NFV: A Dynamic, Multi-Layer Resource Optimization Challenge. Manjari Asawa Product Management, HPE

Transcription

1 NFV: A Dynamic, Multi-Layer Resource Optimization Challenge Manjari Asawa Product Management, HPE

2 Agenda Why NFV Dynamic, Multi-layer Resource Optimization Implementation Approach

3 Early 2010s: Virtualization became common in IT with VmWare ESXi, kvm X86 advances allowed faster I/O and faster packet processing Rackspace & NASA launched open-source OpenStack cloud orchestrator Intel released software libraries and driver for fast packet processing (DPDK) Advances in Programmable networks (SDN)

4 NFV White Paper: Oct, 2012 Operators dilemma New service required procuring and installing new hardware Large variety of proprietary hardware Competition from OTT Players required fast new service rollouts New ETSI initiative launched at&t, BT, CenturyLink, China Mobile, Colt, DT, KDDI, NTT, Orange, TI, Telefonica, Telstra & VZ Aim to leverage virtualization for Use of standard servers and storage Efficient resource sharing and utilization Faster time to market Flexible and programmable operations

5 Vision for NFV* *Source: ETSI White Paper

6 Evolution to Telco Cloud* *Source: ETSI White Paper

7 Enterprise vs Telco Cloud Enterprise Cloud Telco cloud Few Large DCs (Primary and DR IT DCs) Many and Small VMs: referred as Cattles Larger packet size for user applications Limited by CPU Performance Standard, out-of-box platform software Many smaller and distributed service center: POPs Few and Large VMs: Referred as Pets Small packet size for network switching and voice app Limited by both CPU and I/O Performance Software is often augmented with hardware 10G, Software only switching 40G, low latency and jitter requires hardware techniques such as SR-IOV, PCI-PT.

8 ETSI NFV Reference Architecture* *Source: ETSI White Paper

9 Mobile IMS (VoLTE) Architecture 2G/3G Ckt Switched Core + SMSC 4G IMS Regulatory (PSAP, CALEA, location) Ml/Mm/Mi/Mg X1/X2/X3 Rx DRA PCRF Charging Rf Cx HSS Sh CAMEL/MAP/Gd ISC SCC-AS IM-SSF IP-SM-GW TAS Mr ISC Serving-GW Other Services e.g. RCS, Voice Mail IPX/NNI SIP VoIP network S-GW LTE EPC (P0) E-CSCF Mw P-CSCF/SBC enodeb Mw S/I-CSCF LTE/Wi-Fi Ml P-GW BGCF Mr MRF epdg Untrusted Wi-Fi (P0) Mg Mj Mb TWAG Trusted Wi-Fi (P1) IBCF/TrGW MGCF/SigGW/ MGW TDM/SS7 PSTN/PLMN (TDM/SS7)

10 Deploying IMS in Virtualized Architecture Orchestration, OSS, BSS NFV Orchestrator HPE IMS VNFs HSS, MRF, OCCP (TAS,SCC-AP, IM-SSF, IP- SM GW) Field Integrated Apps NFVI Layer Compute Virtualization (KVM, vmware) Specialized HW Servers Storage Networking Network Virtualization WAN Network SDN Controller Infrastructure Management VIM (Openstack)

11 Multi-layer, Dynamic, Resource Optimization

12 vims Service Components Applications E.g. Mobile Registration, Call Origination Orchestration Services (composite VMs) Virtual Topology Physical Topology Physical Resources E.g. SBC, S-CSCF, TAS E.g.: SBC VM1, SBC LB, SBC Route Selector, Overlay n/w E.g.: Physical Connectivity among resources E.g.: Compute 1 CPU, compute 2 memory, NIC 3 Policies Constraints Service Chaining Performance Management Life Cycle Management

13 Physical Data Center Architecture Source: NFV: Report on SDN Usage in NFV Architectural Framework (

14 NFV Platform Requirements Orchestration: On-boarding, global resource management, authorization VNF Management: Lifecycle management, configuration, event reporting Virtualized Infrastructure Management (VIM): Control and management of the NFVI compute, storage, and network Service Performance: E.g. mouth-to-ear delay should be less than 200 msec. Operational: Minimize power consumption Adoption to traffic conditions High availability Security, co-existence with existing platforms, software upgrades etc.

15 Hierarchical Controller Options* Single SDN Controller for WAN Unique abstraction per client for WAN resources *Source: NFV: Report on SDN Usage in NFV Architectural Framework ( Each client has direct access to WAN resource.

16 Hierarchical, Distributed, Resource Allocation Objective: Optimal resource allocation and scheduling at each layer. Environment: Fast, Real-time action and response Distributed, stochastic, dynamic information Approach: Understand application requirements Understand VNFs Know infrastructure Formalize scheduling problem accounting for Translation of application requirement to VNF and service function chains requirements Efficient placement of VNFs onto physical infrastructure

17 Understand Application in terms of VNFs Understand Application Requirements User experience should be comparable to traditional networks. Decomposition of monolithic applications to smaller functions. Critical Open Problems: Efficient placement and chaining of virtual network functions. Optimal decomposition point of services (tradeoffs between elasticity and delay) Description of NS, VNFs, their relationships, performance requirements (descriptors) More Source: ETSI GS NFV 002: NFV Architectural Framework.

18 ETSI E2E Network Service Graph Representation* *Source: ETSI GS NFV 002: NFV Architectural Framework.

19 Understand VNFs VNFs are getting complex Need to work with database, processes Often requires high availability Self-healing and auto-scaling properties Interdependencies Dependencies between VNFs and to external network. Framework is needed to understand VNFs and interdepdencies Dependency on operating conditions Need of dynamic characterization Definition of appropriate measurement metrics Use of Machine Learning to predict changes to traffic, SLAs etc.

