Intelligent Service Function Chaining. March 2015

Transcription

1 Intelligent Service Function Chaining March 2015

2 Drivers & challenges for Service Chaining 1. Easier & faster service deployment 2. Cost reduction 3. Smooth transition to the future architecture 4. Standardization Page 2

3 principle #1: Easier & faster service deployment through automation Telco / 3GPP Services NFV PCRF -aware function (e.g. Parental Control -aware function (e.g. Video Opt.) -Unaware function (e.g. Caching) NFV Orchestrator Automation Proxy VNF Manager P-GW SDN Controller Service Function Forwarder VIM Incoming traffic Service Network IT / SDN Service Page 3

4 principle # 2: Cost savings Page 4

5 principle # 3: Smooth migration from legacy to new apps 1. Tagging mechanism to apply service awareness end-to-end within the network Telco / 3GPP 2. Supports legacy applications by providing reclassification mechanisms -aware and function proxy in the case PCRF of non-transparent (e.g. Parental services Control 3. Turns Layer-2 and Layer-3 equipment into flow-aware equipment as Service Forwarding Functions Automation -aware function (e.g. Video Opt.) Services -Unaware function (e.g. Caching) 2 Proxy NFV NFV Orchestrator VNF Manager P-GW SDN Controller Service Function Forwarder 3 VIM Incoming traffic Service 1 Network IT / SDN Service Page 5

6 principle # 4: Standardization Service Clients NBI Application Orchestrator SF Locator & Transport Cap instance SBI (SDN NBI) Non- Service Functions IPS FW -Enabled Service Functions IDS NAT Cache Load Balancer QoS VPN WOC Source Destination Page 6

7 Working Groups Service Clients NBI OpenStack Group Based Policy (GBP) ETSI NFV MANO ETSI VNF Forwarding Graph Application Orchestrator SF Locator & Transport Cap instance SBI (SDN NBI) ONF North Bound Interface (NBI) ODL Project ONF L4-7, Extensibility Working Group IPS FW -Enabled Service Functions IDS NAT Non- Service Functions Cache Load Balancer QoS VPN WOC IETF Service Function Chaining () Source Destination Page 7

8 Data Plane Mgmt. & orchestration Control Data Source Destination Page 8

9 Data Plane Mgmt. & orchestration Control Data Source Destination Page 9

10 Control Plane Mgmt. & orchestration Control Data IPS FW -Enabled Service Functions IDS NAT Non- Service Functions Cache Load Balancer QoS VPN WOC Source Destination Page 10

11 Control Plane Mgmt. & orchestration Control Data In Port VLAN ID Ethernet SA DA Type IPS FW -Enabled Service Functions IP IDS SA DA Protocol NAT TCP Src port Dst port Cache App.ID Load Balancer QoS Application VPN Subs. Class WOC Source Destination Page 11

12 MANO Service Clients NBI Mgmt. & orchestration Application Orchestrator SF Locator & Transport Cap instance SBI (SDN NBI) Control Data IPS FW -Enabled Service Functions IDS NAT Non- Service Functions Cache Load Balancer QoS VPN WOC Source Destination Page 12

13 MANO Service Clients NBI Mgmt. & orchestration Application Orchestrator SF Locator & Transport Cap instance SBI (SDN NBI) Control Data IPS FW -Enabled Service Functions IDS NAT Non- Service Functions Cache Load Balancer QoS VPN WOC Source Destination Page 13

14 Service Chaining: ETSI PoC # 28 / OPNFV, May 2015 Service Clients Huawei Qosmos BlueCoat Corsa Networks FreeScale Netronome MRV RiverBed Ixia ONF Deutsche Telecom Vodafone Application IPS FW SBI (SDN NBI) -Enabled Service Functions IDS NAT NBI Orchestrator SF Locator & Transport Cap Cache instance Non- Service Functions Load Balancer QoS VPN WOC Source Destination Page 14

15 Service Form Factors principles apply to different environments Telecoms: Mobile Gi-LAN Centralized model Typical form factor for classifier: VNF or standalone SW appliance Standardization: ETSI NFV, OpenDaylight More on qosmos.com: Datacenters Distributed model Typical form factor for classifier: hypervisor extension for vswitch Standardization : Group-Based Policy (GBP) for OpenStack, OpenDaylight More on qosmos.com: Page 15

16 Qosmos Requirements Qosmos capabilities Fast and easy service Open SDN & NFV interfaces, which makes it easy to programmatically create creation any type of service combination Lower cost for bandwidth Optimized network resources and CPU utilization thanks to packet tagging and servers mechanism based on both subscriber and application awareness which makes it possible to steer relevant traffic to relevant service nodes Lower cost for software Deployed on COTS hardware and leveraging open source software frameworks and hardware (e.g. OpenStack, OpenDaylight) Future-proof architecture Based on service chaining standards (ETSI, IETF), with provisioning through orchestrator (e.g. OpenStack) and SDN controller (e.g. OpenDaylight) Smooth migration Supports both existing and new environments: between existing and new - Tagging mechanism turns any of the L2 and L3 equipment into flow-aware architecture function Extensive recognition of networked applications - Supports physical and legacy applications with reclassification and proxy - Classifies applications, with service categories (e.g. video services) and thousands of metadata (as required) - Able to recognize and classify encrypted applications (e.g. Skype, BitTorrent) Page 16

17 Summary Service Chaining is becoming central to future Service Centric Networks (both for telecoms and DC) Service Chaining requires real-time Subscriber and Application Awareness Service Chaining requires standardization, and smooth transition between legacy and future architectures Page 17

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19 Qosmos, Qosmos ixengine, Qosmos ixmachine and Qosmos DeepFlow are trademarks or registered trademarks in France and other countries. Other company and products name mentioned herein are the trademarks or registered trademarks of their respective owners. Copyright Qosmos Non-contractual information. Products and services and their specifications are subject to change without prior notice Qosmos