My network functions are virtualized, but are they cloud-ready
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The document discusses the evaluation frameworks and metrics for assessing the cloud readiness and cloud nativeness of virtualized network functions (VNFs) in network function virtualization (NFV). It outlines three phases of cloudification, detailing performance, reliability, and agility metrics for both infrastructure and VNFs. Additionally, it emphasizes the importance of characterizing VNF performance under various configurations in order to ensure they meet operational and cost requirements in cloud environments.
![Finding the Knee Point…
Possible algorithmic methods for automatic determination of knee point:
• Check slope at each point, stop if slope gets “significantly” small relative to the first slope
• Add points (0,0), (1,T[1]), (2, T[2]), …; find best non-linear fit for TNL = a0 + a1d + a2d2 + …;
find best linear fit TL = g1d; stop when |TNL – TL|
• Use ML techniques for knee point classification
All of these methods have parameter selection problem!
?
Not straight-forward for smooth curves
d
T
m1
mk](https://image.slidesharecdn.com/fr2-mynetworkfunctionsarevirtualizedbutaretheycloud-ready-fileid-104275-170622030450/85/My-network-functions-are-virtualized-but-are-they-cloud-ready-18-320.jpg)
My network functions are virtualized, but are they cloud-ready
- 2. My Network Functions are Virtualized; But are they Cloud-Ready? Ulas C. Kozat & Yaoguang Wang Wireless Cloud and Open Source Research Center Huawei
- 3. Author Bios Ulas C. Kozat, Ph.D. • PTL in OPNFV Domino • Main technology focus is on the design of the next generation wireless network architectures, network/infrastructure modeling and optimization. Yaoguang Wang, Ph.D. • Committer in OPNFV Bottlenecks • Contributor in OPNFV Yardstick • Focuses on NFV performance evaluation, modeling and optimization.
- 4. Talk Outline 3 Phases of Cloudification Virtualization Cloud Ready Functions Cloud Native Infrastructure & VNF Performance Characterization Infrastructure Evaluation Framework & Metrics VNF Evaluation Framework & Metrics Cloud Native Function Characterization
- 5. Network Function Virtualization Cloud Ready Network Functions Cloud Native Network Functions + Scalable performance + Dynamic service chains Phase-1 Phase-2 Phase-3 + Small footprint + Fast start up + Fast failure recovery + Very dynamic micro-chains •Functional Decoupling from Hardware •Portability to Different Clouds •Automated on-boarding •Quasi static service chains 3 Phases of Cloudification
- 6. 3 Phases of Cloudification Sub-system Physical Network Functions Virtualized Network Functions PaaS Cloud Native Network Functions IaaS Targets Brown Field: Requires minimal changes for the software architecture Targets Green Field: Write functions to maximally utilize platform features Phase-1 Phase-3 Phase-2
- 7. Cloud Platform and VNF Evaluation Automation Framework, Tools, Metrics Operator Vendor X Vendor Y Cloud Platform VNF Does this platform satisfy my cost, performance, & operational requirements? Will this VNF perform well over my cloud?
- 8. NFVI Evaluation Framework: IPM • Existing Performance Testing tools/projects: • yardstick/vsperf/storperf, rally, perfkit, etc IPM Software Overview IPM Deployment
- 9. NFVI Evaluation Categories − Node − # of nodes − CPU − # of cores/cache size − Clock speed − Memory − Total DRAM − Storage − disk size − NIC − # of NIC − NIC Bandwidth Capacity − CPU Speed − Integer/Floating computation − Memory Speed − Latency/throughput − Disk Performance − iops/latency(random/seq) − Packet Transmission − Latency (ICMP/SCTP/UDP/PDCP) − Throughput (TCP/UDP/SCTP) − Packet delay variation − Packet loss rate (UDP/PDCP) − Virtualization Overhead − VM/PM, Container/PM Performance
- 10. NFVI Evaluation Categories − HW attributes − MTTF (CPU/Disk) − Self-healing − Data Replication Factor − Failover time − Detection time − Service Assurance − User plane latency assurance (UDP/PDCP) − Performance Variation in time (e.g., peak vs. non-busy hours/days) − Performance Variation over different instances (the same flavor and time) Reliability − Instance O&M − Time to boot/destroy/migration − VM/Container − Scaling Speed − Time to scale-out/in/up/down Agility − Instance distribution − VM/Container − Resource Allocation Distribution − vcpu, memory, disk Balance
