| Benchmarking Working Group | M. Konstantynowicz, Ed. |
| Internet-Draft | P. Mikus, Ed. |
| Intended status: Informational | Cisco Systems |
| Expires: September 12, 2019 | March 11, 2019 |
NFV Service Density Benchmarking
draft-mkonstan-nf-service-density-00
Network Function Virtualization (NFV) system designers and operators continuously grapple with the problem of qualifying performance of network services realised with software Network Functions (NF) running on Commercial-Off-The-Shelf (COTS) servers. One of the main challenges is getting repeatable and portable benchmarking results and using them to derive deterministic operating range that is production deployment worthy.
This document specifies benchmarking methodology for NFV services that aims to address this problem space. It defines a way for measuring performance of multiple NFV service instances, each composed of multiple software NFs, and running them at a varied service "packing" density on a single server.
The aim is to discover deterministic usage range of NFV system. In addition specified methodology can be used to compare and contrast different NFV virtualization technologies.
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Network Function Virtualization (NFV) system designers and operators continuously grapple with the problem of qualifying performance of network services realised with software Network Functions (NF) running on Commercial-Off-The-Shelf (COTS) servers. One of the main challenges is getting repeatable and portable benchmarking results and using them to derive deterministic operating range that is production deployment worthy.
Lack of well defined and standardised NFV centric performance methodology and metrics makes it hard to address fundamental questions that underpin NFV production deployments:
Getting answers to these points should allow designers to make a data based decision about the NFV technology and service design best suited to meet requirements of their use cases. Equally, obtaining the benchmarking data underpinning those answers should make it easier for operators to work out expected deterministic operating range of chosen design.
The primary goal of the proposed benchmarking methodology is to focus on NFV technologies used to construct NFV services. More specifically to i) measure packet data-plane performance of multiple NFV service instances while running them at varied service "packing" densities on a single server and ii) quantify the impact of using multiple NFs to construct each NFV service instance and introducing multiple packet processing hops and links on each packet path.
The overarching aim is to discover a set of deterministic usage ranges that are of interest to NFV system designers and operators. In addition, specified methodology can be used to compare and contrast different NFV virtualisation technologies.
In order to ensure wide applicability of the benchmarking methodology, the approach is to separate NFV service packet processing from the shared virtualisation infrastructure by decomposing the software technology stack into three building blocks:
+-------------------------------+
| NFV Service |
+-------------------------------+
| Virtualization Technology |
+-------------------------------+
| Host Networking |
+-------------------------------+
Figure 1. NFV software technology stack.
Proposed methodology is complementary to existing NFV benchmarking industry efforts focusing on vSwitch benchmarking [RFC8204], [TST009] and extends the benchmarking scope to NFV services.
This document does not describe a complete benchmarking methodology, instead it is focusing on system under test configuration part. Each of the compute node configurations identified by (RowIndex, ColumnIndex) is to be evaluated for NFV service data-plane performance using existing and/or emerging network benchmarking standards. This may include methodologies specified in [RFC2544], [TST009], [draft-vpolak-mkonstan-bmwg-mlrsearch] and/or [draft-vpolak-bmwg-plrsearch].
It is assumed that each NFV service instance is built of one or more constituent NFs and is described by: topology, configuration and resulting packet path(s).
Each set of NFs forms an independent NFV service instance, with multiple sets present in the host.
NFV topology describes the number of network functions per service instance, and their inter-connections over packet interfaces. It includes all point-to-point virtual packet links within the compute node, Layer-2 Ethernet or Layer-3 IP, including the ones to host networking data-plane.
Theoretically, a large set of possible NFV topologies can be realised using software virtualisation topologies, e.g. ring, partial -/full- mesh, star, line, tree, ladder. In practice however, only a few topologies are in the actual use as NFV services mostly perform either bumps-in-a-wire packet operations (e.g. security filtering/inspection, monitoring/telemetry) and/or inter-site forwarding decisions (e.g. routing, switching).
Two main NFV topologies have been identified so far for NFV service density benchmarking:
Both topologies are shown in figures below.
