On October 8, 2014, Karl Wale (Director of Product Management) and James Radley (Architect) presented: Turbocharge the NFV Data Plane in the SDN Era. This expert duo discussed the evolution of the network and service provider objectives around the challenges of deploying SDN/NFV solutions. They take you through some application use cases and introduce the new Radisys FlowEngine data plane software technology.

1. James RadleyArchitectjames.radley@radisys.com
Karl WaleDirector of Product Management karl.wale@radisys.com
October 8, 2014 Webinar
© 2014 Radisys Corporation

2. 2

NFV and SDN: disruptive technology shift
•
Network evolution and service provider objectives
•
Challenges in deploying NFV and SDN

New SDN and NFV solutions
•
Intelligent networking functions

Overcoming data plane challenges in the NFVand SDN era
•
FlowEngine™data plane software technology
•
Application use cases
–
Scaling capacity without overwhelming orchestration resources
–
Service chaining as part of virtualized Gi-LAN

Summary
Agenda
© 2014 Radisys Corporation

3. 3
Market Dynamics
NEWServices in Next- Generation Central Office
Service Providers (SP) Fighting OTT Threat
Regulators Enabling Two- Way Business Models & SP Intelligence
SDN & NFV Deliver Tools to Enable Service Delivery & Cost Reduction
11x capacity growth
2013 –2018 (Cisco VNI)
© 2014 Radisys Corporation
Services Centric Network

4. 4
Evolving Telecom Landscape

Telco data centers
•
Distributed
•
Localized control and service awareness
•
Fixed & mobile co-located

Services include:
•
Mobile EPC
•
Policy enforcement
•
Sponsored content
•
Video optimization
•
Advertising
•
Network analytics
Access
Metro
Optical
Next-generation Central Office for NFV
Need for NFV platform solutions in NGCO and telecom data centers
© 2014 Radisys Corporation

5. 5

Streamlined capex
•
Minimize fixed function platforms
•
New infrastructure hosting multiple services
•
Equipment re-used andre-purposed for new services

Faster service delivery
•
Services centric network

Scalability
•
Simpler to scale up
•
Lower cost vs. buying telecom appliances
Why Do We Need NFV?
Source: ETSI
© 2014 Radisys Corporation

6. 6
NFV Infrastructure and Interfaces
OSS/BSS
Os-Ma
Ve-Vnfm
Virtual Computing
Virtual Network
Virtual storage
Virtualization Layer
Hardware Resources
NFVI
VI-Ha
Nf-Vi
NFV Management & Orchestration
ComputingHardware
NetworkHardware
StorageHardware
Vn-Nf
Vn-Nf
Vn-Nf
EMS1
EMS3
EMS2
VNF1
VNF3
VNF2
NFVOrchestrator
VNFManager(s)
VirtualizedInfrastructureManager(s)
Or-Vnfm
Vi-Vnfm
Or-Vi
Platforms options
•
Bladed and server
•
Integrated or discrete networking functions
Typical Applications
•
Service assurance(PCRF, DPI apps)
•
Mobile gateways
•
IP forwarding(OpenFlow control)
NFV and SDN Tools
•
Load balancing and flow distribution
•
OpenFlowinterfaces for networking
•
OpenStackintegration
•
Nova (Compute), Neutron (Network)
•
Platform management
© 2014 Radisys Corporation

7. 7
Service providers desire COTS hardwarebut concerned existing products not carrier grade
Source: “SDN and NFV Strategies, Global Service Provider Survey”, March 2014, Infonetics
Drivers and Barriers of NFV
© 2014 Radisys Corporation

8. 8
Scalability Challenges for SDN and NFV

Early NFV examples
•
Control plane applications
•
Smaller scale PoCs
•
Limited bandwidth on data plane

Data plane is bigger challenge
•
10s of millions of users
•
100s of millions of sessions/flows
•
Throughputs into the Terabits/sec
•
Latency critical
Control plane vs. Data plane
contrasting example:
3 minute VoIP call
~10-15 SIP signalling packets in control plane
~36,000 RTP packets
in data plane
© 2014 Radisys Corporation

9. 9
1.
How many subscriber sessions would you expect a typical orchestration layer to track?
a)
< 5 million
b)
5 to 50 million
c)
50 to 200 million
d)
> 200 million
Poll Question

