Network Working Group P. Fan Internet-Draft Z. Cao Intended status: Informational China Mobile Expires: August 18, 2014 February 14, 2014 Deep Performance Visualization: Use Cases, Requirements and Framework draft-fan-deep-performance-visualization-00 Abstract Providing deep performance information by the networks is expected in many use cases. This document intends to discuss a unified presentation of performance, by investigating use cases that benefit from performance information, describing relevant requirements, and proposing a framework of how the components work together to enable deep performance visualization. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet- Drafts is at http://datatracker.ietf.org/drafts/current/. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." This Internet-Draft will expire on August 18, 2014. Copyright Notice Copyright (c) 2014 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 (http://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Simplified BSD License text as described in Section 4.e of Fan & Cao Expires August 18, 2014 [Page 1] Internet-Draft Deep Performance Visualization February 2014 the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License. Table of Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2 2. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 2 3. Requirements . . . . . . . . . . . . . . . . . . . . . . . . 3 4. Framework . . . . . . . . . . . . . . . . . . . . . . . . . . 4 5. Potential Work . . . . . . . . . . . . . . . . . . . . . . . 6 6. Security Considerations . . . . . . . . . . . . . . . . . . . 6 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 7 8. References . . . . . . . . . . . . . . . . . . . . . . . . . 7 8.1. Normative References . . . . . . . . . . . . . . . . . . 7 8.2. Informative References . . . . . . . . . . . . . . . . . 7 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 7 1. Introduction There are many applications today expecting a certain level of knowledge about the network, e.g. topology. Knowing network related information will be helpful to better make decisions and change behaviors accordingly. Network performance is a valuable kind of the information as it dynamically reflects how the network is performing and how traffic will be likely to experience. Currently, network performance information is generated and maintained by different elements or systems for purposes like network monitoring, and there is rather limited way for applications to get a deep and instant view of the status of the whole or part of the network. This document intends to discuss a service provided by the network to give a unified presentation of network performance, by investigating use cases that benefit from performance knowledge, describing requirements for performance visualization ability, and proposing a framework of how the components work together to enable deep performance visualization. 2. Use Cases This section gives a non-exhaustive list of uses cases that benefit from obtaining a picture of deep network performance. Network traffic optimization: Traditional path selection for data traffic in a network is based on static and per-link metrics (e.g. link bandwidth). This approach may not be optimal without a picture of performance of the entire network. For example, in a delay sensitive financial network, end-to-end and per-hop latency Fan & Cao Expires August 18, 2014 [Page 2] Internet-Draft Deep Performance Visualization February 2014 performance is critical to traffic optimization. A detailed per-flow performance will be even helpful as network elements can then handle the traffic in a smarter way. Load balancing in data centers: Data centers utilize load balancers to distribute workload across multiple servers, network links or other resources, to achieve optimal resource utilization, maximize throughput, minimize response time, and avoid overload. A load balancer uses a health monitoring function to detect whether the servers can provide services, and distributes service traffic to different resources according to a scheduling algorithm or strategy. For workload that is better served by network support, load balancing will be improved if real-time network performance is taken into account. For example, it will be less likely to distribute a file downloading request to a server to which the network has a limited available bandwidth. Application aware network provisioning: Enabling information exchange between applications and the network will provide ways for them to better accommodate each other. An application may have certain expectations for the network quality, and having an idea of how the network is performing will help the application adjust its behavior accordingly; a network may have its own policies on applications in addition to the information provided by an application, and network elements are then able to adjust forwarding behavior to differentiate application performance. 3. Requirements This section describes requirements on an architecture providing deep network performance visualization service. o An API interface with other systems (regarded as applications) must be provided. Applications utilize the interface to query for desired performance information and get the response. o An ability of real-time network performance query must be provided for the applications that request current performance data. The data can be derived from * Results obtained from instant performance measurements/tests. Fan & Cao Expires August 18, 2014 [Page 3] Internet-Draft Deep Performance Visualization February 2014 * Status information gathered from network elements; the information gathering is often performed on a periodic or routine basis. o An ability of querying historical performance data within a certain period of time should be provided for the applications that request past data. If this ability is provided, then the length of the period must be configurable. o In the absence of real-time performance data for a certain metric, e.g. the current IP packet loss rate on the path A-B-C of TCP flows with a TOS field being 0, an ability of responding with other close performance data for informational reference should be provided. With this ability current performance can be anticipated to some extent. Informational data provided can be * Historic performance data of that metric. * Current performance data of related metrics, e.g. current IP packet loss rate on the path A-B-C of IP flows with a TOS field being 0. o An ability of reporting performance data associated with network topology information should be provided. Traditional metrics focus more on end-to-end performance, while detailed network structure and performance between endpoints are left out. Performance gathered in this way may not be accurate enough, as traffic may go through different paths. This is especially a problem in certain situations, e.g. link aggregation, resource pooling, etc. o An ability of reporting flow based performance should be provided. A traffic flow can be identified by a set of match fields, e.g. the 5-tuples. 