In order to maintain a competitive advantage, CTOs and product managers are shifting their products to the cloud. Many do this by simply replicating their current architectures in the cloud. Those previous architectures, which were optimized for transactional systems, aren't well-suited for the new age of AI. Whether you're a seasoned CTO or an industry trailblazer, this webinar will help make your product ready to meet the competition by adopting an architecture that is optimized for AI innovation. Join Ahmad Jubran, Cloud Product Innovation Consultant, and learn how to adapt your solutions for cloud models the right way.

1. Product Transformation: Adapting
Your Solutions for Cloud Models
Ahmad Jubran Julie Lawson
With: Moderated by:
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From the Build Better Products with Information
Management Webinar Series

2. OpenText is the Information Management company, providing organizations access
to world-class technology to help manage their data and content, improving process
and decision-making and unlocking new business opportunities. Our OEM Team
makes this technology available to other software companies to deploy as part of
their own products. Through the OpenText OEM Program, our partners can
customize, extend, embed and white-label OpenText technology to add critical
information management functionality to their end-user solutions. OpenText OEM
technology is categorized into 7 intuitive solution areas, making it easy to navigate
the vast collection of products that comprise each.

3. Click on the Questions panel to
interact with the presenters
https://www.ctouniverse.com/frs/15081187/product-transformation--adapting-your-solutions-for-cloud-models

4. About Ahmad Jubran
His work has encompassed creating and launching patient social engagement
platforms for major hospitals and health centers, developing one of the largest
healthcare online medical education platforms in North America, and leading multiple
health technology initiatives in Medicare/Medicaid including the health insurance
exchange for the state of Massachusetts. He has overseen technology budgets
exceeding millions of dollars with hundreds of internal and external team members
across organizational departments. He holds a BS in Computer Engineering from the
University of Massachusetts, Dartmouth, where he did research in the areas of digital
signal processing and robotics.
About Julie Lawson
Julie Lawson majored in English at Boston University. She worked at the college radio
station, WTBU, where she developed a passion for producing shows with good music
and good stories. She started her career at a small publishing house in Los Angeles and
went on to become Webinar Coordinator at Aggregage, where she produces webinars
and facilitates BTS webinar functions. In her spare time, she enjoys going to the beach,
camping and reading great books.

5. Agenda
● Motivation
● Tenants
● Examples
● Let’s build a startup
● Q and A

6. Motivation Behind Transformation

7. Product Lifecycle
Product-Market Fit

8. Product Market Fit

9. Product Lifecycle - The knowledge Gap

10. Getting to Product Market Fit and Beyond
● We need to transform our approach to building products in order to:
○ Close the knowledge gap (the quicker we do this, the higher the probability of
success)
○ Foster innovation
○ Build highly engaging products

11. Transformation Tenants

12. Transformation - Framework
● Iterate quickly (agility)
● Move ideas into production quickly
● Minimize upfront commitments (resources, infrastructure, solution design,
budget)
● Make data-driven decisions
● Leverage AI (Personalization, Recommendation, etc.)

13. Transformation - Cloud Model
● Favor higher level of abstractions (API -> Serverless -> Managed -> VM)
● Built from loosely coupled components
● Polyglot (The right tool for the job)
● Event driven
● Intelligent
● Cost efficient

14. Examples

15. Examples - Favors higher level of abstractions
Tensorflow on EC2
Tensorflow on SageMaker
Rekognition API
Classify Image

16. Examples - Favors higher level of abstractions
EC2
EKS
S3/API Gateway/Lambda
Web App

17. Examples - Favors higher level of abstractions
EC2 (Hadoop/Spark)
Glue/Athena
Analytics
EMR / DataPipeline

18. Examples - Built from loosely coupled components
Cloudfront (Web)
DynamoDB
Lambda
Trigger
SNS
(pub/sub)
Lambda
Functions

19. Examples - Polyglot
Relational
(Aurora)
Key/Value
(Dynamo)
Time Series
(TImeStream)
Graph
(Neptune)

20. Examples - Event driven
Lambda
TriggerWeb
DynamoDB
S3
Storage
Rekognition API

21. Examples - Intelligent
NLP
(Comprehend)
Vision
(Rekognition)
Speech to text
(Transcribe)
Conversational
(Lex)
Recommendation
(Personalize)

22. Let’s Build a Startup!
DiabetesMgmtCo

23. Collect User Data

24. Web (S3)
API
Gateway
{Glucose}
(K/V)

25. Add Content

26. Web (S3)
API
Gateway
{Glucose}
(K/V)
{Content}
(Document)

27. Add Social Network

28. Web (S3)
API
Gateway
{Glucose}
(K/V)
{Content}
(Document)
{Social} (Graph)

29. Add Real Time Streaming

30. Web (S3)
API
Gateway
{Glucose}
(K/V)
{Content}
(Document)
{Social} (Graph)
(Firehose)

31. Add Analytics

32. Web (S3)
API
Gateway
{Glucose}
(K/V)
{Content}
(Document)
{Social} (Graph) Spark
(EMR)
(S3)
(Firehose)
Dashboard
(QuckSight)

33. Add Machine Learning

34. Web (S3)
API
Gateway
{Glucose}
(K/V)
{Content}
(Document)
{Social} (Graph) Spark
(EMR)
(S3) SageMaker
{Infer}
(Firehose)
Dashboard
(QuckSight)

35. Q&A
Julie Lawson
With: Moderated by:
Cloud Product Innovation Consultant
Linkedin page: /in/ahmadjubran/
Ahmad Jubran
Webinar Coordinator, Aggregage
Linkedin page: /in/Julie-Lawson/
Email: julie@aggregage.com
https://www.ctouniverse.com/frs/15081187/product-transformation--adapting-your-solutions-for-cloud-models