The document discusses leveraging genomics in the 21st century and presenting genomics data in a cloud-agnostic and complex yet simple architecture. It covers the structure of DNA and different models for genomics applications, architectures, packaging, development approaches, and infrastructure deployment. Docker Hub is presented as a tool for building, shipping, and running containerized applications across development, testing, and production environments.

1. Genomics Data Insights
@vishwasnarayan5 Vishwas N
https://hacksterdude.web.app/

3. About me
I am a Podcaster : http://tiny.cc/vnrpodcast
I love to talking to techies
A Bibliophile
Passionate about Image dataset - Computer Vision
Now exploring Azure cloud
“17 demos and 1.5 hours” dreamer

4. Agenda
● How to leverage the Genomics in 21st Century
● Genomics for the Cloud Agnostic Approach
● Challenges in Genomics and data science how do we put it
all together in a Complex yet simple Architecture

5. Structure of DNA

7. There were different models to it
Application
Architecture
Application
Infrastructure
Deployment
Or
Packaging
Waterfall
Agile
DevOps
Scrum

8. Docker Hub: Build, Ship, Run Applications
Build Ship
Run
Dev
QA
Source
Staging
Physical
Virtual
Cloud
InfrastructureManagement
InfrastructureManagement
DockerFile
Source Code
Repository
TEST
TEST
TEST
TEST
TEST
GCE RAX Azure
Mac/Win Dev
Machine
Boot2Docker
Docker
Analytics
DB
Prod
Machine
Linux OS
Docker
Docker
++
Users Collab
Provenance Policy
Docker Hub
Registries
Public Curated Private
Docker Hub API
Third Party Tools
Prod
Machine
Linux OS
Docker
Docker
Prod
Machine
Linux OS
Docker
Docker
VM
Docker
Docker
VM
Docker
Docker
VM
Docker
Docker
QA Machine
Linux OS
Docker
Docker
Docker Hub provides a centralized resource for container image discovery,
distribution and change management, user and team collaboration, and workflow
automation

9. Some commands will still remain
same relate to some projects or
the software
1. func init
2. func new
3. func start
4. func deploy
5. func publish

10. Choice of Language C#,java,javascript,python and
powershell is also available..

11. So now why is it priced the way it
is priced?
So there are multiple reasons for it:
The money is the number one factor.

12. What makes you intelligent?
You learn to
1. Recognize
2. Make mistakes and learn from it
3. Make sure that you learn from the learnt aspects(you
can relate to some learning)
4. You sometimes go by your Gut Feelings
5. Create Perspectives and we will learn to work with it.

13. AI today is just trying to mimic the
senses
Computer Vision
Natural language
processing

14. Ai today is just trying to mimic the
Cognitive Capability
Perception ,Perspectives

15. Ai today is just trying to derive
Insights and Intent

17. ML models : Research to production
Deployment
Data
Collection
Trainin
g
Inference
and
deployment
Conversion

18. Data Storage
Collect
Transform
Normalize and other steps
Data from different source
Build a Model from Data
Deploy the Model

19. ML
Engineer
Data
Scientist

20. Our typical Development : DevOps
Development Stage
Test
Development Deployed with a Review from
DevOps Engineer

21. Research Methodology
We use the Same DevOps methodology but we use the Six-Sigma Approach in the deployment.
Control
Improve Analyze
Measure
Define

22. It's still a NP Hard Problem
What is it all about

24. So lets see some Case Studies
As in future you have to only make your cloud focus on Architecting a Solution that
is even more feasible.

25. So let's go and

26. Q/A