Methodology for VNF Benchmarking Automation University of Campinas
Av. Albert Einstein, 400 Campinas Sao Paulo 13083-852 Brazil
University of Campinas
Paderborn University
Warburgerstr. 100 Paderborn 33098 Germany
Paderborn University
Warburgerstr. 100 Paderborn 33098 Germany
IETF BMWG Internet-Draft This document describes a common methodology for the automated benchmarking of Virtualized Network Functions (VNFs) executed on general-purpose hardware. Specific cases of automated 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.
Common benchmarking terminology contained in this document is derived from . The reader is assumed to be familiar with the terminology as defined in the European Telecommunications Standards Institute (ETSI) NFV document . Some of these terms, and others commonly used in this document, are defined below. Network Function Virtualization - the principle of separating network functions from the hardware they run on by using virtual hardware abstraction. 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) . Those VNFs are also called composed VNFs. 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 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. Network Service - a collection of interconnected VNFs forming a end-to-end service. The interconnection is often done using chaining of functions.
VNF benchmarking considerations are defined in . Additionally, VNF pre-deployment testing considerations are well explored in .
Following ETSI's model in , we distinguish three methods for VNF evaluation: Where parameters (e.g., CPU, memory, storage) are provided and the corresponding performance metrics (e.g., latency, throughput) are obtained. Note, such evaluations might create multiple reports, for example, with minimal latency or maximum throughput results. Both parameters and performance metrics are provided and a stimulus verifies if the given association is correct or not. Performance metrics are provided and the corresponding parameters obtained. Note, multiple deployments 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 focus on Benchmarking in the rest of the document.
A (automated) benchmarking procedure can be divided into three sub-procedures: Is a single process or iteration to obtain VNF performance metrics from benchmarking measurements. A Test should always run multiple Trials to get statistical confidence about the obtained measurements. Defines unique structural and functional parameters (e.g., configurations, resource assignment) for benchmarked components to perform one or multiple Trials. Each Test must be executed following a particular benchmarking scenario composed by a Method. Proper measures must be taken to ensure statistical validity (e.g., independence across Trials of generated load patterns). Consists of one or more Tests to benchmark a VNF. A Method can explicitly list ranges of parameter values for the configuration of a benchmarking scenario and its components. Each value of such a range is to be realized in a Test. I.e., Methods can define parameter studies. In general, automated VNF benchmarking Tests must capture relevant causes of performance variability. To dissect a VNF benchmarking Test, in the sections that follow different benchmarking phases are categorized defining generic operations that may be automated. When automating a VNF benchmarking methodology, all the influencing aspects on the performance of a VNF must be carefully analyzed and comprehensively reported, in each phase of the overall benchmarking process.
The placement (i.e., assignment and allocation of resources) and the interconnection, physical and/or virtual, of network function(s) and benchmarking components can be realized by orchestration platforms (e.g., OpenStack, Kubernetes, Open Source MANO). In automated manners, the realization of a benchmarking testbed/scenario through those means usually rely on network service templates (e.g., TOSCA, Heat, YANG). Such descriptors have to capture all relevant details of the execution environment to allow the benchmarking framework to correctly instantiate the SUT as well as helper functions required for a Test.
The configuration of benchmarking components and VNFs (e.g., populate routing table, load PCAP source files in source of traffic stimulus) to execute the Test settings can be realized by programming interfaces in an automated way. In the scope of NFV, there might exist management interfaces to control a VNF during a benchmarking Test. Likewise, infrastructure or orchestration components can establish the proper configuration of an execution environment to realize all the capabilities enabling the description of the benchmarking Test. Each configuration registry, its deployment timestamp and target, must all be contained in the VNF benchmarking report.
In the execution of a benchmarking Test, the VNF configuration can be programmed to be changed by itself or by a VNF management platform. It means that during a Trial execution, particular behaviors of a VNF can be automatically triggered, e.g., auto-scaling of its internal components. Those must be captured in the detailed procedures of the VNF execution and its performance report. I.e., the execution of a Trial can determine arrangements of internal states inside a VNF, which can interfere in observed benchmarking metrics. For instance, in a particular benchmarking case where the monitoring measurements of the VNF and/or execution environment are available for extraction, Tests should be run to verify if the monitoring of the VNF and/or execution environment can impact the VNF performance metrics.
The report of a VNF benchmarking Method might contain generic metrics (e.g., CPU and memory consumption) and VNF-specific traffic processing metrics (e.g., transactions or throughput), which can be stored and processed in generic or specific ways (e.g., by statistics or machine learning algorithms). If automated procedures are applied over the generation of a benchmarking report, those must be detailed in the report itself, jointly with their input raw measurements and output processed data. I.e., any algorithm used in the generation of processed metrics must be disclosed in the report.