NF chain topology:
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1NF1 | | S1NF2 | | S1NFn | |
| | | | | .... | | Service1 |
| | | | | | | |
| +-+----+-+ +-+----+-+ + + +-+----+-+ |
| | | | | | | | | Virtual |
| | |<-CS->| |<-CS->| |<-CS->| | Interfaces |
| +-+----+------+----+------+----+------+----+-+ |
| | | CS: Chain |
| | | Segment |
| | Host Data-Plane | |
| +-+--+----------------------------------+--+-+ |
| | | | | |
+-----------------------------------------------------------+
| | | | Physical
| | | | Interfaces
+---+--+----------------------------------+--+--------------+
| |
| Traffic Generator |
| |
+-----------------------------------------------------------+
Figure 2. NF chain topology forming a service instance.
NF pipeline topology:
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1NF1 | | S1NF2 | | S1NFn | |
| | +--+ +--+ .... +--+ | Service1 |
| | | | | | | |
| +-+------+ +--------+ +------+-+ |
| | | Virtual |
| |<-Pipeline Edge Pipeline Edge->| Interfaces |
| +-+----------------------------------------+-+ |
| | | |
| | | |
| | Host Data-Plane | |
| +-+--+----------------------------------+--+-+ |
| | | | | |
+-----------------------------------------------------------+
| | | | Physical
| | | | Interfaces
+---+--+----------------------------------+--+--------------+
| |
| Traffic Generator |
| |
+-----------------------------------------------------------+
Figure 3. NF pipeline topology forming a service instance.
NFV configuration includes all packet processing functions in NFs including Layer-2, Layer-3 and/or Layer-4-to-7 processing as appropriate to specific NF and NFV service design. L2 sub- interface encapsulations (e.g. 802.1q, 802.1ad) and IP overlay encapsulation (e.g. VXLAN, IPSec, GRE) may be represented here too as appropriate, although in most cases they are used as external encapsulation and handled by host networking data-plane.
NFV configuration determines logical network connectivity that is Layer-2 and/or IPv4/IPv6 switching/routing modes, as well as NFV service specific aspects. In the context of NFV density benchmarking methodology the initial focus is on the former.
Building on the two identified NFV topologies, two common NFV configurations are considered:
NFV packet path(s) describe the actual packet forwarding path(s) used for benchmarking, resulting from NFV topology and configuration. They are aimed to resemble true packet forwarding actions during the NFV service lifecycle.
Based on the specified NFV topologies and configurations two NFV packet paths are taken for benchmarking:
Both packet paths are shown in figures below.
Snake packet path:
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1NF1 | | S1NF2 | | S1NFn | |
| | | | | .... | | Service1 |
| | XXXX | | XXXX | | XXXX | |
| +-+X--X+-+ +-+X--X+-+ +X X+ +-+X--X+-+ |
| |X X| |X X| |X X| |X X| Virtual |
| |X X| |X X| |X X| |X X| Interfaces |
| +-+X--X+------+X--X+------+X--X+------+X--X+-+ |
| | X XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX X | |
| | X X | |
| | X Host Data-Plane X | |
| +-+X-+----------------------------------+-X+-+ |
| |X | | X| |
+----X--------------------------------------X---------------+
|X | | X| Physical
|X | | X| Interfaces
+---+X-+----------------------------------+-X+--------------+
| |
| Traffic Generator |
| |
+-----------------------------------------------------------+
Figure 4. Snake packet path thru NF chain topology.
Pipeline packet path:
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1NF1 | | S1NF2 | | S1NFn | |
| | +--+ +--+ .... +--+ | Service1 |
| | XXXXXXXXXXXXXXXXXXXXXXXX XXXXXXXXXXXX | |
| +--X-----+ +--------+ +-----X--+ |
| |X X| Virtual |
| |X X| Interfaces |
| +-+X--------------------------------------X+-+ |
| | X X | |
| | X X | |
| | X Host Data-Plane X | |
| +-+X-+----------------------------------+-X+-+ |
| |X | | X| |
+----X--------------------------------------X---------------+
|X | | X| Physical
|X | | X| Interfaces
+---+X-+----------------------------------+-X+--------------+
| |
| Traffic Generator |
| |
+-----------------------------------------------------------+
Figure 5. Pipeline packet path thru NF pipeline topology.
