Network Management Research Group J. Nobre
Internet-Draft L. Granville
Intended status: Informational Federal University of Rio Grande do Sul
Expires: December 22, 2014 A. Clemm
A. Prieto
Cisco Systems
June 20, 2014
Autonomic Networking Use Case for Distributed Detection of SLA
Violations
draft-irtf-nmrg-autonomic-sla-violation-detection-00
Abstract
This document describes a use case for autonomic networking in
distributed detection of SLA violations. It is one of a series of
use cases intended to illustrate requirements for autonomic
networking.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Problem Statement . . . . . . . . . . . . . . . . . . . . . . 3
3. Benefits of an Autonomic Solution . . . . . . . . . . . . . . 4
4. Intended User and Administrator Experience . . . . . . . . . 5
5. Analysis of Parameters and Information Involved . . . . . . . 5
5.1. Device Based Self-Knowledge and Decisions . . . . . . . . 5
5.2. Interaction with other devices . . . . . . . . . . . . . 5
5.3. Information needed from Intent . . . . . . . . . . . . . 6
5.4. Monitoring, diagnostics and reporting . . . . . . . . . . 6
6. Comparison with current solutions . . . . . . . . . . . . . . 6
7. Related IETF Work . . . . . . . . . . . . . . . . . . . . . . 6
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 7
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 7
10. Security Considerations . . . . . . . . . . . . . . . . . . . 7
11. References . . . . . . . . . . . . . . . . . . . . . . . . . 7
11.1. Normative References . . . . . . . . . . . . . . . . . . 7
11.2. Informative References . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 8
1. Introduction
The Internet has been improving dramatically in terms of size and
capacity, and accessibility in the last years. Besides that, the
communication requirements of distributed services and applications
running on top of the Internet have become increasingly accurate.
Performance issues caused by violations on these requirements usually
present significant financial loss to organizations and end users.
Thus, the service level requirements of critical networked services
provided have become a critical concern for network administrators.
To ensure that SLAs are not being violated, which would usually incur
in costly penalties, service levels need to be constantly monitored
at the 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 measurement, network conditions are said to be 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
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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]. Active measurement mechanisms usually
offer better accuracy and privacy than passive measurement
mechanisms. Furthermore, active measurement mechanisms are able to
detect end-to-end network performance problems in a fine-grained way.
As a result, active is preferred over passive measurement for SLA
monitoring. Measurement probes must be hosted and activated in
network devices to compute the current network metrics (e.g.,
considering those described in [RFC4148]). This activation should
dynamic in order to follow changes in network conditions, such as
those related with routes being added or new customer demands.
2. Problem Statement
The activation of active measurement probes (sender and responder
considering the architecture described by Cisco [RFC6812]) is
expensive in terms of the resource consumption, e.g., CPU cycle and
memory footprint, which could be useful for primary network functions
(e.g., routing and switching). Besides that, the probes also
increase the network load because of the injected traffic. The
resources required and traffic generated by the measurement probes
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 probes. Thus, to have a better
monitoring coverage it is necessary to deploy more probes 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. The current best practice in feasible
deployments of active measurement solutions to distribute the
available measurement probes along the network consists in relying
entirely on the human administrator expertise to infer which would be
the best location to activate the probes. 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 probes. After that, the administrator activates probes
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 probes 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 probes and administrators are not just enough in
computing and activating the new set of probes required every time
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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. Management software can be
embedded inside network devices to control the deployment of active
measurement mechanisms. In fact, this is done by some network
equipment vendors, specially to avoid the starvation of the network
devices (e.g., due to configuration errors and lack of experience
from human administrators). However, the current approach do not
enhance the active measurement capabilities in important terms, such
as scalability and efficiency. For example, the number of local
available measurements (and, consequently, detected SLA violations)
is still bounded by the number of deployed probes. Thus, if the
number of SLA violation is greater than the number of available
probes, only a fraction of the violations will be observed. Also,
devices cannot share resources and knowledge about the networking
infrastructures in order to take advantage of remote management
information (e.g., measurement results).
3. Benefits of an Autonomic Solution
The use case considered here is distributed autonomic detection of
SLA violations. The use of Autonomic Netowrking (AN) properties can
help the activation of measurement probes [P2PBNM-Nobre-2012]. Peer-
to-Peer (P2P) technology can be embedded in network devices in order
to improve the probe activation decisions using autonomic loops.
Thus, it would be possible to coordinate the probe activation and to
share measurement results among different network devices. The
problem to be solved by AN in the present use case is how to steer
the process of measurement probe activation by a complete solution
that sets all necessary parameters for this activation to operate
efficiently, reliably and securely, with minimal human intervention
and without the need for. An autonomic solution for the distributed
detection of SLA violations can provide several benefits. First,
this solution could optimize the resource consumption and avoid
resource starvation on the network devices. This optimization comes
from different sources: sharing of measurement results, better
efficiency in the probe activation decisions, etc. Second, 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 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. 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
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considers that multiple Service Level Objectives (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.
4. Intended User and Administrator Experience
The autonomic solution should avoid 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 is necessary from the
human administrator. For example, the human administrator should
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.
5. Analysis of Parameters and Information Involved
5.1. 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.
5.2. Interaction with other devices
Network devices could share information about service level
measurement results. This information could 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
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 could use its known endpoints neighbors (e.g.,
FIB and RIB tables) as the initial seed to get possible peers.
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5.3. Information needed from Intent
TBD
5.4. Monitoring, diagnostics and reporting
TBD
6. 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.
7. 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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8. Acknowledgements
We wish to acknowledge the helpful contributions, comments, and
suggestions that were received from Bruno Klauser, Eric Voig, and
Hanlin Fang.
9. IANA Considerations
This memo includes no request to IANA.
10. Security Considerations
The bootstrapping of a new device follows the approach of homenet
[draft-autonomic-homenet], 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.
11. References
11.1. Normative References
[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, September 2006.
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[RFC5357] Hedayat, K., Krzanowski, R., Morton, A., Yum, K., and J.
Babiarz, "A Two-Way Active Measurement Protocol (TWAMP)",
RFC 5357, October 2008.
[RFC6812] Chiba, M., Clemm, A., Medley, S., Salowey, J., Thombare,
S., and E. Yedavalli, "Cisco Service-Level Assurance
Protocol", RFC 6812, January 2013.
[draft-autonomic-homenet]
Behringer, M., Pritikin, M., and S. Bjarnason, "draft-
behringer-homenet-trust-bootstrap", draft-behringer-
homenet-trust-bootstrap-02 (work in progress), February
2014.
11.2. Informative References
[RFC3954] Claise, B., "Cisco Systems NetFlow Services Export Version
9", RFC 3954, October 2004.
[RFC4148] Stephan, E., "IP Performance Metrics (IPPM) Metrics
Registry", BCP 108, RFC 4148, August 2005.
Authors' Addresses
Jeferson Campos Nobre
Federal University of Rio Grande do Sul
Porto Alegre
Brazil
Email: jcnobre@inf.ufrgs.br
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
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Alberto Gonzalez Prieto
Cisco Systems
San Jose
USA
Email: albertgo@cisco.com
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