A generic VNF benchmarking architectural framework, shown in , establishes the disposal of essential components and control interfaces, explained below, that enable the automation of VNF benchmarking methodologies.
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 based on available virtual resources/parameters and configured enhancements targeting specific technologies (e.g., NUMA, SR-IOV, CPU-Pinning). 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. executes active stimulus using probers, i.e., benchmarking tools, to benchmark and collect network and system performance metrics. A single Agent can perform localized benchmarks in execution environments (e.g., stress tests on CPU, memory, disk I/O) or can generate stimulus traffic and the other end be the VNF itself where, for example, one-way latency is evaluated. The interaction among distributed Agents enable the generation and collection of end-to-end metrics (e.g., frame loss rate, latency) measured from stimulus traffic flowing through a VNF. An Agent can be defined by a physical or virtual network function. defines an abstraction layer for a software or hardware tool able to generate stimulus traffic to a VNF or perform stress tests on execution environments. Probers might be specific or generic to an execution environment or a VNF. For an Agent, a Prober must provide programmable interfaces for its life cycle management, e.g., configuration of operational parameters, execution of stilumus, parsing of extracted metrics, and debugging options. Specific Probers might be developed to abstract and to realize the description of particular VNF benchmarking methodologies. when possible is instantiated inside the System Under Test, VNF and/or infrastructure (e.g., as a plug-in process in a virtualized execution environment), to perform the passive monitoring, using Listeners, for the extraction of metrics while Agents` stimuli takes place. Monitors observe particular properties according to the execution environment and VNFs capabilities, i.e., exposed passive monitoring interfaces. Multiple Listeners can be executed at once in synchrony with a Prober' stimulus on a SUT. A Monitor can be defined as a virtualized network function. defines one or more software interfaces for the extraction of 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 passive monitoring captures, parsing of extracted metrics, and debugging options. Varied methods of passive performance monitoring might be implemented as a Listener, depending on the interfaces exposed by the VNF and/or execution environment. performs (i) the discovery of available Agents/Monitors and their respective features (i.e., available Probers/Listeners and execution environment capabilities), (ii) the coordination and synchronization of activities of Agents and Monitors to perform a benchmarking Test, (iii) the collection, processing and aggregation of all VNF benchmarking measurements that correlates the VNF stimuli and the, possible, SUT monitored metrics. A Manager executes the main configuration, operation, and management actions to deliver the VNF benchmarking report. A Manager can be defined as a physical or virtualized network function.
A deployment scenario realizes the actual instantiation of physical and/or virtual components of a Generic VNF Benchmarking Architectural Framework needed to habilitate the execution of an automated VNF benchmarking methodology. The following considerations hold for a deployment scenario: Not all components are mandatory for a Test, possible to be disposed in varied settings. 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 benchmarking Test and present measurement results. Monitor can be defined by multiple instances of software components, each addressing a VNF or execution environment. 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. All benchmarking components defined in a deployment scenario must perform the synchronization of clocks.
Portability is an intrinsic characteristic of VNFs and allows them to be deployed in multiple environments. This enables various benchmarking setups in varied deployment scenarios. A VNF benchmarking methodology must be described in a clear and objective manner following four basic principles: Comparability: Output of Tests shall be simple to understand and process, in a human-readable format, coherent, and easily reusable (e.g., inputs for analytic applications). Repeatability: A 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. Configurability: Open interfaces and extensible messaging models shall be available between benchmarking components for flexible composition of Test descriptors and platform configurations. Interoperability: Tests shall be ported to different environments using lightweight components.
As shown in , the outcome of an automated VNF benchmarking methodology, must be captured in a VNF Benchmarking Report (VNF-BR), consisting of two parts: contains all required definitions and requirements to deploy, configure, execute, and reproduce VNF benchmarking tests. VNF-BDs are defined by the developer of a benchmarking methodology and serve as input to the benchmarking process, before being included in the generated VNF-BR. contains all measured metrics resulting from the execution of a benchmarking. 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.
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). A VNF-BD may be specific to a VNF or applicable to several VNF types. It 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.
The specification of the number of executions for Trials, Tests and Method. The execution of a VNF-BD corresponds to the execution of the specified Method.
The details referring to the name, description, and information associated with the interfaces needed for the orchestration, if necessary, of the specified VNF-BD scenario. I.e., it refers to a specific interface that receives the VNF-BD scenario information and converts it to the template needed for an orchestration platform. In this case, the means to the Manager component interface such orchestration platform must be provided, as well as its outcome orchestration status information (e.g., management interfaces of deployed components).
This section contains all information needed to describe the deployment of all involved functional components mandatory for the execution of the benchmarking Tests addressed by the VNF-BD.
