Methodology for VNF Benchmarking Automation
draft-rosa-bmwg-vnfbench-02
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draft-rosa-bmwg-vnfbench-02
BMWG R. Rosa, Ed.
Internet-Draft C. Rothenberg
Intended status: Informational UNICAMP
Expires: January 3, 2019 M. Peuster
H. Karl
UPB
July 2, 2018
Methodology for VNF Benchmarking Automation
draft-rosa-bmwg-vnfbench-02
Abstract
This document describes a common methodology for automated
benchmarking of Virtualized Network Functions (VNFs) executed on
general-purpose hardware. Specific cases of benchmarking
methodologies for particular VNFs can be derived from this document.
Two open source reference implementations are reported as running
code embodiments of the proposed, automated benchmarking methodology.
Status of This Memo
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provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on January 3, 2019.
Copyright Notice
Copyright (c) 2018 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
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to this document. Code Components extracted from this document must
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the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
4. Considerations . . . . . . . . . . . . . . . . . . . . . . . 4
4.1. VNF Testing Methods . . . . . . . . . . . . . . . . . . . . 4
4.2. Generic VNF Benchmarking Setup . . . . . . . . . . . . . . 5
4.3. Deployment Scenarios . . . . . . . . . . . . . . . . . . . 7
4.4. Influencing Aspects . . . . . . . . . . . . . . . . . . . . 8
5. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . 9
5.1. VNF Benchmarking Descriptor (VNF-BD) . . . . . . . . . . . 10
5.1.1. Procedures Configuration . . . . . . . . . . . . . . . . 10
5.1.2. Target Information . . . . . . . . . . . . . . . . . . . 10
5.1.3. Deployment Scenario . . . . . . . . . . . . . . . . . . . 10
5.2. VNF Performance Profile (VNF-PP) . . . . . . . . . . . . . 11
5.2.1. Execution Environment . . . . . . . . . . . . . . . . . . 12
5.2.2. Measurement Results . . . . . . . . . . . . . . . . . . . 12
5.3. Automated Benchmarking Procedures . . . . . . . . . . . . . 13
5.4. Particular Cases . . . . . . . . . . . . . . . . . . . . . 15
6. Open Source Reference Implementations . . . . . . . . . . . . 16
6.1. Gym . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
6.2. tng-bench . . . . . . . . . . . . . . . . . . . . . . . . . 17
7. Security Considerations . . . . . . . . . . . . . . . . . . . 18
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 18
9. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 18
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 18
10.1. Normative References . . . . . . . . . . . . . . . . . . . 18
10.2. Informative References . . . . . . . . . . . . . . . . . . 19
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 20
1. Introduction
Benchmarking Methodology Working Group (BMWG) initiated efforts,
approaching considerations in [RFC8172], to develop methodologies for
benchmarking VNFs. Similarly described in [RFC8172], VNF benchmark
motivating aspects define: (i) pre-deployment infrastructure
dimensioning to realize associated VNF performance profiles; (ii)
comparison factor with physical network functions; (iii) and output
results for analytical VNF development.
Having no strict and clear execution boundaries, different from
earlier self-contained black-box benchmarking methodologies described
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in BMWG, a VNF depends on underlying virtualized environment
parameters [ETS14a], intrinsic factors to be analyzed when one
investivages the performance of a VNF. This document stands as a
ground methodology guide for VNF benchmarking automation. It
addresses the state-of-the-art publications and the current
developments in similar standardization efforts (e.g., [ETS14c] and
[RFC8204]) towards bechmarking VNFs.
Automating the extraction of VNF performance metrics propitiates: (i)
the development of agile performance-focused DevOps methodologies for
Continuous Integration and Delivery (CI/CD) of VNFs; (ii) the
creation of on-demand VNF test descriptors for upcoming execution
environments; (iii) the path for precise-analytics of extensively
automated catalogues of VNF performance profiles; (iv) and run-time
profiling mechanisms to assist VNF lifecycle orchestration/management
workflows.
2. Terminology
Common benchmarking terminology contained in this document is derived
from [RFC1242]. Also, the reader is assumed to be familiar with the
terminology as defined in the European Telecommunications Standards
Institute (ETSI) NFV document [ETS14b]. Some of these terms, and
others commonly used in this document, are defined below.
NFV: Network Function Virtualization - The principle of separating
network functions from the hardware they run on by using virtual
hardware abstraction.
NFVI PoP: NFV Infrastructure Point of Presence - Any combination of
virtualized compute, storage and network resources.
