Harness the power of 3 Devops, Cloud, AI

1. HARNESS
THE POWER OFTHREE
DEVOPS, CLOUD, AI
Archana Joshi
Head –Transformation, LTI
DevOps India Summit 2019
Note:The views represented in the presentation are solely of the presenter and do not represent those of the company /clients she is associated with

2. 2

3. What is common here? 3

4. 4

5. What is
common
here?
5

6. 6

7. With Cloud you get
Improved Scalability
Reduced IT Costs
Business Continuity
….. and many more
7

8. Plan Code Build Test Release Monitor
Typical DevOps Pipeline
8

9. 9
Build… or Buy….
Source: https://www.zdnet.com/article/atlassian-packages-tools-to-help-enterprises-accelerate-devops-adoption/

10. With DevOps you get
Improved Collaboration
Shorter Delivery Cycles
Improved Quality
….. and many more
10

11. Azure DevOps
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12. AWS DevOps Stack
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13. 13

14. ML in DevOps DevOps for ML
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Bringing in Machine Learning into the mix

15. Plan Code Build Test Release Monitor
ML in DevOps
15
Log Analysis
Predicting Server
Failure
Predicting
Application
Failure
Building
applications based
on patterns
EfficientCode
Merging
ML enabled
automated testing
SimplifiedAlerts
Root Cause
Analysis
Data Correlation
Collaboration and
planning aided by
ChatBots

16. Dynatrace: Davis AI engine
16Source: https://www.dynatrace.com/platform/artificial-intelligence/

17. DevOps for ML (aka MLOps)
•Science: Data preparation, model training and
validating
•Engineering: Developing the software that
consume the data
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18. AWS DevOps Stack + AWS SageMaker
AzureDevOps + Azure ML
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For Data scientists
•Is it as flexible as using my own environment
tools/setup?
•Will it make building and training models
easier?
•Will it make working with other data scientists
easier?
•Will it make working with DevOps easier?
For DevOps engineers
•How do I hook this up to existing
systems?
•How can I make these components
scalable?
•Will it make model deployment easier?
•Will it make working with data scientists
easier?
Source: https://towardsdatascience.com/building-a-devops-pipeline-for-machine-learning-and-ai-evaluating-sagemaker-cf7fdd3632e7

19. With DevOps + Cloud + AI/ML
You can achieve your dream of self healing pipelines
You can reduce time to bring out yourAI/ML based solutions
You can contain the costs of your DevOps pipeline
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20. THANK YOU
https://www.linkedin.com/in/arcjoshi