Network Management Research Group J. Nobre
Internet-Draft L. Granville
Intended status: Informational Federal University of Rio Grande do Sul
Expires: October 8, 2016 A. Clemm
A. Prieto
Cisco Systems
April 6, 2016
Autonomic Networking Use Case for Distributed Detection of SLA
Violations
draft-irtf-nmrg-autonomic-sla-violation-detection-03
Abstract
This document describes a use case for autonomic networking in
distributed detection of Service Level Agreement (SLA) violations.
It is one of a series of use cases intended to illustrate
requirements for autonomic networking.
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Definitions and Acronyms . . . . . . . . . . . . . . . . . . 4
3. Current Approaches . . . . . . . . . . . . . . . . . . . . . 4
4. Problem Statement . . . . . . . . . . . . . . . . . . . . . . 5
5. Benefits of an Autonomic Solution . . . . . . . . . . . . . . 5
6. Intended User and Administrator Experience . . . . . . . . . 6
7. Analysis of Parameters and Information Involved . . . . . . . 6
7.1. Device Based Self-Knowledge and Decisions . . . . . . . . 6
7.2. Interaction with other devices . . . . . . . . . . . . . 6
8. Comparison with current solutions . . . . . . . . . . . . . . 7
9. Related IETF Work . . . . . . . . . . . . . . . . . . . . . . 7
10. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 8
11. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
12. Security Considerations . . . . . . . . . . . . . . . . . . . 8
13. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
13.1. Normative References . . . . . . . . . . . . . . . . . . 8
13.2. Informative References . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
The Internet has been growing dramatically in terms of size and
capacity, and accessibility in the last years. Communication
requirements of distributed services and applications running on top
of the Internet have become increasingly demanding. Some examples
are real-time interactive video or financial trading. Providing such
services involves stringent requirements in terms of acceptable
latency, loss, or jitter. Those requirements lead to the
articulation of Service Level Objectives (SLOs) which are to be met.
Those SLOs become part of Service Level Agreements (SLAs) that
articulate a contract between the provider and the consumer of a
service. To fulfill a service, it needs to be ensured that the SLOs
are met. Examples of service fulfillment clauses can be found on
[RFC7297]). Violations of SLOs can be associated with significant
financial loss, which can by divided in two types. First, there is
the loss incurred by the service users (e.g., the trader whose orders
are not executed in a timely manner) and the loss incurred by the
service provider in terms of penalties for not meeting the service
and loss of revenues due to reduced customer satisfaction. Thus, the
service level requirements of critical network services have become a
key concern for network administrators. To ensure that SLAs are not
being violated, service levels need to be constantly monitored at the
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network infrastructure layer. To that end, network measurements must
take place.
Network measurement mechanisms are performed through either active or
passive measurement techniques. In passive measurements, production
traffic is observed. Network conditions are checked in a non
intrusive way because no monitoring traffic is created by the
measurement process itself. In the context of IP Flow Information
EXport (IPFIX) WG, several documents were produced to define passive
measurement mechanisms (e.g., flow records specification [RFC3954]).
Active measurement, on the other hand, is intrusive because it
injects synthetic traffic into the network to measure the network
performance. The IP Performance Metrics (IPPM) WG produced documents
that describe active measurement mechanisms, such as: One-Way Active
Measurement Protocol (OWAMP) [RFC4656], Two-Way Active Measurement
Protocol (TWAMP) [RFC5357], and Cisco Service Level Assurance
Protocol (SLA) [RFC6812]. Besides that, there are some mechanisms
that do not fit into either active or passive categories, such as
Performance and Diagnostic Metrics Destination Option (PDM)
techniques [draft-ietf-ippm-6man-pdm-option].
Active measurement mechanisms offer a high level of control of what
and how to measure. It also does not require inspecting production
traffic. Because of this, it usually offers better accuracy and
privacy than passive measurement mechanisms. Traffic encryption and
regulations that limit the amount of payload inspection that can
occur are non-issues. Furthermore, active measurement mechanisms are
able to detect end-to-end network performance problems in a fine-
grained way (e.g., simulating the traffic that must be handled
considering specific Service Level Objectives - SLOs). As a result,
active measurements are often preferred over passive measurement for
SLA monitoring. Measurement probes must be hosted in network devices
and measurement sessions must be activated to compute the current
network metrics (e.g., considering those described in [RFC4148]).