NFVI: NFV Infrastructure - Collection of NFVI PoPs under one
orchestrator.
VIM: Virtualized Infrastructure Manager - functional block that is
responsible for controlling and managing the NFVI compute, storage
and network resources, usually within one operator's
Infrastructure Domain (e.g. NFVI-PoP).
VNFM: Virtualized Network Function Manager - functional block that
is responsible for controlling and managing the VNF life-cycle.
NFVO: NFV Orchestrator - functional block that manages the Network
Service (NS) life-cycle and coordinates the management of NS life-
cycle, VNF life-cycle (supported by the VNFM) and NFVI resources
(supported by the VIM) to ensure an optimized allocation of the
necessary resources and connectivity.
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VNF: Virtualized Network Function - a software-based network
function. A VNF can be either represented by a single entity or
be composed by a set of smaller, interconnected software
components, called VNF components (VNFCs) [ETS14d]. Those VNFs
are also called composed VNFs.
VNFD: Virtualised Network Function Descriptor - configuration
template that describes a VNF in terms of its deployment and
operational behaviour, and is used in the process of VNF on-
boarding and managing the life cycle of a VNF instance.
VNFC: Virtualized Network Function Component - a software component
that implements (parts of) the VNF functionality. A VNF can
consist of a single VNFC or multiple, interconnected VNFCs
[ETS14d]
VNF-FG: Virtualized Network Function Forwarding Graph - an ordered
list of VNFs or VNFCs creating a service chain.
3. Scope
This document assumes VNFs as black boxes when defining their
benchmarking methodologies. White box approaches are assumed and
analysed as a particular case under the proper considerations of
internal VNF instrumentation, later discussed in this document.
In what follows, this document outlines a basis methodology for VNF
benchmarking, specifically addressing its automation.
4. Considerations
VNF benchmarking considerations are defined in [RFC8172].
Additionally, VNF pre-deployment testing considerations are well
explored in [ETS14c].
4.1. VNF Testing Methods
Following the ETSI's model in [ETS14c], we distinguish three methods
for VNF evaluation:
Benchmarking: Where parameters (e.g., cpu, memory, storage) are
provided and the corresponding performance metrics (e.g., latency,
throughput) are obtained. Note, such request might create
multiple reports, for example, with minimal latency or maximum
throughput results.
Verification: Both parameters and performance metrics are provided
and a stimulus verify if the given association is correct or not.
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Dimensioning: Where performance metrics are provided and the
corresponding parameters obtained. Note, multiple deployment
interactions may be required, or if possible, underlying allocated
resources need to be dynamically altered.
Note: Verification and Dimensioning can be reduced to Benchmarking.
Therefore, we detail Benchmarking in what follows.
4.2. Generic VNF Benchmarking Setup
A generic VNF benchmarking setup is shown in Figure 1, and its
components are explained below. Note here, not all components are
mandatory, and VNF benchmarking scenarios, further explained, can
dispose its components in varied settings.
+---------------+
| Manager |
Control | (Coordinator) |
Interface +---+-------+---+
+--------+-----------+ +-------------------+
| | |
| | +-------------------------+ |
| | | System Under Test | |
| | | | |
| | | +-----------------+ | |
| +--+------- + VNF | | |
| | | | | |
| | | +----+ +----+ | | |
| | | |VNFC|...|VNFC| | | |
| | | +----+ +----+ | | |
| | +----.---------.--+ | |
+-----+---+ | Monitor | : : | +-----+----+
| Agent | |{listeners}|----^---------V--+ | | Agent |
|(Sender) | | | Execution | | |(Receiver)|
| | | | Environment | | | |
|{Probers}| +-----------| | | |{Probers} |
+-----.---+ | +----.---------.--+ | +-----.----+
: +---------^---------V-----+ :
V : : :
:................>.....: :............>..:
Stimulus Traffic Flow
Figure 1: Generic VNF Benchmarking Setup
Agent -- executes active stimulus using probers, i.e., benchmarking
tools, to benchmark and collect network and system performance
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metrics. While a single Agent is capable of performing localized
benchmarks in execution environments (e.g., stress tests on CPU,
memory, disk I/O), the interaction among distributed Agents enable
the generation and collection of VNF end-to-end metrics (e.g.,
frame loss rate, latency). In a benchmarking setup, one Agent can
create the stimuli and the other end be the VNF itself where, for
example, one-way latency is evaluated. An Agent can be defined by
a physical or virtual network function.
