Internet-Draft IFIT October 2021
Song, et al. Expires 24 April 2022 [Page]
Workgroup:
OPSAWG
Internet-Draft:
draft-song-opsawg-ifit-framework-16
Published:
Intended Status:
Informational
Expires:
Authors:
H. Song
Futurewei
F. Qin
China Mobile
H. Chen
China Telecom
J. Jin
LG U+
J. Shin
SK Telecom

In-situ Flow Information Telemetry

Abstract

As network scale increases and network operation becomes more sophisticated, traditional Operation, Administration and Maintenance (OAM) methods, which include proactive and reactive techniques, running in active and passive modes, are no longer sufficient to meet the monitoring and measurement requirements. Data-plane on-path telemetry techniques which provide high-precision flow insight and real-time issue notification are emerging to support suitable quality of experience for users and applications, and network fault or deficiency identification.

Centering on the new data-plane on-path telemetry techniques, this document outlines a high-level framework to provide an operational environment that utilizes these techniques to enable the collection and correlation of performance measurement information from the network. The framework identifies the components that are needed to coordinate the existing protocol tools and telemetry mechanisms, and addresses key deployment challenges for flow-oriented on-path telemetry techniques, especially in carrier networks.

The framework is informational and intended to guide system designers attempting to apply the referenced techniques as well as to motivate further work to enhance the ecosystem.

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 https://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 24 April 2022.

Table of Contents

1. Introduction

Efficient network operation increasingly relies on high-quality data-plane telemetry to provide the necessary visibility. Traditional Operation, Administration and Maintenance (OAM) methods, which include proactive and reactive techniques, running both active and passive modes, are no longer sufficient to meet the monitoring and measurement requirements when networks becomes more and more autonomous and application-aware. The complexity of today's networks and service quality requirements demand new high-precision and real-time techniques.

The ability to expedite network failure detection, fault localization, and recovery mechanisms, particularly in the case of soft failures or path degradation is expected, without causing service disruption. Application-awareness requires the capacity of a network to maintain current information about users and application connections which may be used to optimize the network resource usage, provide differential services, and improve the quality of service.

The emerging on-path telemetry techniques can provide high-precision flow insight and real-time network issue notification (e.g., jitter, latency, packet loss, significant bit error variations, and unequal load-balancing). On-path telemetry refers to the data-plane telemetry techniques that directly tap and measure network traffic by embedding instructions or metadata into user packets. The data provided by on-path telemetry are especially useful for SLA compliance, user experience enhancement, service path enforcement, fault diagnosis, and network resource optimization. It is essential to recognize that existing work on this topic includes a variety of on-path telemetry techniques, including In-situ OAM(IOAM) [I-D.ietf-ippm-ioam-data], IOAM Direct Export (DEX) [I-D.ietf-ippm-ioam-direct-export], Marking-based Postcard-based Telemetry(PBT-M) [I-D.song-ippm-postcard-based-telemetry], Enhanced Alternate Marking (EAM) [I-D.zhou-ippm-enhanced-alternate-marking], and Hybrid Two Steps (HTS) [I-D.mirsky-ippm-hybrid-two-step], have been proposed, which can provide flow information on the entire forwarding path on a per-packet basis in real-time. The aforementioned on-path telemetry techniques differ from the active and passive OAM schemes discussed earlier in that, they directly modify and monitor the user packets in networks so as to achieve high measurement accuracy. Formally, these on-path telemetry techniques can be classified as the OAM hybrid type I, since they involve "augmentation or modification of the stream of interest, or employment of methods that modify the treatment of the streams", according to [RFC7799].

On-path telemetry is useful for application-aware networking operations not only in data center and enterprise networks but also in carrier networks which may cross multiple domains. Carrier network operators have shown interest in utilizing such techniques for various purposes. For example, it is critical for the operators who offer high-bandwidth, latency and loss-sensitive services such as video streaming and online gaming to closely monitor the relevant flows in real-time as the basis for any further optimizations.

This framework document is intended to guide system designers attempting to use the referenced techniques as well as to motivate further work to enhance the telemetry ecosystem. It highlights requirements and challenges, outlines vital techniques that are applicable, and provides examples of how these might be applied for critical use cases.

The document scope is discussed in Section 1.3.