This activation should be dynamic in order to follow changes in
network conditions, such as those related with routes being added or
new customer demands.
The activation of active measurement sessions (hosted in senders and
responders considering the architecture described by Cisco [RFC6812])
is expensive in terms of the resource consumption, e.g., CPU cycle
and memory footprint, and monitoring functions compete for resources
with other functions, including routing and switching. Besides that,
the activated sessions also increase the network load because of the
injected traffic. The resources required and traffic generated by
the active measurement sessions are a function of the number of
measured network destinations, i.e., with more destinations the
larger will be the resources and the traffic needed to deploy the
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sessions. Thus, to have a better monitoring coverage it is necessary
to deploy more sessions what consequently turns increases consumed
resources. Otherwise, enabling the observation of just a small
subset of all network flows can lead to an insufficient coverage.
Hence, the decision how to place measurement probes becomes an
important management activity, so that with a limited amount of
measurement overhead the maximum benefits in terms of service level
monitoring are obtained.
2. Definitions and Acronyms
Active Measurements: Techniques to measure service levels that
involves generating and observing synthetic test traffic
Passive Measurements: Techniques used to measure levels based on
observation of production traffic
SLA: Service Level Parameter
SLO: Service Level Objective
P2P: Peer-to-Peer
3. Current Approaches
The current best practice in feasible deployments of active
measurement solutions to distribute the available measurement
sessions along the network consists in relying entirely on the human
administrator expertise to infer which would be the best location to
activate such sessions. This is done through several steps. First,
it is necessary to collect traffic information in order to grasp the
traffic matrix. Then, the administrator uses this information to
infer which are the best destinations for measurement sessions.
After that, the administrator activates sessions on the chosen subset
of destinations considering the available resources. This practice,
however, does not scale well because it is still labor intensive and
error-prone for the administrator to compute which sessions should be
activated given the set of critical flows that needs to be measured.
Even worse, this practice completely fails in networks whose critical
flows are too short in time and dynamic in terms of traversing
network path, like in modern cloud environments. That is so because
fast reactions are necessary to reconfigure the sessions and
administrators are not just enough in computing and activating the
new set of required sessions every time the network traffic pattern
changes. Finally, the current active measurements practice usually
covers only a fraction of the network flows that should be observed,
which invariably leads to the damaging consequence of undetected SLA
violations.
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4. Problem Statement
The problem to solve involves automating the placement of active
measurement probes in the most effective manner possible.
Specifically, assuming a bounded resource budget that is available
for measurements, the problem becomes how to place those measurement
probes such that the likelihood of detecting service level violations
is maximized, and subsequently performing the required
configurations. The method should be embeddable as management
software inside network devices that controls the deployment of
active measurement mechanisms. The method shall furthermore be
dynamic and be able to adapt to changing network conditions.
5. Benefits of an Autonomic Solution
The use case considered here is the distributed autonomic detection
of SLA violations. The use of Autonomic Networking (AN) properties
can help such detection through an efficient activation of
measurement sessions [P2PBNM-Nobre-2012]. The problem to be solved
by AN in the present use case is how to steer the process of
measurement session activation by a complete solution that sets all
necessary parameters for this activation to operate efficiently,
reliably and securely, with no required human intervention, while
allowing for their input.
We advocate for embedding Peer-to-Peer (P2P) technology in network
devices in order to improve the measurement session activation
decisions using autonomic control loops. The provisioning of the P2P
management overlay should be transparent for the network
administrator. It would be possible to control the measurement
session activation using local data and logic and to share
measurement results among different network devices.