Prober -- defines a software/hardware-based tool able to generate
stimulut traffic specific to a VNF (e.g., sipp) or generic to
multiple VNFs (e.g., pktgen). A Prober must provide
programmable interfaces for its life cycle management
workflows, e.g., configuration of operational parameters,
execution of stilumi, parsing of extracted metrics, and
debugging options. Specific Probers might be developed to
abstract and to realize the description of particular VNF
benchmarking methodologies.
Monitor -- when possible, it is instantiated inside the target VNF
or NFVI PoP (e.g., as a plug-in process in a virtualized
environment) to perform passive monitoring, using listeners, for
metrics collection based on benchmark tests evaluated according to
Agents` stimuli. Different from the active approach of Agents
that can be seen as generic benchmarking VNFs, Monitors observe
particular properties according to NFVI PoPs and VNFs
capabilities. A Monitor can be defined as a virtual network
function.
Listener -- defines one or more software interfaces for the
extraction of particular metrics monitored in a target VNF and/
or execution environment. A Listener must provide programmable
interfaces for its life cycle management workflows, e.g.,
configuration of operational parameters, execution of
monitoring captures, parsing of extracted metrics, and
debugging options. White-box benchmarking approaches must be
carefully analyzed, as varied methods of performance monitoring
might be coded as a Listener, possibly impacting the VNF and/or
execution environment performance results.
Manager -- in a VNF benchmarking setup, a Manager is responsible for
(i) the coordination and synchronization of activities of Agents
and Monitors, (ii) collecting and parsing all VNF benchmarking
results, and (iii) aggregating the inputs and parsed benchmark
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outputs to construct a VNF performance profile, which defines a
report that correlates the VNF stimuli and the monitored metrics.
A Manager executes the main configuration, operation, and
management actions to deliver the VNF benchmarking results. A
Manager can be defined as a physical or virtual network function,
and be split into multiple sub-components, each responsible for
separated functional aspects of the overall Manager component.
Virtualized Network Function (VNF) -- consists of one or more
software components, so called VNF components (VNFC), adequate for
performing a network function according to allocated virtual
resources and satisfied requirements in an execution environment.
A VNF can demand particular configurations for benchmarking
specifications, demonstrating variable performance profiles based
on available virtual resources/parameters and configured
enhancements targeting specific technologies (e.g., NUMA, SR-IOV,
CPU-Pinning).
Execution Environment -- defines a virtualized and controlled
composition of capabilities necessary for the execution of a VNF.
An execution environment stands as a general purpose level of
virtualization with abstracted resources available for one or more
VNFs. It can also define specific technology habilitation,
incurring in viable settings for enhancing the performance of
VNFs.
4.3. Deployment Scenarios
A VNF benchmark deployment scenario establishes the physical and/or
virtual instantiation of components defined in a VNF benchmarking
setup.
The following considerations hold for deployment scenarios:
o Components can be composed in a single entity and be defined as
black or white boxes. For instance, Manager and Agents could
jointly define one hardware/software entity to perform a VNF
benchmark and present results.
o Monitor is not a mandatory component and must be considered only
when performed white box benchmarking approaches for a VNF and/or
its execution environment.
o Monitor can be defined by multiple instances of software
components, each addressing a VNF or execution environment and
their respective open interfaces for the extraction of metrics.
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o Agents can be disposed in varied topology setups, included the
possibility of multiple input and output ports of a VNF being
directly connected each in one Agent.
o All benchmarking components defined in a deployment scenario must
perform the synchronization of clocks.
4.4. Influencing Aspects
In general, VNF benchmarks must capture relevant causes of
performance variability. Concerning a deployment scenario,
influencing aspects on the performance of a VNF can be observed in:
Deployment Scenario Topology: The disposition of components can
define particular interconnections among them composing a specific
case/method of VNF benchmarking.
Execution Environment: The availability of generic and specific
capabilities satisfying VNF requirements define a skeleton of
opportunities for the allocation of VNF resources. In addition,
particular cases can define multiple VNFs interacting in the same
execution environment of a benchmarking setup.
VNF: A detailed description of functionalities performed by a VNF
sets possible traffic forwarding and processing operations it can
perform on packets, added to its running requirements and specific
configurations, which might affect and compose a benchmarking
setup.
Agent: The toolset available for the benchmarking stimulus of a VNF
and its characteristics of packets format and workload can
interfere in a benchmarking setup. VNFs can support specific
traffic format as stimulus.
