Overture End-to-end Service Intelligence for NFV
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Transcript of Overture End-to-end Service Intelligence for NFV
1 110/17/2014 O V E R T U R E N E T W O R K S . C O M
End to End Service Intelligence for NFV: Leveraging Insights from the Physical & Virtual
SDN & OpenFlow World CongressOctober 17, 2014
2 210/17/2014 210/17/2014
End-to-End Service Intelligence is Needed …
Collecting data from devices is not enough
We must create actionable intelligence about the end user service – but how?
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Limits to Today’s Tools• Requires pre-defined data formats and relationships
(schema) -> Complicated• Proprietary -> Closed• Pre-defined Correlation -> Inflexible
Result: Slow and Limited
But it is worsethan that because
things have become more complicated!
4 410/17/2014 410/17/2014
What Has Changed? SDN!
Increased Dynamics
Improved Control
5 510/17/2014 510/17/2014
What Has Changed? Virtualization!
Remember this Major Transformation?
We are now replacing Appliances with Virtual Network
Functions (VNFs)
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Operators Plan to Deploy Virtual Services• Using SDN for dynamic control • Using NFV for CapEx and OpEx reduction• Using both for service innovation
That’s a lot of new stuff.
A lot of moving parts.
Are we crazy?
7 710/17/2014 710/17/2014
First Problem – Data Explosion
• Collection – from numerous disparate sources• Volume – more sources, and
data moved from network elements to big data servers• Analysis and Intelligence –
correlations, trends, root cause analysis• Application – optimization,
pricing, diagnostics
8 810/17/2014 810/17/2014
Next Issue – Dynamic AssignmentSDN and virtualization enables dynamic assignment of resources, which adds complexity to monitoring those resources. Examples:
Policy-based resourcesMapping of virtual functions to physical devices
Virtual/overlay networksShared hardware
On-demand services
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Challenge - Virtualized Services Vary Over Time
Create Service
IMS Homer
IMS SproutIMS
Switch
IMS Sprout
How do you associate the service with the VNF and its server – at any given time?
Scale Up
Fault recovery /Resource migration
10 1010/17/2014 1010/17/2014
Hurdle – Data and Correlation Change
Change is a constant• Data sources • Data formats and values• Types of correlation
11 1110/17/2014 1110/17/2014
Barrier - Services Spread Across Silos
Old separations can no longer apply!
Acce
ss
Tran
spor
t
IT
Ope
ratio
ns
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What is Needed? Dynamic Data Gathering• An efficient way to
gather data
• From numerous physical and virtual resources
• Using push and/or pull
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What is Needed? Big Storage
Ability to feed multiple data streams into a sharedsource-independent, common-format storage
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What is Needed? Definable CorrelationAbility to define arbitrary, cross-source correlations between data sources using rules:
• Historical
• Geographical
• Event-based
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What is Needed? Powerful, Simple Query• Efficiently answer
arbitrary questions
• Using arbitrary queries
• Through a simple and open API
• Without a pre-defined schema
16 1610/17/2014 1610/17/2014
My View of a Workable Architecture
Host
API
VNF
PhysicalNetwork Function
VNF
VNF
VNFVNFVM
VNF Host
API API API
Service Order
Runtime Correlation
VNFM / EMS OpenStack OSS/BSSVNFO
Big Data Storage
NFV Service Dashboard
NFV Auto-Scale
NFV Fault Management
Applications
ServicePerformance
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Benefits of this ApproachProvides actionable intelligence for SDN/NFV enabled services in a complex, virtual world!
Examples of enabled applications:• Fault and Performance Management• Root Cause Analysis • Inventory Management• Service Consumption and
Capacity Planning• … and many others!
18 1810/17/2014 18
Thank You!Prayson Pate - [email protected]