In-situ Flow Information Telemetry Framework
draft-song-opsawg-ifit-framework-04
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| Authors | Haoyu Song , Zhenbin Li , Tianran Zhou , Fengwei Qin , Jongyoon Shin , Jaewhan Jin | ||
| Last updated | 2019-09-06 (Latest revision 2019-07-08) | ||
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draft-song-opsawg-ifit-framework-04
OPSAWG H. Song, Ed.
Internet-Draft Futurewei
Intended status: Informational Z. Li
Expires: March 9, 2020 T. Zhou
Huawei
F. Qin
China Mobile
J. Shin
SK Telecom
J. Jin
LG U+
September 6, 2019
In-situ Flow Information Telemetry Framework
draft-song-opsawg-ifit-framework-04
Abstract
Unlike the existing active and passive OAM techniques, the emerging
on-path flow telemetry techniques provide unmatched visibility into
user traffic, showing great application potential not only for
today's network OAM but also for future's automatic network
operation. Summarizing the current industry practices that addresses
the deployment challenges and application requirements, we provide a
closed-loop framework, named In-situ Flow Information Telemetry
(iFIT), for efficiently applying a family of underlying on-path flow
telemetry techniques in various network environments. The framework
enumerates several key architectural components and describes how
these components are assembled together to achieve a complete and
closed-loop working solution for on-path flow telemetry. Following
such a framework allows better scalability, fosters application
innovations, and promotes both vertical and horizontal
interoperability.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP
14 [RFC2119][RFC8174] when, and only when, they appear in all
capitals, as shown here.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on March 9, 2020.
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Copyright (c) 2019 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
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Table of Contents
1. Requirements and Challenges . . . . . . . . . . . . . . . . . 3
2. iFIT Framework Overview . . . . . . . . . . . . . . . . . . . 4
3. Smart Flow and Data Selection . . . . . . . . . . . . . . . . 6
4. Export Data Reduction . . . . . . . . . . . . . . . . . . . . 6
5. Dynamic Network Probe . . . . . . . . . . . . . . . . . . . . 7
6. Encapsulation and Tunnel Modes . . . . . . . . . . . . . . . 7
7. On-demand Technique Selection and Integration . . . . . . . . 8
8. Summary and Future Work . . . . . . . . . . . . . . . . . . . 8
9. Security Considerations . . . . . . . . . . . . . . . . . . . 8
10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
11. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 9
12. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 9
13. References . . . . . . . . . . . . . . . . . . . . . . . . . 9
13.1. Normative References . . . . . . . . . . . . . . . . . . 9
13.2. Informative References . . . . . . . . . . . . . . . . . 9
13.3. URIs . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 11
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1. Requirements and Challenges
Application-aware network operation is important for user SLA
compliance, service path enforcement, fault diagnosis, and network
resource optimization. A family of on-path flow telemetry
techniques, including In-situ OAM (IOAM)
[I-D.brockners-inband-oam-data], PBT
[I-D.song-ippm-postcard-based-telemetry], IFA [I-D.kumar-ippm-ifa],
Enhanced AM [I-D.zhou-ippm-enhanced-alternate-marking], and HTS
[I-D.mirsky-ippm-hybrid-two-step], are emerging, which can provide
flow information on the entire forwarding path on a per-packet basis
in real time. These techniques are very different from the previous
active and passive OAM schemes in that they directly modify the user
packets and can gain visibility on every user packet. Given the
unique characteristics of such techniques, we categorize these on-
path telemetry techniques as the hybrid OAM type III, supplementing
the classification defined in [RFC7799].
These techniques are invaluable for application-aware network
operations not only in data center and enterprise networks but also
in carrier networks which may cross multiple domains. Carrier
network operators have shown strong interests in utilizing such
techniques for various purposes. For example, it is vital for the
operators who offer the bandwidth intensive, latency and loss
sensitive services such as video streaming and gaming to closely
monitor the relevant flows in real time as the indispensable first
step for any further measure.
However, successfully applying such techniques in carrier networks
poses several practical challenges:
o C1: On-path flow telemetry incurs extra packet processing which
may strain the network data plane. The potential impact on the
forwarding performance creates an unfavorable "observer effect"
which not only damages the fidelity of the measurement but also
defies the purpose of the measurement.
o C2: On-path flow telemetry can generate a huge amount of OAM data
which may claim too much transport bandwidth and inundate the
servers for data collection, storage, and analysis. Increasing
the data handling capacity is technically viable but expensive.
o C3: The collectible data defined currently are essential but
limited. As the network operation evolves to become intent-based
and automatic, and the trends of network virtualization, network
convergence, and packet-optical integration continue, more data
will be needed in an on-demand and interactive fashion.