Information about each component in a benchmarking setup (see ). It contains the identification, name, image, role (i.e., agent, monitor, sut), connection-points and resource requirements (i.e., allocation of cpu, memory, disk). The lifecycle specification of a node lists all the workflows that must be realized on it during a Test. For instance, main workflows include: create, start, stop, delete. Particular workflows can be specified containing the required parameters and implementation. Those details must reflect the actions taken on or by a node that might affect the VNF performance profile.
Links contain information about the data plane links interconnecting the components of a benchmarking setup. Links refer to two or more connection-points of a node. A link might refer to be part of a network. Depending on the link type, the network might be implemented as a layer 2 mesh, or as directional-oriented traffic forwarding flow entries. Links also detain resource requirements, specifying the minimum bandwidth, latency, and frame loss rate for the execution of benchmarking Tests.
Involves the definition of execution environment policies to run the Tests. Policies might specify the (anti-)affinity placement rules for each component in the topology, min/max allocation of resources, and specific enabling technologies (e.g., DPDK, SR-IOV, PCIE) needed for each component.
This information is utilized by the Manager component to execute the benchmarking Tests. It consists of agent(s) and monitor(s) settings, detailing their prober(s)/listener(s) specification and running parameters. Defines a list containing the Agent(s) needed for the VNF-BD tests. The information of each Agent contains its host environment, making reference to a node specified in the VNF-BD scenario (). In addition, each Agent also is defined with the the configured toolset of the Prober(s) and their running parameters fulfilled (e.g., stimulus workload, traffic format/trace, configurations to enable hardware capabilities, if existent). In each Prober, it is also detailed the output metrics to be extracted from it when running the benchmarking Tests. Defines a list containing the Monitor(s) needed for the VNF-BD tests. The information of each Monitor contains its host environment, making reference to a node specified in the VNF-BD scenario () and detailing the placement settings of it (e.g., internal or external with the target VNF and/or execution environment). In addition, each Monitor also is defined with the the configured toolset of the Listener(s) and their running parameters fulfilled (e.g., tap interfaces, period of monitoring, interval among the measurements). In each Listener, it is also detailed the output metrics to be extracted from it when running the benchmarking Tests.
Execution environment information has to be included in every VNF-PP and is required to describe the environment on which a benchmark Test 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 (), for each component in the deployment scenario of the VNF benchmarking setup, the following topics must be detailed: 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. 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.
The methodology for VNF Benchmarking Automation encompasses the process defined in , i.e., the procedures that translate a VNF-BD into a VNF-PP composing a VNF-BR by the means of the components specified in . This section details the sequence of events that realize such process.
Before the execution of benchmarking Tests, some procedures must be performed: A VNF-BD must be defined to be later instantiated into a deployment scenario and have executed its Tests. Such a description must contain all the structural and functional settings defined in . At the end of this step, the complete Method of benchmarking the target VNF is defined. The VNF target image must be prepared to be benchmarked, having all its capabilities fully described. In addition all the probers and listeners defined in the VNF-BD must be implemented to realize the benchmark Tests. At the end of this step, the complete set of components of the benchmarking VNF-BD deployment scenario is defined. The environment needed for a VNF-BD must be defined to realize its deployment scenario, in an automated or manual method. This step might count on the instantiation of orchestration platforms and the composition of specific topology descriptors needed by those platforms to realize the VNF-BD deployment scenario. At the end of this step, the whole environment needed to instantiate the components of a VNF-BD deployment scenario is defined.
Satisfied all the pre-execution procedures, the automated execution of the Tests specified by the VNF-BD follow: Upon the parsing of a VNF-BD, the Manager must detect the VNF-BD variable input field (e.g., list of resources values) and compose the all the permutations of parameters. For each permutation, the Manager must elaborate a VNF-BD instance. Each VNF-BD instance defines a Test, and it will have its deployment scenario instantiated accordingly. I.e., the Manager must interface an orchestration platform to realize the automated instantiation of each deployment scenario defined by a VNF-BD instance (i.e., a Test). The Manager must iterate through all the VNF-BD instances to finish the whole set of Tests defined by all the permutations of the VNF-BD input fields. Given a VNF-BD instance, the Manager, using the VNF-BD environment settings, must interface an orchestrator platform requesting the deployment of a scenario to realize a Test. To perform such step, The Manager might interface a management function responsible to properly parse the deployment scenario specifications into the orchestration platform interface format. An orchestration platform must deploy the scenario requested by the Manager, assuring the requirements and policies specified on it. In addition, the orchestration platform must acknowledge the deployed scenario to the Manager specifying the management interfaces of the VNF and the other components in the running instances for the benchmarking Test. Agent(s) and Monitor(s) (if existing) and the target VNF must be configured by the Manager according to the components settings defined in the VNF-BD instance. After this step, the whole VNF-BD Test will be ready to be executed. Manager must interface Agent(s) and Monitor(s) (if existing) via management interfaces to require the execution of the benchmarking probers (and listeners, if existing), and retrieve expected metrics captured during or at the end of each Trial. I.e., for a single Test, according to the VNF-BD execution settings, the Manager must guarantee that one or more Trials realize the required measurements to characterize the performance behavior of a VNF. Output measurements from each obtained benchmarking Test, and its possible Trials, must be collected by the Manager, until all the Tests are finished. In the execution settings of the parsed VNF-BD, the Manager must check the Method repetition, and perform the whole set of VNF-BD Tests (i.e., since step 1), until all methods specified are finished. Collected all measurements from the VNF-BD (Trials, Tests and Methods) execution, the intended metrics, as described in the VNF-BD, must be parsed, extracted and combined to create the corresponding VNF-PP. The combination of used VNF-BD and generated VNF-PP compose the resulting VNF benchmark report (VNF-BR).