An autonomic solution for the distributed detection of SLA violations
can provide several benefits. First, efficiency: this solution could
optimize the resource consumption and avoid resource starvation on
the network devices. In practice, the solution should maximize the
benefits of SLA monitoring (i.e., maximize the likelihood of SLA
violations being detected) by operating within a given resource
budget. This optimization comes from different sources: taking into
account past measurement results, taking into account other
observations (such as, observations of link utilizations and passive
measurements, where available) sharing of measurement results between
network devices, better efficiency in the probe activation decisions,
etc. Second, effectiveness: the number of detected SLA violations
could be increased. This increase is related with a better coverage
of the network. Third, the solution could decrease the time
necessary to detect SLA violations. Adaptivity features of an
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autonomic loop could capture faster the network dynamics than an
human administrator. Finally, the solution could help to reduce the
workload of human administrator, or, at least, to avoid their need to
perform operational tasks.
6. Intended User and Administrator Experience
The autonomic solution should not require the human intervention in
the distributed detection of SLA violations. Besides that, it could
enable the control of SLA monitoring by less experienced human
administrators. However, some information may be provided from the
human administrator. For example, the human administrator may
provide the SLOs regarding the SLA being monitored. The
configuration and bootstrapping of network devices using the
autonomic solution should be minimal for the human administrator.
Probably it would be necessary just to inform the address of a device
which is already using the solution and the devices themselves could
exchange configuration data.
7. Analysis of Parameters and Information Involved
The active measurement model assumes that a typical infrastructure
will have multiple network segments and Autonomous Systems (ASs), and
a reasonably large number of several of routers and hosts. It also
considers that multiple SLOs can be in place in a given time. Since
interoperability in a heterogenous network is a goal, features found
on different active measurement mechanisms (e.g. OWAMP, TWAMP, and
IPSLA) and programability interfaces (e.g., Cisco's EEM and onePK)
could be used for the implementation. The autonomic solution should
include and/or reference specific algorithms, protocols, metrics and
technologies for the implementation of distributed detection of SLA
violations as a whole.
7.1. Device Based Self-Knowledge and Decisions
Each device has self-knowledge about the local SLA monitoring. This
could be in the form of historical measurement data and SLOs.
Besides that, the devices would have algorithms that could decide
which probes should be activated in a given time. The choice of
which algorithm is better for a specific situation would be also
autonomic.
7.2. Interaction with other devices
Network devices should share information about service level
measurement results. This information can speed up the detection of
SLA violations and increase the number of detected SLA violations.
In any case, it is necessary to assure that the results from remote
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devices have local relevancy. The definition of network devices that
exchange measurement data, i.e., management peers, creates a new
topology. Different approaches could be used to define this topology
(e.g., correlated peers [P2PBNM-Nobre-2012]). To bootstrap peer
selection, each device should use its known endpoints neighbors
(e.g., FIB and RIB tables) as the initial seed to get possible peers.
8. Comparison with current solutions
There is no standartized solution for distributed autonomic detection
of SLA violations. Current solutions are restricted to ad hoc
scripts running on a per node fashion to automate some
administrator's actions. There some proposals for passive probe
activation (e.g., DECON and CSAMP), but without the focus on
autonomic features. It is also mentioning a proposal from Barford et
al. to detect and localize links which cause anomalies along a
network path.
9. Related IETF Work
The following paragraphs discuss related IETF work and are provided
for reference. This section is not exhaustive, rather it provides an
overview of the various initiatives and how they relate to autonomic
distributed detection of SLA violations. 1. [LMAP]: The Large-Scale
Measurement of Broadband Performance Working Group aims at the
standards for performance management. Since their mechanisms also
consist in deploying measurement probes the autonomic solution could
be relevant for LMAP specially considering SLA violation screening.
Besides that, a solution to decrease the workload of human
administrators in service providers is probably highly desirable. 2.
[IPFIX]: IP Flow Information EXport (IPFIX) aims at the process of
standardization of IP flows (i.e., netflows). IPFIX uses measurement
probes (i.e., metering exporters) to gather flow data. In this
context, the autonomic solution for the activation of active
measurement probes could be possibly extended to address also passive
measurement probes. Besides that, flow information could be used in
the decision making of probe activation. 3. [ALTO]: The Application
Layer Traffic Optimization Working Group aims to provide topological
information at a higher abstraction layer, which can be based upon
network policy, and with application-relevant service functions
located in it. Their work could be leveraged for the definition of
the topology regarding the network devices which exchange measurement
data.