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Flexibility and extensibility on data defining and acquiring must
be considered.
o C4: If we were to apply some on-path telemetry technique in
today's carrier networks, we must provide solutions to tailor the
provider's network deployment base and support an incremental
deployment strategy. That is, we need to come up with
encapsulation schemes for various predominant protocols such as
Ethernet, IPv4, and MPLS with backward compatibility and properly
handle various transport tunnels.
o C5: Applying only a single underlying telemetry technique may lead
to defective result. For example, packet drop can cause the lost
of the flow telemetry data and the packet drop location and reason
remains unknown if only In-situ OAM trace option is used. A
comprehensive solution needs the flexibility to switch between
different underlying techniques and adjust the configurations and
parameters at runtime.
2. iFIT Framework Overview
To address these challenges, we propose a framework based on multiple
network operators' requirements and the common industry practice,
which can help to build a workable on-path flow telemetry solution.
We name the framework "In-situ Flow Information Telemetry" (iFIT) to
reflect the fact that this framework is dedicated to the on-path
telemetry data about user/application flow experience. As a solution
framework, iFIT works a level higher than any specific OAM
techniques, be it active, passive, or hybrid. The framework is built
up on a few architectural components. By assembling these components
together, a closed-loop is formed to provide a complete solution for
a particular static, dynamic, and interactive telemetry applications.
iFIT is an open framework. It does not enforce any implementation
details for each component. Users are free to pick one or more
underlying techniques and design their own algorithms and
architectures to fit in each component and make all the components
work in concert.
The network architecture that applies iFIT is shown in Figure 1. The
iFIT domain is confined between the iFIT head nodes and the iFIT end
nodes. An iFIT domain may cross multiple network domains. iFIT
support two basic on-path telemetry data collection modes: passport
mode (e.g., IOAM trace option and IFA), in which telemetry data are
carried in user packets and exported at the iFIT end nodes, and
postcard mode (e.g., PBT), in which each node in the iFIT domain may
export telemetry data through independent OAM packets. Note that the
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boundary between the two modes can be blurry. An application only
need to mix the two modes.
The key components of iFIT is listed as follows:
o Smart flow and data selection policy to address C1.
o Export data reduction to address C2.
o Dynamic network probe to address C3.
o Encapsulation and tunnel modes to address C4.
o On-demand technique selection to address C5.
+---------------------------------+
| |
| iFIT Applications |
| |
+---------------------------------+
^ ^
| |
V |
+------------+ +-----+-----+
| | | |
| Controller | | Collector |
| | | |
+-----:------+ +-----------+
: ^
:configuration |telemetry data
: |
...............:.....................|..........
: : : | :
: +---------:---+-------------:---++---------:---+
: | : | : | : |
V | V | V | V |
+------+-+ +-----+--+ +------+-+ +------+-+
usr pkts | iFIT | | Path | | Path | | iFIT |
====>| Head |====>| Node |==//==>| Node |====>| End |====>
| Node | | A | | B | | Node |
+--------+ +--------+ +--------+ +--------+
Figure 1: iFIT Architecture
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In the remaining of the document, we provide the detailed discussion
of the iFIT's components.
3. Smart Flow and Data Selection
In most cases, it is impractical to enable the data collection for
all the flows and for all the packets in a flow due to the potential
performance and bandwidth impacts. Therefore, a workable solution
must select only a subset of flows and flow packets to enable the
data collection, even though this means the loss of some information.
In data plane, the Access Control List (ACL) provides an ideal means
to determine the subset of flow(s).
[I-D.song-ippm-ioam-data-validation-option] describes how one can set
a sample rate or probability to a flow to allow only a subset of flow
packets to be monitored, how one can collect different set of data
for different packets, and how one can disable or enable data
collection on any specific network node. The document further
introduces enhancement to IOAM to allow any node to accept or deny
the data collection in full or partially.
Based on these flexible mechanisms, iFIT allows applications to apply
smart flow and data selection policies to suit the requirements. The
applications can dynamically change the policies at any time based on
the network load, processing capability, focus of interest, and any
other criteria. We have developed some adaptive algorithm which can
limit the performance impact and yet achieve the satisfactory
telemetry data density.
4. Export Data Reduction
The flow telemetry data can catch the dynamics of the network and the
interactions between user traffic and network. Nevertheless, the
data inevitably contain redundancy. It is advisable to remove the
redundancy from the data in order to reduce the data transport
bandwidth and server processing load.