In all cases packets enter NFV system via shared physical NIC interfaces controlled by shared host data-plane, are then associated with specific NFV service (based on service discriminator) and subsequently are cross- connected/switched/routed by host data-plane to and through NF topologies per one of above listed schemes.
NFV services are built of composite isolated NFs, with virtualisation technology providing the workload isolation. Following virtualisation technology types are considered for NFV service density benchmarking:
Different virtual interface types are available to VNFs and CNFs:
Host networking data-plane is the central shared resource that underpins creation of NFV services. It handles all of the connectivity to external physical network devices through physical network connections using NICs, through which the benchmarking is done.
Assuming that NIC interface resources are shared, here is the list of widely available host data-plane options for providing packet connectivity to/from NICs and constructing NFV chain and pipeline topologies and configurations:
Analysing properties of each of these options and their Pros/Cons for specified NFV topologies and configurations is outside the scope of this document.
From all listed options, performance optimised Linux user-mode vswitch deserves special attention. Linux user-mode switch decouples NFV service from the underlying NIC hardware, offers rich multi-tenant functionality and most flexibility for supporting NFV services. But in the same time it is consuming compute resources and is harder to benchmark in NFV service density scenarios.
Following sections focus on using Linux user-mode vSwitch, focusing on its performance benchmarking at increasing levels of NFV service density.
In order to evaluate performance of multiple NFV services running on a compute node, NFV service instances are benchmarked at increasing density, allowing to construct an NFV Service Density Matrix. Table below shows an example of such a matrix, capturing number of NFV service instances (row indices), number of NFs per service instance (column indices) and resulting total number of NFs (values).
NFV Service Density - NF Count View SVC 001 002 004 006 008 00N 001 1 2 4 6 8 1*N 002 2 4 8 12 16 2*N 004 4 8 16 24 32 4*N 006 6 12 24 36 48 6*N 008 8 16 32 48 64 8*N 00M M*1 M*2 M*4 M*6 M*8 M*N RowIndex: Number of NFV Service Instances, 1..M. ColumnIndex: Number of NFs per NFV Service Instance, 1..N. Value: Total number of NFs running in the system.
In order to deliver good and repeatable network data-plane performance, NFs and host data-plane software require direct access to critical compute resources. Due to a shared nature of all resources on a compute node, a clearly defined resource allocation scheme is defined in the next section to address this.
In each tested configuration host data-plane is a gateway between the external network and the internal NFV network topologies. Offered packet load is generated and received by an external traffic generator per usual benchmarking practice.
It is proposed that initial benchmarks are done with the offered packet load distributed equally across all configured NFV service instances. This could be followed by various per NFV service instance load ratios mimicking expected production deployment scenario(s).
Following sections specify compute resource allocation, followed by examples of applying NFV service density methodology to VNF and CNF benchmarking use cases.
Performance optimized NF and host data-plane software threads require timely execution of packet processing instructions and are very sensitive to any interruptions (or stalls) to this execution e.g. cpu core context switching, or cpu jitter. To that end, NFV service density methodology treats controlled mapping ratios of data plane software threads to physical processor cores with directly allocated cache hierarchies as the first order requirement.
Other compute resources including memory bandwidth and PCIe bandwidth have lesser impact and as such are subject for further study. For more detail and deep-dive analysis of software data plane performance and impact on different shared compute resources is available in [BSDP].
It is assumed that NFs as well as host data-plane (e.g. vswitch) are performance optimized, with their tasks executed in two types of software threads:
Core mapping scheme described below allocates cores for all threads of specified type belonging to each NF app instance, and separately lists number of threads to a number of logical/physical core mappings for processor configurations with enabled/disabled Symmetric Multi- Threading (SMT) (e.g. AMD SMT, Intel Hyper-Threading).