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10. Acknowledgements
We wish to acknowledge the helpful contributions, comments, and
suggestions that were received from Mohamed Boucadair, Bruno Klauser,
Eric Voit, and Hanlin Fang.
11. IANA Considerations
This memo includes no request to IANA.
12. Security Considerations
The bootstrapping of a new device follows the approach proposed on
anima wg [draft-anima-boot], thus in order to exchange data a device
should register first. This registration could be performed by a
"Registrar" device or a cloud service provided by the organization to
facilitate autonomic mechanisms. The new device sends its own
credentials to the Registrar, and after successful authentication,
receives domain information, to enable subsequent enrolment to the
domain. The Registrar sends all required information: a device name,
domain name, plus some parameters for the operation. Measurement
data should be exchanged signed and encripted among devices since
these data could carry sensible information about network
infrastructures. Some attacks should be considering when analyzing
the security of the autonomic solution. Denial of service (DoS)
attacks could be performed if the solution be tempered to active more
local probe than the available resources allow. Besides that,
results could be forged by a device (attacker) in order to this
device be considered peer of a specific device (target). This could
be done to gain information about a network.
13. References
13.1. Normative References
[draft-anima-boot]
Pritikin, M., Richardson, M., Behringer, M., and S.
Bjarnason, "draft-ietf-anima-bootstrapping-keyinfra",
draft-ietf-anima-bootstrapping-keyinfra-02 (work in
progress), March 2016.
[draft-ietf-ippm-6man-pdm-option]
Elkins, N., Hamilton, R., and M. Ackermann, "draft-ietf-
ippm-6man-pdm-option", draft-ietf-ippm-6man-pdm-option-01
(work in progress), October 2015.
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[P2PBNM-Nobre-2012]
Nobre, J., Granville, L., Clemm, A., and A. Prieto,
"Decentralized Detection of SLA Violations Using P2P
Technology, 8th International Conference Network and
Service Management (CNSM)", 2012,
<http://ieeexplore.ieee.org/xpls/
abs_all.jsp?arnumber=6379997>.
[RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M.
Zekauskas, "A One-way Active Measurement Protocol
(OWAMP)", RFC 4656, DOI 10.17487/RFC4656, September 2006,
<http://www.rfc-editor.org/info/rfc4656>.
[RFC5357] Hedayat, K., Krzanowski, R., Morton, A., Yum, K., and J.
Babiarz, "A Two-Way Active Measurement Protocol (TWAMP)",
RFC 5357, DOI 10.17487/RFC5357, October 2008,
<http://www.rfc-editor.org/info/rfc5357>.
[RFC6812] Chiba, M., Clemm, A., Medley, S., Salowey, J., Thombare,
S., and E. Yedavalli, "Cisco Service-Level Assurance
Protocol", RFC 6812, DOI 10.17487/RFC6812, January 2013,
<http://www.rfc-editor.org/info/rfc6812>.
[RFC7297] Boucadair, M., Jacquenet, C., and N. Wang, "IP
Connectivity Provisioning Profile (CPP)", RFC 7297,
DOI 10.17487/RFC7297, July 2014,
<http://www.rfc-editor.org/info/rfc7297>.
13.2. Informative References
[RFC3954] Claise, B., Ed., "Cisco Systems NetFlow Services Export
Version 9", RFC 3954, DOI 10.17487/RFC3954, October 2004,
<http://www.rfc-editor.org/info/rfc3954>.
[RFC4148] Stephan, E., "IP Performance Metrics (IPPM) Metrics
Registry", BCP 108, RFC 4148, DOI 10.17487/RFC4148, August
2005, <http://www.rfc-editor.org/info/rfc4148>.
Authors' Addresses
Jeferson Campos Nobre
Federal University of Rio Grande do Sul
Porto Alegre
Brazil
Email: jcnobre@inf.ufrgs.br
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Lisandro Zambenedetti Granvile
Federal University of Rio Grande do Sul
Porto Alegre
Brazil
Email: granville@inf.ufrgs.br
Alexander Clemm
Cisco Systems
San Jose
USA
Email: alex@cisco.com
Alberto Gonzalez Prieto
Cisco Systems
San Jose
USA
Email: albertgo@cisco.com
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