- 11. Host Host Test Methodology Host e.g. Performance: − cpu speed/disk iops − virtualization overhead Reliability: − performance variation Guest (vm/container) Host e.g. Performance: − Packet transmission − virtualization overhead Reliability: − service assurance Guest (vm/container) e.g. Capacity: − resource statistics Agility: − time to boot/migration Balance: − Instance distribution Single node Multiple nodes All nodes Host Guest (vm/container) Host
- 12. Ranking Platforms with Multiple Objectives 1. Capacity: the amount of HW resources 2. Performance: characteristics of fundamental operations 3. Reliability: credibility as some conditions(time/instance) vary 4. Agility: speed of resource allocation 5. Balance: distribution of resource allocation Category Score Normalization Weighing Modeling
- 13. VNF Evaluation Framework Target: Evaluate VNF performance under different configurations User Input: SUT: VNFD, Parameter value files(Resource Vector), bootstrap mode Evaluation: metrics, method, search direction Workload: deployment, generation, parameters Traffic Generator: Built-in (iperf, pktgen, MoonGen) External (VNF owner provide)
- 14. VNF Performance Metrics Granularity − Independent VNFs, e.g. vSwitch, vDPI, vFW, vIDS, etc. − VNF-FG, e.g. vIMS, vEPC, etc. Consideration: − Functional metrics − Case-by-case: VNF Metrics Reference Virtual Switch Maximum forwarding rate (bps,pps) Latency (us) RFC 2285 bmwg-vswitch-opnfv vFirewall Maximum offered load(pps) Forwarding rate(pps) RFC 3511 vIMS Mean session setup time Successful call rate(calls/sec, w/input call rate) 3GPP TS 32.454 vEPC EPS attach success rate Mean dedicated bearer set-up time 3GPP TS 32.455
- 15. When is your VNF Cloud Ready? Cloud == Utility Based Computing == Unit Price Efficiency Double the Resources Double the Throughput Double the Price Scale Out Scale Up (T, $1) (2T, $2) (4T, $4) Scale Up Scale Down (T, $1) (T, $1) (T, $1) (2T, $2) (2T, $2) (4T, $4) Scale Out Scale In
- 16. Evaluating a VNF Max. Throughput (e.g., API-calls/sec, packets/sec, flows/sec, etc.) Measured at a specified latency and packet loss target Total VNF Resource Allocation1 2 3 4 5 y 2y 3y 4y 5y ds = Scaling Degree of VNF ds is measured at the curve knee point where linear growth phase changes to sub-linear growth This is a vectoral value with CPU, memory, disk, network bandwidth resources. Minimum resource requirement depends on the VNF implementation. Maps to the $ value Scalar performance value different for different VNF implementations
- 17. Evaluating & Ranking VNFs (T, $, ds) $ amount is computed from minimum resource requirement, i.e., $ = nCPU$CPU + nGPU$GPU + nm$m + ns$s + nnet$net + … Measured by VNF Evaluation Framework Measured by VNF Evaluation Framework ds T/$ VNF X better VNF VNF Y VNF Z worse VNF ? ?
- 18. Finding the Knee Point… Possible algorithmic methods for automatic determination of knee point: • Check slope at each point, stop if slope gets “significantly” small relative to the first slope • Add points (0,0), (1,T[1]), (2, T[2]), …; find best non-linear fit for TNL = a0 + a1d + a2d2 + …; find best linear fit TL = g1d; stop when |TNL – TL| • Use ML techniques for knee point classification All of these methods have parameter selection problem! ? Not straight-forward for smooth curves d T m1 mk
- 19. Scaling Score () Can we instead use an indirect method for comparing scaling performance? Proposal: Compare maximum flavor vs. minimum flavor in terms of price efficiency )1exp(100 $/ $/ minmin maxmax flavorflavor flavorflavor T T 1 2 3 4 5 Throughput/$ VNF Flavor ideal 1 , 100 2 , 37
- 20. Cloud Native Network Functions Qualitative features (from ETSI) Level of separation of logic and state Degree of scale-out Resource footprint (Scheduling Density) Use of accelerators VNF Resiliency Model Monitoring capabilities Abstraction and APIs exposed Testing code coming with it Plan to address in Automated VNF Evaluation Framework
- 21. Cloud Native Network Functions Logic State X Logic Logic State 1 2 3 3 time Throughput Introduce failure Relaunch instance Recovery time Scheduling Freedom Vs. Dynamic Service Chain Creation Models
- 22. Conclusions & Next Steps Presented NFVI and VNF evaluation frameworks Discussed (and proposed) evaluation categories and metrics for cloud readiness and cloud nativeness VNF evaluation framework is currently under development: (1) Cloud Readiness evaluation (2) Cloud Nativeness evaluation