20 Registration Requests/sec VNF Performance with Different Configuration* 1000 Clearwater Performance Characterization Homer Ellis Bono Sprout Homestead Ralf Clearwater * Source: NFV-VITAL: A framework for characterizing the performance of virtual network functions, Cao et.al., 1 st IEEE NFVSDN Conference, San Francisco, November 2015 bono1small-sprout1small-homestead1small bono1medium-sprout1medium-homestead1medium bono1large-sprout1large-homestead1large bono1medium-sprout2small-homestead2small bono1large-sprout2medium-homestead2medium

21 Know Your Infrastructure in Detail Compute resource parameters vcpu, CPU partitioning, CPU model Huge pages, NUMA support, vswitch capabilities and requirements NICs - speeds and feeds of NICs capabilities such as SR-IOV Network Layout Connectivity Link bandwidth Storage How much, where Location and connectivity among and within data centers

22 VNF Capacity (K packets per sec.) Performance Variation on Heterogeneous Servers* Not all servers are created equal 250 VNF Performance for different Server Configurations Different servers exhibit different performance for different VNFs 150 Server support for different virtualization and optimization knobs e.g. SR-IOV, CPU speed, NUMA etc. Varying VNF requirements e.g. data plane throughput, storage access rates etc * Source: NFV-VITAL: A framework for characterizing the performance of virtual network functions, Cao et.al., 1 st IEEE NFVSDN Conference, San Francisco, November Snort Suricata VNF ServerConfig1(1.2Ghz) ServerConfig2(2.0Ghz) ServerConfig3(2,8Ghz)

23 Once we understand applications, VNFs and infrastructure, how to manage VNFs and Infrastructure mapping to meet application requirements efficiently?

24 Formalize Options at Each Layer Applications: How much to decompose and how NS: How many VNFs, and forwarding graph among them. VNFs: Scale up or Scale-out Determine the way it scales Watch for noisy neighbors Auto-scale, auto-migrate Compute Processor types NICs/Ports types and numbers Decision at one layer affects performance of the others

25 Optimally Allocate Resources Should understand application and constraints. Should be hierarchical with abstraction at every layer Should keep detailed inventory Should be contextual: The right thing to do may not be the same Contexual information should be represented and available Should be dynamic with fast response time

26 Intent Driven Framework Translate application requirement to action Method to describe intent Map intent to appropriate technology Things to consider during mapping State of VNFs (application analytics: include prediction) Current state of infrastructure (performance analytics) Environment constraints Management constraints Mechanism to resolve conflicts

27 Implementation Approach

28 Open Source Approaches* Standards Open Source OSS / BSS Open Source VNFs NFV ISG *Source: OPNFV

29 OpenStack Architecture* * Source:

30 Nova Filter Scheduler* Uses knowledge of VNF and infrastructure to filter out the computes. * Source: Openstack configuration guide

31 Scheduler projects Nova scheduler Simple and fast. Projects such as watcher, blazar will bring more intelligence and control. Other open-source projects : Mesos, Kubertenes IBM Platform Resource Scheduler: Dynamic, intelligent, policy-driven resource scheduler HPE labs Stringer : Accounts for heterogenous nodes, service chaining, integer programming. Research: Network-Aware Round Robin (NARR) Elastic Edge (E2) framework More

32 Watcher Architecture* *Source: Openstack wiki

33 Some NFV Related Open-source Projects Name Tacker Openstack Blazar, OPNFV Promise Kingbird Watcher Congress Network Intent Composition (NIC) Doctor (OPNFV) Description Generic VNF Manager (VNFM) and a NFV Orchestrator (NFVO) to deploy and operate Network Services and Virtual Network Functions (VNFs) on an NFV infrastructure Resource reservation and management : user can request the resources of cloud environment to be provided ( leased ) to his/her project for a specific amount of time, immediately or in future. Centralized service for resource management across multiple OpenStack instances in a multi-region deployment, such as centralized quota management, centralized view for distributed virtual resources, global view of tenant address space, synchronization of ssh keys, images, flavors, security groups, etc. Watcher provides a flexible and scalable complete resource optimization service. Include metric receiver, optimization processor and action plan applier using machine learning algorithms. Can run in advise only mode or active mode. Framework for governance and regulatory compliance across services (e.g. application, network, compute and storage) within a dynamic infrastructure. Use a high-level, general purpose, declarative language to describe which states of the cloud are in compliance and which are not, and allows enforcement. Enables the controller to manage and direct network services and network resources based on describing the Intent for network behaviors and policies instead of describing how to provide different services. NFVI fault management and maintenance framework supporting high availability of the Network Services on top of the virtualized infrastructure.

34 Relationship Among Projects Policy Congr ess Copper NIC Promise (Resource Reservation) Blazar MANO TOSCA NFV profile NFVO Watcher VNFs Service Function Chaining VNF1 VNF2 VNF3 Tacker Prediction Ceilo meter Heat VIM Virtual compute NetVirt Virtual network OVSDB Virtual storage Monasca Doctor ODL controller KVM KVM NFV OVS OVS NFV Ceph Nova Neutron compute network storage Vitrage (Root cause analysis) Monitoring Infrastructure NFVI OPNFV OPENSTACK ODL

35 Verizon SDN-NFV Architecture* *Source: Verizon Network Infrastructure Planning: SDN-NFV Reference Architecture

36 at&t ECOMP architecture* *Source: ECOMP (Enhanced Control, Orchestration, Management & Policy) Architecture White Paper,

37 Summary Dynamic and stochastic environment Applications are demanding Hierarchical control is a necessity End-to-end optimization framework is needed.

38 Happy Birthday, Demos