After the process of a VNF-BD execution, some automated procedures, not necessarily mandatory, can be performed to improve the quality and utility of a VNF-BR: Archive the raw output contained in the VNF-PP, perform statistical analysis on it, or train machine learning models with the collected data. Evaluate the analysis output to the detection of any possible cause-effect factors and/or intrinsic correlations in the VNF-BR (e.g., outliers). Review the input VNF-BD and modify it to realize the proper extraction of the target VNF metrics based on the performed research. Iterate in the previous steps until composing a stable and representative VNF-BR.
As described in , VNF benchmarking might require to change and adapt existing benchmarking methodologies. More specifically, the following cases need to be considered.
Currently, technical motivating factors in favor of the automation of VNF benchmarking methodologies comprise: (i) the facility to run high-fidelity and commodity traffic generators by software; (ii) the existent means to construct synthetic traffic workloads purely by software (e.g., handcrafted pcap files); (iii) the increasing availability of datasets containing actual sources of production traffic able to be reproduced in benchmarking tests; (iv) the existence of a myriad of automating tools and open interfaces to programmatically manage VNFs; (v) the varied set of orchestration platforms enabling the allocation of resources and instantition of VNFs through automated machineries based on well-defined templates; (vi) the ability to utilize a large tool set of software components to compose pipelines that mathematically analyze benchmarking metrics in automated ways. In simple terms, network softwarization enables automation. There are two open source reference implementations that are build to automate benchmarking of Virtualized Network Functions (VNFs).
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” . 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 , such output profiles might be used by orchestrator functions to perform VNF lifecycle tasks (e.g., deployment, maintenance, tear-down). In Gym was utilized to benchmark a decomposed IP Multimedia Subsystem VNF. And in , 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. Gym stands as one open source reference implementation that realizes the VNF benchmarking methodologies presented in this document. Gym is released as open source tool under Apache 2.0 license .
This document does not require any IANA actions.
Benchmarking Virtual Switches in the Open Platform for NFV (OPNFV) M. Tahhan, B. O'Mahony, A. Morton Considerations for Benchmarking Virtual Network Functions and Their Infrastructure A. Morton Benchmarking Terminology for Network Interconnection Devices S. Bradner Architectural Framework - ETSI GS NFV 002 V1.2.1 ETSI Terminology for Main Concepts in NFV - ETSI GS NFV 003 V1.2.1 ETSI NFV Pre-deployment Testing - ETSI GS NFV TST001 V1.1.1 ETSI Network Functions Virtualisation (NFV); Virtual Network Functions Architecture - ETSI GS NFV SWA001 V1.1.1 ETSI Report on CI/CD and Devops - ETSI GS NFV TST006 V0.0.9 ETSI VBaaS: VNF Benchmark-as-a-Service R. V. Rosa, C. E. Rothenberg, R. Szabo Take your VNF to the Gym: A Testing Framework for Automated NFV Performance Benchmarking R. Rosa, C. Bertoldo, C. Rothenberg Taking Open vSwitch to the Gym: An Automated Benchmarking Approach R. V. Rosa, C. E. Rothenberg Gym Framework Source Code Understand Your Chains: Towards Performance Profile-based Network Service Management M. Peuster, H. Karl Profile Your Chains, Not Functions: Automated Network Service Profiling in DevOps Environments M. Peuster, H. Karl Understand your chains and keep your deadlines: Introducing time-constrained profiling for NFV M. Peuster, H. Karl 5GTANGO: Development and validation platform for global industry-specific network services and apps 5GTANGO VNF/NS Benchmarking Framework