Monitor: In a particular benchmarking setup where measurements of
VNF and/or execution environment metrics are available for
extraction, an important analysis consist in verifying if the
Monitor components can impact performance metrics of the VNF and
the underlying execution environment.
Manager: The overall composition of VNF benchmarking procedures can
determine arrangements of internal states inside a VNF, which can
interfere in observed benchmarking metrics.
The listed influencing aspects must be carefully analyzed while
automating a VNF benchmarking methodology.
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5. Methodology
Portability is an intrinsic characteristic of VNFs and allows them to
be deployed in multiple environments. This enables various
benchmarking procedures in varied deployment scenarios. A VNF
benchmarking methodology must be described in a clear and objective
manner in order to allow effective repeatability and comparability of
the test results. Those results, the outcome of a VNF benchmarking
process, are captured in a VNF Benchmarking Report (VNF-BR) as shown
in Figure 2.
X
/ \
/ \
/ \
+--------+ / \
| | / \
| VNF-BD |--(defines)-->| Benchmark |
| | \ Process /
+--------+ \ /
\ /
\ /
\ /
V
|
(generates)
|
v
+-------------------------+
| VNF-BR |
| +--------+ +--------+ |
| | | | | |
| | VNF-BD | | VNF-PP | |
| | {copy} | | | |
| +--------+ +--------+ |
+-------------------------+
Figure 2: VNF benchmarking process inputs and outputs
VNF Benchmarking reports comprise two parts:
VNF Benchmarking Descriptor (VNF-BD) -- contains all required
definitions and requirements to configure, execute and reproduce
VNF benchmarking experiments. VNF-BDs are defined by the
developer of a benchmarking experiment and serve as input to the
benchmarking process, before being included in the generated VNF-
BR.
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VNF Performance Profile (VNF-PP) -- contains all measured metrics
resulting from the execution of a benchmark. Additionally, it
might also contain additional recordings of configuration
parameters used during the execution of the benchmarking scenario
to facilitate comparability of VNF-BRs.
A VNF-BR correlates structural and functional parameters of VNF-BD
with extracted VNF benchmarking metrics of the obtained VNF-PP. The
content of each part of a VNF-BR is described in the following
sections.
5.1. VNF Benchmarking Descriptor (VNF-BD)
VNF Benchmarking Descriptor (VNF-BD) -- an artifact that specifies a
method of how to measure a VNF Performance Profile. The
specification includes structural and functional instructions and
variable parameters at different abstraction levels (e.g., topology
of the deployment scenario, benchmarking target metrics, parameters
of benchmarking components). VNF-BD may be specific to a VNF or
applicable to several VNF types. A VNF-BD can be used to elaborate a
VNF benchmark deployment scenario aiming at the extraction of
particular VNF performance metrics.
The following items define the VNF-BD contents.
5.1.1. Procedures Configuration
The definition of parameters concerning the execution of the
benchmarking procedures (see Section 5.3), for instance, containing
the number of repetitions and duration of each test.
5.1.2. Target Information
General information addressing the target VNF, with references to any
of its specific characteristics (e.g., type, model, version/release,
architectural components, etc). In addition, it defines the metrics
to be extracted when running the benchmarking tests.
5.1.3. Deployment Scenario
This section of a VNF-BD contains all information needed to describe
the deployment of all involved components used during the
benchmarking test.
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5.1.3.1. Topology
Information about the experiment topology, concerning the disposition
of the components in a benchmarking setup (see Section 4.2). It must
define the role of each component and how they are interconnected
(i.e., interface, link and network characteristics).
5.1.3.2. Requirements
Involves the definition of execution environment requirements to
execute the tests. Therefore, they concern all required capabilities
needed for the execution of the target VNF and the other components
composing the benchmarking setup. Examples of specifications
involve: min/max allocation of resources, specific enabling
technologies (e.g., DPDK, SR-IOV, PCIE).
5.1.3.3. Parameters
Involves any specific configuration of benchmarking components in a
setup described the the deployment scenario topology.
VNF Configurations: Defines any specific configuration that must be
loaded into the VNF to execute the benchmarking experiments (e.g.,
routing table, firewall rules, vIMS subscribers profile).
VNF Resources: Contains particular VNF resource configurations that
should be tested during the benchmarking process, e.g., test the
VNF for configurations with 2, 4, and 8 vCPUs associated.
Agents: Defines the configured toolset of available probers and
related benchmarking/active metrics, available workloads, traffic
formats/traces, and configurations to enable hardware capabilities
(if existent).