In addition to efficiently encode the export data (e.g., IPFIX
[RFC7011] or protobuf [1]), iFIT can also cache the data and send the
accumulated data in batch if the data is not time sensitive. Various
deduplication and compression techniques can be applied on the batch
data.
From the application perspective, an application may only be
interested in some special events which can be derived from the
telemetry data. For example, in case that the forwarding delay of a
packet exceeds a threshold or a flow changes its forwarding path is
of interest, it is unnecessary to send the original raw data to the
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data collecting and processing servers. Rather, iFIT takes advantage
of the in-network computing capability of network devices to process
the raw data and only push the event notifications to the subscribing
applications.
5. Dynamic Network Probe
Due to the limited data plane resource, it is unlikely one can
provide all the data all the time. On the other hand, the data
needed by applications may be arbitrary but ephemeral. It is
critical to meet the dynamic data requirements with limited resource.
Fortunately, data plane programmability allows iFit to dynamically
load new data probes. These on-demand probes are called Dynamic
Network Probes (DNP) [I-D.song-opsawg-dnp4iq]. DNP is the technique
to enable probes for customized data collection in different network
planes. When working with IOAM or PBT, DNP is loaded to the data
plane through incremental programming or configuration. The DNP can
effectively conduct data generation, processing, and aggregation.
DNP introduces enough flexibility and extensibility to iFIT. It can
implement the optimizations for export data reduction motioned in the
previous section. It can also generate custom data as required by
today and tomorrow's applications.
6. Encapsulation and Tunnel Modes
Since MPLS and IPv4 network are still prevalent in carrier networks.
iFIT provides solutions to apply the on-path flow telemetry
techniques in such networks. PBT-M
[I-D.song-ippm-postcard-based-telemetry] does not introduce new
headers to the packets so the trouble of encapsulation for a new
header is avoided. In case a technique that requires a new header is
preferred, [I-D.song-mpls-extension-header] provides a means to
encapsulate the extra header using an MPLS extension header. As for
IPv4, it is possible to encapsulate the new header in an IP option.
For example, RAO [RFC2113] can be used to indicate the presence of
the new header. A recent proposal [I-D.herbert-ipv4-eh] that
introduces the IPv4 extension header may lead to a long term
solution.
In carrier networks, it is common for user traffic to traverse
various tunnels for QoS, traffic engineering, or security. iFIT
supports both the uniform mode and the pipe mode for tunnel support
as described in [I-D.song-ippm-ioam-tunnel-mode]. With such
flexibility, the operator can either gain a true end-to-end
visibility or apply a hierarchical approach which isolates the
monitoring domain between customer and provider.
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7. On-demand Technique Selection and Integration
With multiple underlying data collection and export techniques at its
disposal, iFIT can flexibly adapt to different network conditions and
different application requirements.
For example, depending on the types of data that are of interest,
iFIT may choose either IOAM or PBT to collect the data; if an
application needs to track down where the packets are lost, it may
switch from IOAM to PBT.
iFIT can further integrate multiple data plane monitoring and
measurement techniques together and present a comprehensive data
plane telemetry solution to network operating applications.
8. Summary and Future Work
iFIT is a framework for applying on-path data plane telemetry
techniques. Combining with algorithmic and architectural schemes
that fit into the framework components, iFIT framework enables a
practical telemetry solution based on two basic on-path traffic data
collection modes: passport and postcard.
The operation of iFIT differs from both active OAM and passive OAM as
defined in [RFC7799]. It does not generate any active probe packets
or passively observe unmodified user packets. Instead, it modifies
selected user packets to collect useful information about them.
Therefore, the iFIT operation can be considered the hybrid type III
mode, which can provide more flexible and accurate network OAM.
More challenges and corresponding solutions for iFIT may need to be
covered. For example, how iFIT can fit in the big picture of
autonomous networking and support closed control loops. A complete
iFIT framework should also consider the cross-domain operations. We
leave these topics for future revisions.
9. Security Considerations
No specific security issues are identified other than those have been
discussed in the drafts on on-path flow information telemetry.
10. IANA Considerations
This document includes no request to IANA.
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11. Contributors
TBD.
12. Acknowledgments
TBD.
