Big Data Visualization Problem in IT Management
Serge Mankovski, Research Staff member at CA Technologies
January 22nd 2014
Big Data exposes and amplifies need for understanding big picture of what data tells you without loosing track of minute details. This need manifests in different aspects of Big Data from data processing and management to visual analytics and insight. This problem clearly manifests in management of very large IT infrastructures. CA Labs, as a part of CA Technologies, is focusing on the problem of visualization of Big Data in context of traditional IT management problems of root cause analysis, impact analysis, and change management. We will demonstrate examples of the Big Data Visualization problem as we see it and try to somehow outline this area of research problems.
Big Data Visualization Meetup - South Bay
http://www.meetup.com/Big-Data-Visualisation-South-Bay
1. Serge Mankovski
CA Labs Research Staff Members
Big Data Visualization in IT
Management Environment
2. Problem as we see it
— Data is more complex than ever before
− Three Vs of Big Data
− Mushup of structured, semi structured, and unstructured
− Longer time frames
— and we are eager to use long term data more than ever before
− Big promise of Big Data
— Existing visualization techniques mostly built for less complex data
— Time constraints for interactive visualization remain as before
— It is clear in IT management that new techniques are needed to
accomplish common use cases
3. Problematic Use Cases In IT MGMT
Elements of interest
− Single element
• Server
• Router
• Database
−
Groups
• Service
• Network
• Location
Relationship
• Server A hosts Virtual Machine B
• Application A uses Database B
• Service A is contains Application B
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− Datacenter
• Multiple datacenters @ 20,000+ servers each with
several hundred items
− Mainframe
• Single LPAR can have 30,000+ items
− Cloud Connected Enterprise
• All of the above plus partially transparent cloud
deployments
6. 6
Our approach to resolving the dilemma
— Common Approach
− Show as much as possible
− Use various layouts
− Use overview and zooming
— Our Approach
− Show as little as possible
− Use simple layout
− Use semantic zooming and
layered overview
7. Map of IT Environment
— A map of the user’s workspace, where elements of the IT
environment are assigned to a layered structure that
allows the user to quickly recognize dependencies
between areas of the network
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Enterprise Asset
Terrain
Layer 1
Layer 2
Dependency
8. Definition of Layers
We define a layer in terms of:
− A set of elements (or aggregations) we want
to visualize on the layer
− The resources these elements share
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9. Defining Hierarchical Layers
Step 1 – Assign elements to the layer
1. Select subset of elements
we want to visualize
2. Assign elements
to layer
Services layer
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11. Defining Hierarchical Layers
Step 2 – Select related resources
1. Select type of resource
dependencies to visualize
2. Select relevant relations
between layer element
and related resources
Services layer
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12. Defining Hierarchical Layers
Step 3 – Detect and draw dependencies
1. Identify layer elements
with shared resources
2. Draw layer elements to
represent overlapping of
resources
Services layer
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14. A Map of the IT Environment
Semantic navigation of complex environment
Services Applications Systems
AssetsNetworks
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15. Complete Map of the IT Environment
Visual Summary of the Environment based on Filters
Service 5 is selected
Services
Related items in all other levels are highlighted
Applications Systems
Assets
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17. Getting to What is Important
Start with a complex IT
environment
Use simple filters to create an
abstract representation of IT
infrastructure
Open areas of interest in
context using traditional
visualization tools
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20. Select Green Elements
Select Blue Elements
Defining Blue-Green Layer by Type of Element
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Select Red Relationship
21. Naming Surfaces of the Layer
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APPLICATION
SERVCE
USES
Top Class
Bottom Class
Relationship
Set
22. Equivalence
22 CEWIT 2011 November 3rd, 2011
Equivalency in Top and Bottom
Classes
red = gray
yellow = green
Equivalency in Relationship Set
(yellow = green)
25. Graph Cache Behind the Visualization
Graphic Renderer
Web
Service
Database
A
P
P A
P
P
A
P
P
DB
DB
DB DB
Graph database querying system
3rd party
application
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