Monitors: defines the configured toolset of available listeners and
related monitoring/passive metrics, configuration of the
interfaces with the monitoring target (VNF and/or execution
environment), and configurations to enable specific hardware
capabilities (if existent).
5.2. VNF Performance Profile (VNF-PP)
VNF Performance Profile (VNF-PP) -- defines a mapping between
resources allocated to a VNF (e.g., CPU, memory) as well as assigned
configurations (e.g., routing table used by the VNF) and the VNF
performance metrics (e.g., throughput, latency between in/out ports)
obtained in a benchmarking test conducted using a VNF-BD. Logically,
packet processing metrics are presented in a specific format
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addressing statistical significance (e.g., median, standard
deviation, percentiles) where a correspondence among VNF parameters
and the delivery of a measured VNF performance exists.
The following items define the VNF-PP contents.
5.2.1. Execution Environment
Execution environment information is has to be included in every VNF-
PP and is required to describe the environment on which a benchmark
was actually executed.
Ideally, any person who has a VNF-BD and its complementing VNF-PP
with its execution environment information available, must be able to
reproduce the same deployment scenario and VNF benchmarking tests to
obtain identical VNF-PP measurement results.
If not already defined by the VNF-BD deployment scenario requirements
(Section 5.1.3), for each component in the VNF benchmarking setup,
the following topics must be detailed:
Hardware Specs: Contains any information associated with the
underlying hardware capabilities offered and used by the component
during the benchmarking tests. Examples of such specification
include allocated CPU architecture, connected NIC specs, allocated
memory DIMM, etc. In addition, any information concerning details
of resource isolation must also be described in this part of the
VNF-PP.
Software Specs: Contains any information associated with the
software apparatus offered and used during the benchmarking tests.
Examples include versions of operating systems, kernels,
hypervisors, container image versions, etc.
Optionally, a VNF-PP execution environment might contain references
to an orchestration description document (e.g., HEAT template) to
clarify technological aspects of the execution environment and any
specific parameters that it might contain for the VNF-PP.
5.2.2. Measurement Results
Measurement results concern the extracted metrics, output of
benchmarking procedures, classified into:
VNF Processing/Active Metrics: Concerns metrics explicitly defined
by or extracted from direct interactions of Agents with a VNF.
Those can be defined as generic metric related to network packet
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processing (e.g., throughput, latency) or metrics specific to a
particular VNF (e.g., vIMS confirmed transactions, DNS replies).
VNF Monitored/Passive Metrics: Concerns the Monitors' metrics
captured from a VNF execution, classified according to the
virtualization level (e.g., baremetal, VM, container) and
technology domain (e.g., related to CPU, memory, disk) from where
they were obtained.
Depending on the configuration of the benchmarking setup and the
planned use cases for the resulting VNF-PPs, measurement results can
be stored as raw data, e.g., time series data about CPU utilization
of the VNF during a throughput benchmark. In the case of VNFs
composed of multiple VNFCs, those resulting data should be
represented as vectors, capturing the behavior of each VNFC, if
available from the used monitoring systems. Alternatively, more
compact representation formats can be used, e.g., statistical
information about a series of latency measurements, including
averages and standard deviations. The exact output format to be used
is defined in the complementing VNF-BD (Section 5.1).
A VNF performance profile must address the combined set of classified
items in the 3x3 Matrix Coverage defined in [RFC8172].
5.3. Automated Benchmarking Procedures
VNF benchmarking offers the possibility of defining distinct aspects/
steps that may or may not be automated:
Orchestration: placement (assignment/allocation of resources) and
interconnection (physical/virtual) of network function(s) and
benchmark components (e.g., OpenStack/Kubernetes templates, NFV
description solutions, like OSM, SONATA, ONAP) -> Defines
deployment scenario.
Management/Configuration: benchmark components and VNF are
configured to execute the experiment/test (e.g., populate routing
table, load pcap source files in agent) -> Realizes VNF-BD
settings.
Execution: Tests/experiments are executed according to
configuration and orchestrated components -> Runs the VNF
benchmarking cases.
Output: There might be generic VNF footprint metrics (e.g., CPU,
memory) and specific VNF traffic processing metrics (e.g.,
transactions or throughput). Output processing must be taken into
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account (e.g., if sampling is applied or not) in a generic
(statistics) or specific (clustering) ways -> Generates VNF-PP.
For the purposes of dissecting the execution procedures, consider the
following definitions:
Trial: is a single process or iteration to obtain VNF benchmarking
metrics as a singular measurement.