If NFV service density benchmarking is run on server nodes with Symmetric Multi-Threading (SMT) (e.g. AMD SMT, Intel Hyper-Threading) for higher performance and efficiency, logical cores allocated to data- plane threads should be allocated as pairs of sibling logical cores corresponding to the hyper-threads running on the same physical core.
Separate core ratios are defined for mapping threads of vSwitch and NFs. In order to get consistent benchmarking results, the mapping ratios are enforced using Linux core pinning.
| application | thread type | app:core ratio | threads/pcores (SMT disabled) | threads/lcores map (SMT enabled) |
|---|---|---|---|---|
| vSwitch-1c | data | 1:1 | 1DT/1PC | 2DT/2LC |
| main | 1:S2 | 1MT/S2PC | 1MT/1LC | |
| vSwitch-2c | data | 1:2 | 2DT/2PC | 4DT/4LC |
| main | 1:S2 | 1MT/S2PC | 1MT/1LC | |
| vSwitch-4c | data | 1:4 | 4DT/4PC | 8DT/8LC |
| main | 1:S2 | 1MT/S2PC | 1MT/1LC | |
| NF-0.5c | data | 1:S2 | 1DT/S2PC | 1DT/1LC |
| main | 1:S2 | 1MT/S2PC | 1MT/1LC | |
| NF-1c | data | 1:1 | 1DT/1PC | 2DT/2LC |
| main | 1:S2 | 1MT/S2PC | 1MT/1LC | |
| NF-2c | data | 1:2 | 2DT/2PC | 4DT/4LC |
| main | 1:S2 | 1MT/S2PC | 1MT/1LC |
Maximum benchmarked NFV service densities are limited by a number of physical cores on a compute node.
A sample physical core usage view is shown in the matrix below.
NFV Service Density - Core Usage View vSwitch-1c, NF-1c SVC 001 002 004 006 008 010 001 2 3 6 9 12 15 002 3 6 12 18 24 30 004 6 12 24 36 48 60 006 9 18 36 54 72 90 008 12 24 48 72 96 120 010 15 30 60 90 120 150 RowIndex: Number of NFV Service Instances, 1..10. ColumnIndex: Number of NFs per NFV Service Instance, 1..10. Value: Total number of physical processor cores used for NFs.
To illustrate defined NFV service density applicability, following sections describe three sets of NFV service topologies and configurations that have been benchmarked in open-source: i) in [LFN-FDio-CSIT], a continuous testing and data-plane benchmarking project, and ii) as part of CNCF CNF Testbed initiative [CNCF-CNF-Testbed].
In both cases each NFV service instance definition is based on the same set of NF applications, and varies only by network addressing configuration to emulate multi-tenant operating environment.
Initial NFV density throughput benchmarks have been performed using Maximum Receive Rate (MRR) test methodology defined and used in FD.io CSIT.
MRR tests measure the packet forwarding rate under the maximum load offered by traffic generator over a set trial duration, regardless of packet loss. Maximum load for specified Ethernet frame size is set to the bi-directional link rate (2x 10GbE in referred results).
Tests were conducted with two traffic profiles: i) continuous stream of 64B frames, ii) continuous stream of IMIX sequence of (7x 64B, 4x 570B, 1x 1518B), all sizes are L2 untagged Ethernet.
NFV service topologies tested include: VNF service chains, CNF service chains and CNF service pipelines.
VNF Service Chain (VSC) topology is tested with KVM hypervisor (Ubuntu 18.04-LTS), with NFV service instances consisting of NFs running in VMs (VNFs). Host data-plane is provided by FD.io VPP vswitch. Virtual interfaces are virtio-vhostuser. Snake forwarding packet path is tested using [TRex] traffic generator, see figure.
