog ie s are use d for software app lication de ve lopm e nt, but le ade rship , archite c ture , contrac ts , and e ng ine e ring all be ne fit from Agile .

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Tre nd 3: De vOps

De vOps is d riving organizational change . This approach involve s app lication of skills , p roce ss im prove m e nt, and tool patte rns to d rive cultural change in Te chnology-Enab le d Busine ss organizations.

De vOps organizations inc lude archite c ture , controls , se curity, and gove rnance to build the m ost e ffic ie nt p ipe line s for the flow of app lications, data , and knowle dge .

Le arning ne ve r e nds.

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Tre nd 4: Machine Le arning and AI

Ke y knowle dge are as: • Inte llige nt apps• Advance d analytics • Conve rsational p la tform s• Adap tive risk and trust asse ssm e nt• Blockchain se curing IoT data colle ction• Robotic Proce ss Autom ation (RPA)

Are as we se e custom e r AI usage : • Chatbots/ AI assis tants• Drive r pe rform ance m onitoring• Insurance m arke t analytics

He llo. We lcom e to Skyne t. How m ay I he lp you?

Trend 5: Data Scie nce

Turning data into knowle dge by cre ating value s tre am s from your organizational d ig ita l data supp ly chain

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Com pute r Scie nce / IT Math & Statis tics

Machine Le arning

Software De ve lopm e nt

Trad itional Re se arch

Data Science

Dom ains/ Busine ss Knowle dge

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Tre nd 6: Cloud

Application m ode rnization utilizing Cloud to cre ate Eve rything and Anything as-a-Se rvice m ode ls for le gacy and future app lications.

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Com bining Cloud-native and Existing Applications

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CloudHow are companies ramping up? Cloud provisioning , Cloud-native , Microse rvice s, Containe rization, XaaS/ EaaS, Application Mode rnization

CloudFoundryTerraform & VaultCloud Format ionAWS, Azure, GCP

Docker, Kubernetes and ContainersVMWare/ Virtual Box Private

ARCHITECTURE

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Tre nd 7: Containe rization

Many organizations se tup sandbox e nvironm e nts using containe rs that a llow pe op le to le arn in a guard ra ile d e nvironm e nt

The use of containe rs as worke r node s for Continuous Inte gration and De live ry is ke y to fle xib le p ipe line s.

Containe rize d Microse rvice s and Le gacy Applications are top of m ind for m ost organizations.

ARCHITECTURE

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Containe rization: Top of Mind

ARCHITECTURE

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Tre nd 8: Ag ile Archite c ture

Archite c ture is not one size fits a ll.

“Any custom e r can have a car painte d any color that he wants as long as it is b lack.” - Henry Ford

With the ve locity of change , the de ve lopm e nt te chnology landscape is daunting to s tay curre nt. Ag ile Archite c ture re quire s Ente rprise , Busine ss , Solution and Application Ste wards who can m itigate risk by se tting ope rating s tandards and prom oting cross-functional collaboration.

For instance , if we inte nd to use Microse rvice s , Archite c ture works across te am s to cre ate the gold m aste r for usage ..

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Tre nd 9: Low-Code , No-Code

Utilizing “citize n de ve lope rs” fe ature functionality such as m ode l-d rive n de ve lopm e nt, point-and-click p rogram m ing , d rag-and -d rop com posab ility, wizard -base d workflows and s im ilar te chnique s. Rap id cre ation of e volutionary p rototype s.

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De fining the Roadm ap

Strate g ic workshops to de fine the curre nt s tate , future s tate and roadm ap for e volution of app lications.

Standards, patte rns, and gove rnance to allow the organization to de sign the base line for app lication m ode rnization.

Workforce s trate gy to b ring the com pe te ncie s and skills into alignm e nt with the app lication m ode rnization strate gy.

Collaboration and com m unication to e nsure that the organization has aware ne ss of the patte rns to be use d e ffe c tive ly and e ffic ie ntly

Application Modernization Academy

Agile Architecture & Data Cloud

DevOps Security & Controls

Application Mode rnization Ce rtifie d Spe cialis t*

Application Mode rnization Ce rtifie d Expe rt Practitione r Le arning Paths*

All IT Employees attend core curriculum

Targeted participation

LEVEL 2

LEVEL 1Partic ipant com m itm e nt: tota l 40 hours e ngage m e nt

1

2

Digita l Transform ation ce rtifica tion focuse s on the te chnical and functional com pe te ncie s and skills

Completion Recognition

Complet ion Recognit ion

Care e r de ve lopm e nt le arning paths com pris ing tra ining (instructor-le d , e le arning ), knowle dge (e xpe rie nce and ab ility), coaching , Brown Bags, and industry ce rtifica tions

Re inforce s culture shift (collabora tion, m atrixe d te am s) through a share d base line of knowle dge and com pe te ncie s across a ll job role s

“Pull conce p t” putting the focus on the “i” (the ind ividual) to de ve lop the ir com pe te ncie s

Agile DevOps Cloud Security & Controls

1 2 3 4 6

TRAINING

example• Classes• Certification

COACHING

• Project embedded

KNOWLEDGE

• Work experience• Assessment

TRAINING

• Classes• Certification

KNOWLEDGE

• Work experience• Assessment

TRAINING

• Classes• Certification

KNOWLEDGE

• Work experience• Assessment

TRAINING

• Classes• Certification

KNOWLEDGE

• Work experience• Assessment

TRAINING

• Classes• Certification

KNOWLEDGE

• Work experience• Assessment

TRAINING

• Classes• Certification

KNOWLEDGE

• Work experience• Assessment

5

Customer Centric Design

Customer Centric Design

Architecture & Data

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Application Mode rnization Training Path 2018 – Com pe te ncy Vie w

Exe cutive s & Manage rs

DevOps

Prac titione rs

WA2678 Designing REST Services for Architects

1 d ay

WA2271 Cont inuous Integrat ion w ith

Jenkins2 d ays

WA2451 DevOps Fundamentals

3 d ays

WA2593 DevOps for Leaders2 d ays

DevOps Architecture Patterns

1 d ay

WA2542 DevOps for Architects

3 d ays

WA2675 Architect ing MicroServices with

Kube rne te s, Docke r, and Continuous Inte gration

1 d ay

WA2409 Int roduct ion to Agile

Architecture2 d ays

Je nkins p lug-in d e ve lopm e nt

1 d ay

Cucum be r3 d ays

Se le nium2 d ays

De vOps Se curity2 d ays

De vOps SonarQubeRule Se t De ve lopm e nt

CI/ CD Pipe line for z/ Se rie s 2 d ays

WA2452 Node.JsSoftware

Development3 d ays

CI/ CD Pipe line for Java

2 d ays

CI/ CD Pipe line for wind ows

2 d ays

TFS with GIT1 d ay

Data Manage m e nt De vOps

with Datical

Application Mod e rnization

2 d ays

WA2184 Apache Maven2 d ays

WA2684 Developing Microservices

5 DaysWind ows/ Java ve rsion

De vOps Value Stre am Mapping (1 d ay gam ifie d )

Gett ing Started

DevOps Architecture

(as appropriate)

DevOps Hands-On

(as appropriate)

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Skills for the Mode rn Age

Big Data

Cloud MicroSe rvice s

Java Technologies including:Node Angular 5 Re act. Re sponsive We b De ve lopm e nt

Blockchain

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Questions?