Test: Defines strict parameters for benchmarking components to
perform one or more trials. Multiple Trials must be performed for
statistical significance of the obtained benchmarking results of a
Test. Each Trial must be executed following a particular
deployment scenario composed by a VNF-BD. Proper measures must be
taken to ensure statistic validity (e.g., independence across
trials of generated load patterns).
Method: Consists of a VNF-BD, including one or more Tests to
benchmark a VNF. A Method can explicitly list ranges of parameter
values for the configuration of benchmarking components. Each
value of such a range is to be realized in a Test. I.e., Methods
can define parameter studies.
The following sequence of events composes basic, general procedures
to execute a Test (as defined above).
1. A VNF-BD must be defined to be later instantiated into and
executed as a deployment scenario. Such a description must
contain all the structural and functional settings defined in
Section 5.1. At the end of this step, the complete method of
benchmarking the target VNF is defined.
2. Via an automated orchestrator or in a manual process, all the
components of the VNF benchmark setup must be allocated and
interconnected. VNF and the execution environment must be
configured to properly address the VNF benchmark stimuli.
3. Manager, Agent(s) and Monitor(s) (if existing), must be started
and configured to execute the benchmark stimuli and retrieve
expected metrics captured during or at the end of each Trial. One
or more trials realize the required measurements to characterize
the performance behavior of a VNF according to the benchmark setup
defined in the VNF-BD.
4. Output results from each obtained benchmarking test must be
collected by the Manager. In an automated or manual process,
intended metrics, as described in the VNF-BD, are extracted and
combined to the final VNF-PP. The combination of used VNF-BD and
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generated VNF-PP make up the resulting VNF benchmark report (VNF-
BR).
5.4. Particular Cases
Configurations and procedures concerning particular cases of VNF
benchmarks address testing methodologies proposed in [RFC8172]. In
addition to the general description previously defined, some details
must be taken into consideration in the following VNF benchmarking
cases.
Noisy Neighbor: An Agent can assume the role of a noisy neighbor,
generating a particular workload in synchrony with a benchmarking
procedure over a VNF. Adjustments of the noisy workload stimulus
type, frequency, virtualization level, among others, must be
detailed in the VNF-BD.
Representative Capacity: An average value of workload must be
specified as an Agent stimulus. Considering a long-term analysis,
the VNF must be configured to properly address a desired average
behavior of performance in comparison with the value of the
workload stimulus.
Flexibility and Elasticity: Having the possibility of a VNF be
composed by multiple components (VNFCs), internal events of the
VNF might trigger changes in VNF behavior, e.g., activating
functionalities associated with elasticity such as load balancing.
In this sense, a detailed characterization of a VNF must be
specified (e.g. the VNFs scaling state) and be contained in the
VNF-PP and thus the VNF benchmarking report.
On Failures: Similar to the case before, VNF benchmarking setups
must also capture the dynamics involved in VNF behavior. In case
of failures, a VNF might restart itself and possibly result in an
offline period (e.g., self healing). A VNF-PP and benchmarking
report must capture such variation of VNF states.
White Box VNF: A benchmarking setup must define deployment
scenarios to be compared with and without monitor components into
the VNF and/or the execution environment, in order to analyze if
the VNF performance is affected. The VNF-PP and benchmarking
report must contain such analysis of performance variability,
together with all the extracted VNF performance metrics.
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6. Open Source Reference Implementations
There are two open source reference implementations that are build to
automate benchmarking of Virtualized Network Functions (VNFs).
6.1. Gym
The software, named Gym, is a framework for automated benchmarking of
Virtualized Network Functions (VNFs). It was coded following the
initial ideas presented in a 2015 scientific paper entitled "VBaaS:
VNF Benchmark-as-a-Service" [Rosa-a]. Later, the evolved design and
prototyping ideas were presented at IETF/IRTF meetings seeking impact
into NFVRG and BMWG.
Gym was built to receive high-level test descriptors and execute them
to extract VNFs profiles, containing measurements of performance
metrics - especially to associate resources allocation (e.g., vCPU)
with packet processing metrics (e.g., throughput) of VNFs. From the
original research ideas [Rosa-a], such output profiles might be used
by orchestrator functions to perform VNF lifecycle tasks (e.g.,
deployment, maintenance, tear-down).