1.1. Classification and Modes of On-path Telemetry

The operation of on-path telemetry differs from both active OAM and passive OAM as defined in [RFC7799]. It does not generate any active probe packets or passively observes unmodified user packets. Instead, it modifies selected user packets in order to collect useful information about them. Therefore, the operation is categorized as the hybrid OAM type I mode per [RFC7799].

This hybrid type OAM can be further partitioned into two modes [passport-postcard]. In the passport mode, each node on the path adds the telemetry data to the user packets (i.e., stamp the passport). The accumulated data trace is exported at a configured end node. In the postcard mode, each node directly exports the telemetry data using an independent packet (i.e., send a postcard) while the user packets are intact. It is possible to combine the two modes together in one solution. We call this the hybrid mode.

Figure 1 shows the classification of the existing on-path telemetry techniques.


 +-----------+--------------+--------------+---------------+
 |  Mode     | Passport     | Postcard     | Hybrid        |
 +-----------+--------------+--------------+---------------+
 |           | IOAM Trace   | IOAM DEX     | Multicast Te- |
 | Technique | IOAM E2E     | PBT-M        | lemetry       |
 |           |              | EAM          | HTS           |
 +-----------+--------------+--------------+---------------+
Figure 1: On-path Telemetry Technique Classification

IOAM Trace and E2E options are described in [I-D.ietf-ippm-ioam-data]. EAM is described in [I-D.zhou-ippm-enhanced-alternate-marking]. IOAM DEX option is described in [I-D.ietf-ippm-ioam-direct-export]. PBT-M is described in [I-D.song-ippm-postcard-based-telemetry]. Multicast Telemetry is described in [I-D.ietf-mboned-multicast-telemetry]. HTS is described in [I-D.mirsky-ippm-hybrid-two-step].

The advantages of the passport mode include:

  • It automatically retains the telemetry data correlation along the entire path. The self-describing feature eases the data consumption.
  • The on-path data for a packet is only exported once so the data export overhead is low.
  • Only the head and end nodes of the paths need to be configured so the configuration overhead is low.

The disadvantages of the passport mode include:

  • The telemetry data carried by user packets inflate the packet size, which may be undesirable or prohibitive.
  • Approaches for encapsulating the instruction header and data in transport protocols need to be standardized.
  • Carrying sensitive data along the path is vulnerable to security and privacy breach.
  • If a packet is dropped on the path, the data collected are also lost.

The postcard mode complements the passport mode. The advantages of the postcard mode include:

  • Either there is no packet header overhead (e.g., PBT-M) or the overhead is small and fixed (e.g., IOAM DEX).
  • The encapsulation requirement may be avoided (e.g., PBT-M).
  • The telemetry data can be secured before export.
  • Even if a packet is dropped on the path, the partial data collected are still available.

The disadvantages of the postcard mode include:

  • Telemetry data are spread in multiple postcards so extra effort is needed to correlate the data.
  • Every node exports a postcard for a packet which increases the data export overhead.
  • In case of PBT-M, every node on the path needs to be configured, so the configuration overhead is high.
  • In case of IOAM DEX, the transport encapsulation requirement remains.

The hybrid mode either tailors for some specific application scenario (e.g., Multicast Telemetry) or provides some alternative approach (e.g., HTS).

1.2. Requirements and Challenges

Although on-path telemetry is beneficial, successfully applying such techniques in carrier networks must consider performance, deployability, and flexibility. Specifically, we need to address the following practical deployment challenges:

1.3. Scope

Following the network telemetry framework discussed in [I-D.ietf-opsawg-ntf], this document focuses on the on-path telemetry, a specific class of data-plane telemetry techniques, and provides a high-level framework which addresses the aforementioned challenges for deployment, especially in carrier operator networks.

This document aims to clarify the problem space, essential requirements, and summarizes best practices and general system design considerations. This document provides some examples to show the novel network telemetry applications under the framework.

As an informational document, it describes an open framework with a few key components. The framework does not enforces any specific implementation on each component, neither does it define interfaces (e.g., API, protocol) between components. The choice of underlying on-path telemetry techniques and other implementation details is determined by application implementer. Therefore, the framework is not a solution specification. It only provides a high-level overview and is not necessarily a mandatory recommendation for on-path telemetry applications.

The standardization of the underlying techniques and interfaces mentioned in this document is undertaken by various working groups. Due to the limited scope and intended status of this document, it has no overlap or conflict with those works.

1.4. Glossary

This section defines and explains the acronyms and terms used in this document.