10. 10
NFV Questions and ChallengesFor Data Plane Applications
Virtualized Compute Resources
-
Linux, hypervisors, virtual switching
-
Performance scales to 100s Gbps
-
Optimizing/Offloading OvSfunctions
-
Who integrates and tests the functions?
Orchestration
-
e.g. OpenStack
-
Sessions tracked? Flows managed?
-
How far can it scale?
-
How fast can it respond to events?
Support for
100s millions events/flows
Must scale toTbpsat frame level, including supportfor 100GbE ports
Networking (with Simple Switch)
-
L2/L3 forwarding
-
Fixed, limited encapsulation support
-
Poor elasticity for flow re-direct
-
Service chaining not possible
Source: ETSI
© 2014 Radisys Corporation

11. 11
Source: ETSI
Completing the NFV PictureFor Data Plane Applications
Virtualized Compute Resources
-
Linux, hypervisors, virtual switching
-
Performance scales to 100s Gbps
-
Optimizing/Offloading OvSfunctions
-
Who integrates and tests the functions?
Orchestration
-
e.g. OpenStack
-
Intelligent switch reduces work load
-
Autonomous flow assignment scales to millions flows vs.10s thousands
Networking (with added flow awareness)
-
L2/L3 forwarding
-
Multi-protocol encapsulation
-
Cost effective scaling to Tbpsincl. 100G
-
Statefuland stateless load balancing
-
Flow classification and ACLs
-
Enables service chaining
-
Autonomous flow assignment
Add Intelligent Switching & Load Balancing
© 2014 Radisys Corporation

12. 12
Load Balancing & Flow Awareness Today It works…but not ideal
Load Balancer
Switch/ToR
Server
Server
Server
Switch/ToR
Network/Router
Stand-alone Devices
Integrated/Chassis-based
Standard Switch (L2/L3)
Basic 5 tuple load balancing
Stateless, only scales to few 10K flows
Network
Advanced Load Balancing
Implemented on payload blades;
...but uses payload slots
Server
Server
Server
Stand-alone Load Balancer
Delivers capabilities…but, typically high-cost/Gb, limited scalability and likely over-featured?

13. 13
Intelligent Switching ArchitecturesEvolving switch architectures for NFV and SDN
Commercial Switch Silicon
1.2Tbps
Network
Network
Commercial Switch Silicon
1.2Tbps
NPU(s)
800Gbps
Multi-core CPU
Exception packets, OpenFlowMgmt…
10, 40 and 100GbE
Optical Ports
Server CPUs
Server CPUs
Simple
MgmtCPU
Limited rules available
Up to few 10K flows
Stateless 5 tuple LB
Intelligent Switching & Load Balancing (egA2470)
L2/L3 forwarding
Multi-protocol encapsulation
Stateful& stateless LB
Flow classification & ACLs
Enables service chaining
Autonomous flow assignment
© 2014 Radisys Corporation

14. 14
Intelligent Switching Solves Problem
Inbound Packets
Outbound Packets
AP
AP
AP
AP
AP
AP
AP
AP
AP
AP
AP
SDN/ Controller
In
IPF
LB
AP
Out
Input
SDN IP Packet Forwarder
Load Balancer
Application Processor
Output
A2470 Intelligent Switch (4x100G each)
A4700 Intel® Xeon® E5-2600 v3 Blade
AP
A2470 Intelligent Switchwith FlowEngine™
A4700 Intel® Xeon® E5-2600 v3x86 CPU Blade
LB
In
IPF
Out
Rule-based automatic flow assignment
100s millions flows managed
Minimizes overhead on orchestration
© 2014 Radisys Corporation

15. 15
2.
How will you implement flow classification and load balancing within your NFV deployments?
a)
Dedicated load balancer from established vendor
b)
Develop (or partner for it ) based on commercial appliance
c)
Implement on compute server (blade or RMS/server)
d)
Standard white box switch and commercial silicon
e)
Don’t need load balancing
Poll Question

16. Overcoming Data Plane Challenges in the NFV and SDN Era
James RadleyArchitectjames.radley@radisys.com

17. 17
The SDN Model
Orchestration
Automated provisioning, coordination, management of defined services within the DC or Telecom Network (e.g. Virtualization)
Node
In a network, a node is either a Connection Point (e.g. media gateway), a distribution point (Top of Rack Switch) or an end point (Cloud Server) for data transmissions.
Controller
Manages network control plane to configure network devices, choose the optimal network path for application traffic flows.
Source: Intel
© 2014 Radisys Corporation