The proposed guiding principles, elaborated in [Rosa-b], to design
and build Gym can be composed in multiple practical ways for
different VNF testing purposes:
o Comparability: Output of tests shall be simple to understand and
process, in a human-read able format, coherent, and easily
reusable (e.g., inputs for analytic applications).
o Repeatability: Test setup shall be comprehensively defined through
a flexible design model that can be interpreted and executed by
the testing platform repeatedly but supporting customization.
o Configurability: Open interfaces and extensible messaging models
shall be available between components for flexible composition of
test descriptors and platform configurations.
o Interoperability: Tests shall be ported to different environments
using lightweight components.
In [Rosa-b] Gym was utilized to benchmark a decomposed IP Multimedia
Subsystem VNF. And in [Rosa-c], a virtual switch (Open vSwitch -
OVS) was the target VNF of Gym for the analysis of VNF benchmarking
automation. Such articles validated Gym as a prominent open source
reference implementation for VNF benchmarking tests. Such articles
set important contributions as discussion of the lessons learned and
the overall NFV performance testing landscape, included automation.
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Gym stands as one open source reference implementation that realizes
the VNF benchmarking methodologies presented in this document. Gym
is being released open source at [Gym]. The code repository includes
also VNF Benchmarking Descriptor (VNF-BD) examples on the vIMS and
OVS targets as described in [Rosa-b] and [Rosa-c].
6.2. tng-bench
Another software that focuses on implementing a framework to
benchmark VNFs is the "5GTANGO VNF/NS Benchmarking Framework" also
called "tng-bench" (previously "son-profile") and was is as part of
the two European Union H2020 projects SONATA NFV and 5GTANGO [tango].
Its initial ideas were presented in [Peu-a] and the system design of
the end-to-end prototype was presented in [Peu-b].
Tng-bench's aims to act as a framework for the end-to-end automation
of VNF benchmarking processes. Its goal is to automate the
benchmarking process in such a way that VNF-PPs can be generated
without further human interaction. This enables the integration of
VNF benchmarking into continuous integration and continuous delivery
(CI/CD) pipelines so that new VNF-PPs are generated on-the-fly for
every new software version of a VNF. Those automatically generated
VNF-PPs can then be bundled with the VNFs and serve as inputs for
orchestration systems, fitting to the original research ideas
presented in [Rosa-a] and [Peu-a].
Following the same high-level VNF testing purposes as Gym, namely:
Comparability, repeatability, configurability, and interoperability,
tng-bench specifically aims to explore description approaches for VNF
benchmarking experiments. In [Peu-b] a prototype specification VNF-
BDs is presented which not only allows to specify generic, abstract
VNF benchmarking experiments, it also allows to describe sets of
parameter configurations to be tested during the benchmarking
process, allowing the system to automatically execute complex
parameter studies on the SUT, e.g., testing a VNF's performance under
different CPU, memory, or software configurations.
Tng-bench was used to perform a set of initial benchmarking
experiments using different VNFs, like a Squid proxy, an Nginx load
balancer, and a Socat TCP relay in [Peu-b]. Those VNFs have not only
been benchmarked in isolation, but also in combined setups in which
up to three VNFs were chained one after each other. These
experiments were used to test tng-bench for scenarios in which
composed VNFs, consisting of multiple VNF components (VNFCs), have to
be benchmarked. The presented results highlight the need to
benchmark composed VNFs in end-to-end scenarios rather than only
benchmark each individual component in isolation, to produce
meaningful VNF-PPs for the complete VNF.
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Tng-bench is actively developed and released as open source tool
under Apache 2.0 license [tng-bench].
7. Security Considerations
Benchmarking tests described in this document are limited to the
performance characterization of VNFs in a lab environment with
isolated network.
The benchmarking network topology will be an independent test setup
and MUST NOT be connected to devices that may forward the test
traffic into a production network, or misroute traffic to the test
management network.
Special capabilities SHOULD NOT exist in the VNF benchmarking
deployment scenario specifically for benchmarking purposes. Any
implications for network security arising from the VNF benchmarking
deployment scenario SHOULD be identical in the lab and in production
networks.
8. IANA Considerations
This document does not require any IANA actions.
9. Acknowledgement
The authors would like to thank the support of Ericsson Research,
Brazil. Parts of this work have received funding from the European
Union's Horizon 2020 research and innovation programme under grant
agreement No. H2020-ICT-2016-2 761493 (5GTANGO: https://5gtango.eu).
10. References
10.1. Normative References
[ETS14a] ETSI, "Architectural Framework - ETSI GS NFV 002 V1.2.1",
Dec 2014, <http://www.etsi.org/deliver/etsi\_gs/
NFV/001\_099/002/01.02.01-\_60/gs\_NFV002v010201p.pdf>.
