This document discusses machine learning and how it can be applied to optimize IT environments. It introduces SIOS Technology Corp and their product called SIOS iQ, which uses machine learning and topological data analysis to analyze VMware environments. The document explains how machine learning and algorithms can help address challenges of analyzing large and complex data in IT operations more effectively than conventional tools. It encourages readers to learn about machine learning through online courses to stay relevant in their fields.

1. AI is coming!
Are you ready?
Story of “Self-Driving” Datacenter
Sergey A. Razin
CTO, SIOS Technology Corp.

2. 2
Who is SIOS?

3. Who is SIOS?
3

4. What is
Machine Learning?
“the state of humanity”

5. Does ML Exist Today?
5

6. What is Machine Learning?
6

7. Why
Machine Learning?
“ML will save the world”

8. Productivity
8

9. IoT - Is a big deal!
9

10. Internet of Things Kills Internet
10

11. What is the problem? Why Conventional
Tools Can’s Solve It?
• Understanding of Data Semantics because:
• Data is Big
• Data is complex
• Data is high-dimensional (with a lot of interrelationships and interplay)
• Data is features rich
• Solution required different type of tool

12. 12
2016 and 2017
ML is HOT!

14. Let’s look at the IT evolution
14

15. How did IT started?
15

16. How did IT started?
16

18. 18

19. Give me more Data!
19

20. Operational Scale & Complexity in Virtualized
IT
20
0
10,000,000,000
20,000,000,000
30,000,000,000
40,000,000,000
50,000,000,000
60,000,000,000
70,000,000,000
100
1,000
3,000
5,000
10,000
100 1,000 3,000 5,000 10,000
VMs 100 1,000 3,000 5,000 10,000
# of Objects 2,000 15,000 50,000 100,000 200,000
# of Metrics 604,800,000 4,536,000,000 15,120,000,000 30,240,000,000 60,480,000,000

21. IT Operations with the Hammer and a Chisel
21

22. 22
API

23. Conventional Tools
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 23
Data
Still Dealing With Noise
Conventional Tools

24. State of The Productized Art
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 24
Computer Science Approach

25. State of The Productized Art
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 25

26. Copyright @ 2015 SIOS Technology Corp. All rights reserved. 26

27. Copyright @ 2015 SIOS Technology Corp. All rights reserved. 27

28. What if there was a solution?
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 28

29. Topological Behavior Analysis
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 29

30. Topological Data Analysis (TDA)
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 30
TDA
Mathematics (Topology)
Data
Shape

31. Algorithms – How is TBA works?
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 31

32. Copyright @ 2015 SIOS Technology Corp. All rights reserved. 32
Algorithms – How is TBA works?
Dynamic K (Deep Learning):
- Data scaling
- Goal is Gaussian distribution with in the
cluster via PDF
- Re-cluster -> # of K
- Throw away noise clusters
Semi-Supervised power of Clusters:
- Cluster Tagging
- Cluster Instrumentation

33. Copyright @ 2015 SIOS Technology Corp. All rights reserved. 33
Algorithms – How is TBA works? (Learned
Behavior)
“Shape” of the date.

34. Algorithms – How is TBA works? (Topology)
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 34
Monthly Topology
0
0.2
0.4
0.6
0.8
1
1 2 3 4 5 6 7
Metric
0
0.2
0.4
0.6
0.8
1
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
Quarterly Topology
Etc.

35. Copyright @ 2015 SIOS Technology Corp. All rights reserved. 35
Algorithms – How is TBA works? (Anomaly)

36. Dynamic ML Sensitivity Coefficient (Deep
Learning)
Copyright @ 2015 SIOS Technology Corp. All rights reserved. 36

37. Copyright @ 2015 SIOS Technology Corp. All rights reserved. 37
Topological Behavior Analysis (TBA)

38. 38
What’s Next?

39. Self-Driving Datacenter
39

40. What is
Machine Learning
for Real?

41. What is Machine Learning for Real?
41
- It is science
- It is algorithms
- It is pattern recognition
and computational
learning theory in
artificial intelligence

42. 42
Why should
you brush up
on Algorithms?

43. Expert Knowledge + Machine Intelligence
43

44. 44
Stay Relevant - Education
Machine Learning Course: https://www.coursera.org/learn/machine-learning

45. DIY – Machine Learning/Deep Learning
http://www.r-project.org/
http://www.cs.waikato.ac.nz/ml/weka/
https://mahout.apache.org/
https://www.tensorflow.org/
https://madlib.incubator.apache.org/
http://spark.apache.org/docs/latest/ml-guide.html

46. Social Graph -> IT Graph
http://neo4j.com/
FlockDB
https://github.com/twitter/flockdb
http://giraph.apache.org/

47. 47
Neo4j
https://www.vmware.com/support/pubs/sdk_pubs.html
API

48. 48

49. 49
Want to see it
in Action?
http://us.sios.com/

50. SIOS iQ™
Machine Learning Analytics for optimizing
VMware environments

51. 51
• Data Scientists
• Back-end and Full Stack
Developers
Job Opportunities @ SIOS
Great People. Exciting and Innovative Projects.