18. 18
FlowEngine Overview

FlowEngine is a portfolio of functions for identifying, manipulating and steering IP traffic at line rate

Built around core load balancing function running on NPU

Core load balancing application isextensiblewith configurable derivations
•
MPLS edge routing forwarding plane element
•
Bespoke SDN switch for NFV style deployment

FlowEngine functions can be managed by CLI, OpenFlowand high-speed table update interfaces

Integration with OpenFlow and ForCES-basedcontrollers supported
© 2014 Radisys Corporation

19. 19
Example of SDN Table Stacking
Access Control List Inbound Flow External PortsLBG[0]LBG[1]LBG[2]LBG[3] Router FunctionPort Queuing & Traffic Management FunctionBackplane & RTM ports
© 2014 Radisys Corporation

20. 20
Load Balancing Groups
Hash Logic BFlow type AFlow type AFlow type BFlow type BAccess Control List (ACL) is used to determine what type of flow type an individual packet belongs to. Hash Logic AField SelectorGTP tunneled IPField SelectorGTP TEID fieldLBG1LBG2

Supports up to 4 Load Balancing Groups (LBGs)

LBG selected by ACL rules

Each LBG can determine load balanced target using differentkey header fields
•
IP addresses (outer IP header)
•
GTP Tunnelling Endpoint Identifier (TEID)
•
Tunnelled IP header

21. 21
NPU
Typical SDN Handling for a New Flow
Introduces very long latency 
NPU
© 2014 Radisys Corporation

22. 22
NPU
Controller Can Predefine Flow Rules
Controller would need to anticipate flow in advance
NPU
© 2014 Radisys Corporation

23. 23
Autonomous Handling of New Flows
NPU
NPU
© 2014 Radisys Corporation

24. 24
Table Cascade for Stateful Load Balancing
© 2014 Radisys Corporation

25. 25
Capacity-aware Load Balancing
© 2014 Radisys Corporation

26. 26
Service Function Chaining
A
C
D
B
© 2014 Radisys Corporation

27. 27
Service Function Chaining

Industry recognises that some form of per-packet tagging is required to allow switch to properly chain functions
•
cf. IETF SFC drafts

However, getting agreement on a standard for such tags willprove challenging
•
Will impact many legacy applications from numerous vendors
•
Will it be the vSwitchor VNF application vendors who decide?

In short term, flexibility of a programmable NPU device isrequired to support whatever SFC tagging schemes emerge
•
NPU can initially apply list of SFC hops on system ingress
•
NPU can pop tags as packet returns from one VNF and use nextSFCtag to identify next service type
© 2014 Radisys Corporation

28. 28
Service Function Chaining Methods
L2VLANSFC-HDRL3L4PayloadSFC-IDSFC-IDSFC-IDSFC-IDL2VLANSFC-HDRL3L4PayloadCounter-- L2VLANSFC-HDRL3L4Payload
© 2014 Radisys Corporation

29. 29
Automatic Packet Bypass

Only established flows sent to CPU resources for analysis
•
Failed TCP session setups and short UDP bursts bypass servers

Samples of flow sent to servers
•
Only every nthpacket of identified flow sent to CPU resources
© 2014 Radisys Corporation

30. 30
Automatic Packet Bypass

Majority of traffic not sent to server resources

Compute capacity of server array does notdefine total system throughput
© 2014 Radisys Corporation

31. Final Thoughts and Summary
Karl WaleDirector of Product Management karl.wale@radisys.com

32. 32
Summary

SDN and NFV driving new platform requirements
•
NFV transition for control plane underway
•
NFV transition for data plane has unique challenges

Load balancing and flow distribution key
•
Cost effective and high performance
•
Customizable and highly elastic to track VMs
•
Need more than simple switching

Specialized networking required to scale
•
Commercial switch silicon cannot handle all permutations
•
Terabit+ performance levels, deeply embedded packets etc.
•
100s of millions of sessions per rack/frame/chassis
© 2014 Radisys Corporation

33. Thank You for AttendingQuestions?
James RadleyArchitectjames.radley@radisys.com
Karl WaleDirector of Product Management karl.wale@radisys.com