[ETS14b] ETSI, "Terminology for Main Concepts in NFV - ETSI GS NFV
003 V1.2.1", Dec 2014,
<http://www.etsi.org/deliver/etsi_gs/NFV/001_099-
/003/01.02.01_60/gs_NFV003v010201p.pdf>.
[ETS14c] ETSI, "NFV Pre-deployment Testing - ETSI GS NFV TST001
V1.1.1", April 2016,
<http://docbox.etsi.org/ISG/NFV/Open/DRAFTS/TST001_-_Pre-
deployment_Validation/NFV-TST001v0015.zip>.
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[ETS14d] ETSI, "Network Functions Virtualisation (NFV); Virtual
Network Functions Architecture - ETSI GS NFV SWA001
V1.1.1", December 2014,
<https://docbox.etsi.org/ISG/NFV/Open/Publications_pdf/
Specs-Reports/NFV-SWA%20001v1.1.1%20-%20GS%20-%20Virtual%2
0Network%20Function%20Architecture.pdf>.
[RFC1242] S. Bradner, "Benchmarking Terminology for Network
Interconnection Devices", July 1991,
<https://www.rfc-editor.org/info/rfc1242>.
[RFC8172] A. Morton, "Considerations for Benchmarking Virtual
Network Functions and Their Infrastructure", July 2017,
<https://www.rfc-editor.org/info/rfc8172>.
[RFC8204] M. Tahhan, B. O'Mahony, A. Morton, "Benchmarking Virtual
Switches in the Open Platform for NFV (OPNFV)", September
2017, <https://www.rfc-editor.org/info/rfc8204>.
10.2. Informative References
[Gym] "Gym Home Page", <https://github.com/intrig-unicamp/gym>.
[Peu-a] M. Peuster, H. Karl, "Understand Your Chains: Towards
Performance Profile-based Network Service Management",
Fifth European Workshop on Software Defined Networks
(EWSDN) , 2016,
<http://ieeexplore.ieee.org/document/7956044/>.
[Peu-b] M. Peuster, H. Karl, "Profile Your Chains, Not Functions:
Automated Network Service Profiling in DevOps
Environments", IEEE Conference on Network Function
Virtualization and Software Defined Networks (NFV-SDN) ,
2017, <http://ieeexplore.ieee.org/document/8169826/>.
[Rosa-a] R. V. Rosa, C. E. Rothenberg, R. Szabo, "VBaaS: VNF
Benchmark-as-a-Service", Fourth European Workshop on
Software Defined Networks , Sept 2015,
<http://ieeexplore.ieee.org/document/7313620>.
[Rosa-b] R. Rosa, C. Bertoldo, C. Rothenberg, "Take your VNF to the
Gym: A Testing Framework for Automated NFV Performance
Benchmarking", IEEE Communications Magazine Testing
Series , Sept 2017,
<http://ieeexplore.ieee.org/document/8030496>.
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[Rosa-c] R. V. Rosa, C. E. Rothenberg, "Taking Open vSwitch to the
Gym: An Automated Benchmarking Approach", IV Workshop pre-
IETF/IRTF, CSBC Brazil, July 2017,
<https://intrig.dca.fee.unicamp.br/wp-
content/plugins/papercite/pdf/rosa2017taking.pdf>.
[tango] "5GTANGO: Development and validation platform for global
industry-specific network services and apps",
<https://5gtango.eu>.
[tng-bench]
"5GTANGO VNF/NS Benchmarking Framework",
<https://github.com/sonata-nfv/tng-sdk-benchmark>.
Authors' Addresses
Raphael Vicente Rosa (editor)
University of Campinas
Av. Albert Einstein, 400
Campinas, Sao Paulo 13083-852
Brazil
Email: rvrosa@dca.fee.unicamp.br
URI: https://intrig.dca.fee.unicamp.br/raphaelvrosa/
Christian Esteve Rothenberg
University of Campinas
Av. Albert Einstein, 400
Campinas, Sao Paulo 13083-852
Brazil
Email: chesteve@dca.fee.unicamp.br
URI: http://www.dca.fee.unicamp.br/~chesteve/
Manuel Peuster
Paderborn University
Warburgerstr. 100
Paderborn 33098
Germany
Email: manuel.peuster@upb.de
URI: http://go.upb.de/peuster
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Holger Karl
Paderborn University
Warburgerstr. 100
Paderborn 33098
Germany
Email: holger.karl@upb.de
URI: https://cs.uni-paderborn.de/cn/
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