4. Framework The following picture depicts a framework providing deep performance visualization service. Fan & Cao Expires August 18, 2014 [Page 4] Internet-Draft Deep Performance Visualization February 2014 +------+ +------+ +------+ +------+ +------+ +------+ +------+ | ALTO | | PCE | | Load | |Traff.| | Web | | Net | |Other | | | | | | ball.| |engi. | | app. | |admin | |apps..| +------+ +------+ +------+ +------+ +------+ +------+ +------+ /\ /\ /||\ API /||\ ,--------------------------------------. | Performance Synthetic Analyzer | \______________________________________/ : : : : : : : : : : *---------:--:-------------:------:---------:---------* / +------,-.+ : : : +------,-.+ / / |Ter- ( R ) : : : |Web ( R ) / / |minal `-'| : : : |server`-'| / / +---------+ : : : +---------+ /---* *-----------------:-------------:------:--------------* / / : +--------:+ : / / +--------:+ |Fwd. ,-. ,-.-------+ / / |Test ,-.| |device( R ) ( R ) NMS | / / |agent( R ) +-------`-' `-' | / / +------`-'+ +---------+ /R:Performance *---------------------------------------------------* Reporter Components contained in the framework include: o Performance reporter. A performance reporter obtains raw performance information at a certain location of the network. The carrier of a reporter can be a forwarding device, a test agent that runs measurement, a web server, a mobile device, the NMS (Network Management System), etc. Performance metrics covered by different reporters may be varied, e.g. a reporter on a forwarding device gets packet drop counts and another reporter on a web server gets CPU utilization ratio. Performance information obtained by a reporter is not modified, but directly sent to the performance synthetic analyzer. o Performance synthetic analyzer. A performance synthetic analyzer receives performance information sent by the performance reporters, and processes the information into performance records to associate data, reduce duplication, and unify format. Records are stored in the database of the analyzer. The analyzer receives query request from applications, and comprehend requested performance metrics. The analyzer comes up with requested performance value by seeking among the records and probable computations using relevant records, and responds the application with the exact values, informational values as described in the requirements, or a message indicating value providing failure. Fan & Cao Expires August 18, 2014 [Page 5] Internet-Draft Deep Performance Visualization February 2014 o Applications. Applications utilize this framework to get information about network performance. An application can be a system/protocol/function that intends to rely on some knowledge of the network to be better performed. To an application the analyzer acts as an infrastructure representing a global view of performance, while the details of the network are hidden under the infrastructure. As depicted in the picture, the framework incorporates two interfaces: o The analyzer-to-reporter interface is used to report raw performance information from reporter to analyzer. o The analyzer-to-application interface is used to request for performance information from application to analyzer, and respond with corresponding values from analyzer to application. 5. Potential Work This section gives a list of work items that needs to sort through. o The architecture of the framework is to be defined, including specification of components and interfaces. o Method of report between reporter and analyzer is to be specified, including an information model and a reporting protocol. Existing information models and protocols (e.g. IPFIX, Syslog, SNMP, etc.) can be considered as candidates, and possible extensions are to be developed in relevant working groups. o API interface provided by the analyzer toward applications is to be defined. How applications call the API to get the information concerned has to be specified. o Performance metrics that better evaluate network state for different purposes will have to be extended in relevant working groups. 6. Security Considerations Certain authentication, authorization, or encryption mechanism is expected to be developed to deal with potential problems of attack, privacy or security. Security consideration is to be further discussed. Fan & Cao Expires August 18, 2014 [Page 6] Internet-Draft Deep Performance Visualization February 2014 7. IANA Considerations This memo includes no request to IANA. 8. References 8.1. Normative References [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", RFC 2119, March 1997. 8.2. Informative References [I-D.ietf-alto-protocol] Alimi, R., Penno, R., and Y. Yang, "ALTO Protocol", draft- ietf-alto-protocol-25 (Work in Progress), January 2014. [RFC2578] McCloghrie, K., Perkins, D., and J. Schoenwaelder, "Structure of Management Information Version 2 (SMIv2)", RFC 2578, April 1999. [RFC4655] Farrel, A., Vasseur, J., and J. Ash, "A Path Computation Element (PCE)-Based Architecture", RFC 4655, August 2006. [RFC5424] Gerhards, R., "The Syslog Protocol", RFC 5424, March 2009. [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of the IP Flow Information Export (IPFIX) Protocol for the Exchange of Flow Information", RFC 7011, September 2013. Authors' Addresses Peng Fan China Mobile 32 Xuanwumen West Street, Xicheng District Beijing 100053 P.R. China Email: fanpeng@chinamobile.com Zhen Cao China Mobile 32 Xuanwumen West Street, Xicheng District Beijing 100053 P.R. China Email: caozhen@chinamobile.com Fan & Cao Expires August 18, 2014 [Page 7]