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1VNF1 | | S1VNF2 | | S1VNFn | |
| | | | | .... | | Service1 |
| | XXXX | | XXXX | | XXXX | |
| +-+X--X+-+ +-+X--X+-+ +-+X--X+-+ |
| |X X| |X X| |X X| Virtual |
| |X X| |X X| |X X| |X X| Interfaces |
| +-+X--X+------+X--X+------+X--X+------+X--X+-+ |
| | X XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX X | |
| | X X | |
| | X FD.io VPP vSwitch X | |
| +-+X-+----------------------------------+-X+-+ |
| |X | | X| |
+----X--------------------------------------X---------------+
|X | | X| Physical
|X | | X| Interfaces
+---+X-+----------------------------------+-X+--------------+
| |
| Traffic Generator (TRex) |
| |
+-----------------------------------------------------------+
Figure 6. VNF service chain test setup.
CNF Service Chain (CSC) topology is tested with Docker containers (Ubuntu 18.04-LTS), with NFV service instances consisting of NFs running in Containers (CNFs). Host data-plane is provided by FD.io VPP vswitch. Virtual interfaces are memif. Snake forwarding packet path is tested using [TRex] traffic generator, see figure.
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1CNF1 | | S1CNF2 | | S1CNFn | |
| | | | | .... | | Service1 |
| | XXXX | | XXXX | | XXXX | |
| +-+X--X+-+ +-+X--X+-+ +-+X--X+-+ |
| |X X| |X X| |X X| Virtual |
| |X X| |X X| |X X| |X X| Interfaces |
| +-+X--X+------+X--X+------+X--X+------+X--X+-+ |
| | X XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX X | |
| | X X | |
| | X FD.io VPP vSwitch X | |
| +-+X-+----------------------------------+-X+-+ |
| |X | | X| |
+----X--------------------------------------X---------------+
|X | | X| Physical
|X | | X| Interfaces
+---+X-+----------------------------------+-X+--------------+
| |
| Traffic Generator (TRex) |
| |
+-----------------------------------------------------------+
Figure 7. CNF service chain test setup.
CNF Service Pipeline (CSP) topology is tested with Docker containers (Ubuntu 18.04-LTS), with NFV service instances consisting of NFs running in Containers (CNFs). Host data-plane is provided by FD.io VPP vswitch. Virtual interfaces are memif. Pipeline forwarding packet path is tested using [TRex] traffic generator, see figure.
+-----------------------------------------------------------+
| Host Compute Node |
| |
| +--------+ +--------+ +--------+ |
| | S1NF1 | | S1NF2 | | S1NFn | |
| | +--+ +--+ .... +--+ | Service1 |
| | XXXXXXXXXXXXXXXXXXXXXXXX XXXXXXXXXXXX | |
| +--X-----+ +--------+ +-----X--+ |
| |X X| Virtual |
| |X X| Interfaces |
| +-+X--------------------------------------X+-+ |
| | X X | |
| | X X | |
| | X FD.io VPP vSwitch X | |
| +-+X-+----------------------------------+-X+-+ |
| |X | | X| |
+----X--------------------------------------X---------------+
|X | | X| Physical
|X | | X| Interfaces
+---+X-+----------------------------------+-X+--------------+
| |
| Traffic Generator (TRex) |
| |
+-----------------------------------------------------------+
Figure 8. CNF service chain test setup.
FD.io CSIT project introduced NFV density benchmarking in release CSIT-1901 and published results for the following NFV service topologies and configurations:
More information is available in FD.io CSIT-1901 report, with specific references listed below:
CNCF CI team introduced a CNF testbed initiative focusing on benchmaring NFV density with open-source network applications running as VNFs and CNFs. Following NFV service topologies and configurations have been tested to date:
More information is available in CNCF CNF Testbed github, with summary test results presented in summary markdown file, references listed below:
No requests of IANA
..
Thanks to Vratko Polak of FD.io CSIT project and Michael Pedersen of the CNCF Testbed initiative for their contributions and useful suggestions.
| [RFC2544] | Bradner, S. and J. McQuaid, "Benchmarking Methodology for Network Interconnect Devices", RFC 2544, DOI 10.17487/RFC2544, March 1999. |
| [RFC8174] | Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC 2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174, May 2017. |