On-path Telemetry:
Remotely acquiring performance and behavior data about network flows on a per-packet basis on the packet's forwarding path. The term refers to a class of data-plane telemetry techniques, including IOAM, PBT, EAM, and HTS. Such techniques may need to mark user packets, or insert instruction/ metadata to the headers of user packets.
IFIT:
In-situ Flow Information Telemetry is a high-level reference framework that shows how network data-plane monitoring and measurement applications can address the deployment challenges of the flow-oriented on-path telemetry techniques.
Reflective Telemetry:
The telemetry functions in a dynamic and closed-loop fashion. A new telemetry action is provisioned as a result of self-knowledge acquired through prior telemetry actions.

1.5. 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.

2. Architectural Concepts and Key Components

To address the challenges mentioned above, a high-level framework which can help to build a workable and efficient on-path telemetry application is presented. In-situ Flow Information Telemetry (IFIT) is dedicated to on-path telemetry data about user and application traffic flows. It covers a class of on-path telemetry techniques and works a level higher than any specific underlying technique. The framework is comprised of some key functional components (Section 2.2). By assembling these components, IFIT supports reflective telemetry that enables autonomous network operations (Section 2.4).

2.1. Typical Deployment

Figure 2 shows a typical deployment scenario of on-path telemetry.

                                Application
                   +-------------------------------------+
                   |             Controller              |
                   | +------------+        +-----------+ |
                   | | Configure  |        | Collector | |
                   | |     &      |<-------|     &     | |
                   | | Control    |        | Analyzer  | |
                   | +-----:------+        +-----------+ |
                   |       :                     ^       |
                   +-------:---------------------|-------+
                           :configuration        |telemetry data
                           :& action             |
            ...............:.....................|..........
            :             :                 :    |         :
            :   +---------:---+-------------:---++---------:---+
            :   |         :   |             :   |          :   |
            V   |         V   |             V   |          V   |
         +------+-+     +-----+--+       +------+-+     +------+-+
  packets| Head   |     | Path   |       | Path   |     | End    |
      ==>| Node   |====>| Node   |==//==>| Node   |====>| Node   |==>
         |        |     | A      |       | B      |     |        |
         +--------+     +--------+       +--------+     +--------+

         |<---          On-path Telemetry Domain             --->|
Figure 2: Deployment Scenario

An on-path telemetry application can conduct some network data-plane monitoring and measurement tasks over a limited domain by applying one or more underlying techniques. The application needs to contains multiple elements, including configuring the network nodes and processing the telemetry data. The application usually runs in a logically centralized controller which is responsible for configuring the network nodes in the domain, and collecting and analyzing telemetry data. The configuration determines which underlying technique is used, what telemetry data are of interest, which flows and packets are concerned with, how the telemetry data are collected, etc. The process can be dynamic and interactive: after the telemetry data processing and analyzing, the application may instruct the controller to modify the configuration of the nodes, which affects the future telemetry data collection.

From the system-level view, it is recommended to use the standardized configuration and data collection interfaces, regardless of the underlying technique. The specification of these interfaces and the implementation of the controller are out of scope for this document.

The on-path telemetry domain encompasses the head nodes and the end nodes, and may cross multiple network domains. The head nodes are responsible for enabling the on-path telemetry functions and the end nodes are responsible for terminating them. All capable nodes in this domain will be capable of executing the instructed on-path telemetry function. It is important to note that any application must, through configuration and policy, guarantee that any packet with on-path telemetry header and metadata will not leak out of the domain.

The underlying on-path telemetry techniques covered by the IFIT framework can be of any modes discussed in Section 1.1.

2.2. Key Components

The key components of IFIT are as follows, to address the challenges mentioned above:

  • Flexible flow, packet, and data selection policy, addressing the challenge C1 described in Section 1;
  • Flexible data export, addressing the challenge C2;
  • Dynamic network probe, addressing C3;
  • On-demand technique selection and integration, addressing C4.

Note that the challenges C5 and C6 are mostly standard related, which are fundamental to IFIT. We discuss the protocol implications and guidance for solution developers in Section 3.

In the following section, we provide a detailed description of each component.

2.2.1. Flexible Flow, Packet, 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 impact. Therefore, a workable solution usually need to select only a subset of flows and flow packets to enable the data collection, even though this means the loss of some information and accuracy.

In the data plane, the Access Control List (ACL) provides an ideal means to determine the subset of flow(s). An application can set a sample rate or probability to a flow to allow only a subset of flow packets to be monitored, collect a different set of data for different packets, and disable or enable data collection on any specific network node. An application can further allow any node to accept or deny the data collection process in full or partially.