13. References
13.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC7799] Morton, A., "Active and Passive Metrics and Methods (with
Hybrid Types In-Between)", RFC 7799, DOI 10.17487/RFC7799,
May 2016, <https://www.rfc-editor.org/info/rfc7799>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
13.2. Informative References
[I-D.brockners-inband-oam-data]
Brockners, F., Bhandari, S., Pignataro, C., Gredler, H.,
Leddy, J., Youell, S., Mizrahi, T., Mozes, D., Lapukhov,
P., Chang, R., and d. daniel.bernier@bell.ca, "Data Fields
for In-situ OAM", draft-brockners-inband-oam-data-07 (work
in progress), July 2017.
[I-D.herbert-ipv4-eh]
Herbert, T., "IPv4 Extension Headers and Flow Label",
draft-herbert-ipv4-eh-01 (work in progress), May 2019.
[I-D.kumar-ippm-ifa]
Kumar, J., Anubolu, S., Lemon, J., Manur, R., Holbrook,
H., Ghanwani, A., Cai, D., Ou, H., and L. Yizhou, "Inband
Flow Analyzer", draft-kumar-ippm-ifa-01 (work in
progress), February 2019.
[I-D.mirsky-ippm-hybrid-two-step]
Mirsky, G., Lingqiang, W., and G. Zhui, "Hybrid Two-Step
Performance Measurement Method", draft-mirsky-ippm-hybrid-
two-step-03 (work in progress), April 2019.
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[I-D.song-ippm-ioam-data-validation-option]
Song, H. and T. Zhou, "In-situ OAM Data Validation
Option", draft-song-ippm-ioam-data-validation-option-02
(work in progress), April 2018.
[I-D.song-ippm-ioam-tunnel-mode]
Song, H., Li, Z., Zhou, T., and Z. Wang, "In-situ OAM
Processing in Tunnels", draft-song-ippm-ioam-tunnel-
mode-00 (work in progress), June 2018.
[I-D.song-ippm-postcard-based-telemetry]
Song, H., Zhou, T., Li, Z., Shin, J., and K. Lee,
"Postcard-based On-Path Flow Data Telemetry", draft-song-
ippm-postcard-based-telemetry-04 (work in progress), June
2019.
[I-D.song-mpls-extension-header]
Song, H., Li, Z., Zhou, T., and L. Andersson, "MPLS
Extension Header", draft-song-mpls-extension-header-02
(work in progress), February 2019.
[I-D.song-opsawg-dnp4iq]
Song, H. and J. Gong, "Requirements for Interactive Query
with Dynamic Network Probes", draft-song-opsawg-dnp4iq-01
(work in progress), June 2017.
[I-D.zhou-ippm-enhanced-alternate-marking]
Zhou, T., Fioccola, G., Li, Z., Lee, S., Cociglio, M., and
Z. Li, "Enhanced Alternate Marking Method", draft-zhou-
ippm-enhanced-alternate-marking-03 (work in progress),
July 2019.
[RFC2113] Katz, D., "IP Router Alert Option", RFC 2113,
DOI 10.17487/RFC2113, February 1997,
<https://www.rfc-editor.org/info/rfc2113>.
[RFC7011] Claise, B., Ed., Trammell, B., Ed., and P. Aitken,
"Specification of the IP Flow Information Export (IPFIX)
Protocol for the Exchange of Flow Information", STD 77,
RFC 7011, DOI 10.17487/RFC7011, September 2013,
<https://www.rfc-editor.org/info/rfc7011>.
[RFC8321] Fioccola, G., Ed., Capello, A., Cociglio, M., Castaldelli,
L., Chen, M., Zheng, L., Mirsky, G., and T. Mizrahi,
"Alternate-Marking Method for Passive and Hybrid
Performance Monitoring", RFC 8321, DOI 10.17487/RFC8321,
January 2018, <https://www.rfc-editor.org/info/rfc8321>.
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13.3. URIs
[1] https://developers.google.com/protocol-buffers/
Authors' Addresses
Haoyu Song (editor)
Futurewei
2330 Central Expressway
Santa Clara
USA
Email: haoyu.song@futurewei.com
Zhenbin Li
Huawei
156 Beiqing Road
Beijing, 100095
P.R. China
Email: lizhenbin@huawei.com
Tianran Zhou
Huawei
156 Beiqing Road
Beijing, 100095
P.R. China
Email: zhoutianran@huawei.com
Fengwei Qin
China Mobile
No. 32 Xuanwumenxi Ave., Xicheng District
Beijing, 100032
P.R. China
Email: qinfengwei@chinamobile.com
Jongyoon Shin
SK Telecom
South Korea
Email: jongyoon.shin@sk.com
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Jaewhan Jin
LG U+
South Korea
Email: daenamu1@lguplus.co.kr
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