Based on these flexible mechanisms, IFIT allows applications to apply flexible 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.

2.2.1.1. Block Diagram
            +----------------------------+
            | +----------+  +----------+ |
            | |Flow      |  |Data      | |
            | |Selection |  |Selection | |
            | +----------+  +----------+ |
            | +----------+               |
            | |Packet    |               |
            | |Selection |               |
            | +----------+               |
            +----------------------------+
Figure 3: Flexible Flow, Packet, and Data Selection

Figure 3 shows the block diagram of this component. The flow selection block defines the policies to choose target flows for monitoring. Flow has different granularity. A basic flow is defined by 5-tuple IP header fields. Flow can also be aggregated at interface level, tunnel level, protocol level, and so on. The packet selection block defines the policies to choose packets from a target flow. The policy can be either a sampling interval, a sampling probability, or some specific packet signature. The data selection block defines the set of data to be collected. This can be changed on a per-packet or per-flow basis.

2.2.1.2. Example: Sketch-guided Elephant Flow Selection

Network operators are usually more interested in elephant flows which consume more resource and are sensitive to changes in network conditions. A CountMin Sketch [CMSketch] can be used on the data path of the head nodes, which identifies and reports the elephant flows periodically. The controller maintains a current set of elephant flows and dynamically enables the on-path telemetry for only these flows.

2.2.1.3. Example: Adaptive Packet Sampling

Applying on-path telemetry on all packets of selected flows can still be out of reach. A sample rate should be set for these flows and only enable telemetry on the sampled packets. However, the head nodes have no clue on the proper sampling rate. An overly high rate would exhaust the network resource and even cause packet drops; An overly low rate, on the contrary, would result in the loss of information and inaccuracy of measurements.

An adaptive approach can be used based on the network conditions to dynamically adjust the sampling rate. Every node gives user traffic forwarding higher priority than telemetry data export. In case of network congestion, the telemetry can sense some signals from the data collected (e.g., deep buffer size, long delay, packet drop, and data loss). The controller may use these signals to adjust the packet sampling rate. In each adjustment period (i.e., RTT of the feedback loop), the sampling rate is either decreased or increased in response of the signals. An AIMD policy similar to the TCP flow control mechanism for the rate adjustment can be used.

2.2.2. Flexible Data Export

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 efficient export data encoding (e.g., IPFIX [RFC7011] or protobuf), nodes have several other ways to reduce the export data by taking advantage of network device's capability and programmability. Nodes can 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 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.

Such events can be expressed as policies. An policy can request data export only on change, on exception, on timeout, or on threshold.

2.2.2.1. Block Diagram
            +-------------------------------------------+
            | +-----------+ +-----------+ +-----------+ |
            | |Data       | |Data       | |Export     | |
            | |Encoding   | |Batching   | |Protocol   | |
            | +-----------+ +-----------+ +-----------+ |
            | +-----------+ +-----------+ +-----------+ |
            | |Data       | |Data       | |Data       | |
            | |Compression| |Dedup.     | |Filter     | |
            | +-----------+ +-----------+ +-----------+ |
            | +-----------+ +-----------+               |
            | |Data       | |Data       |               |
            | |Computing  | |Aggregation|               |
            | +-----------+ +-----------+               |
            +-------------------------------------------+
Figure 4: Flexible Data Export

Figure 4 shows the block diagram of this component. The data encoding block defines the method to encode the telemetry data. The data batching block defines the size of batch data buffered at the device side before export. The export protocol block defines the protocol used for telemetry data export. The data compression block defines the algorithm to compress the raw data. The data deduplication block defines the algorithm to remove the redundancy in the raw data. The data filter block defines the policies to filter the needed data. The data computing block defines the policies to prepocess the raw data and generate some new data. The data aggregation block defines the procedure to combine and synthesize the data.

2.2.2.2. Example: Event-based Anomaly Monitor

Network operators are interested in the anomalies such as path change, network congestion, and packet drop. Such anomalies are hidden in raw telemetry data (e.g., path trace, timestamp). Such anomalies can be described as events and programmed into the device data plane. Only the triggered events are exported. For example, if a new flow appears at any node, a path change event is triggered; if the packet delay exceeds a predefined threshold in a node, the congestion event is triggered; if a packet is dropped due to buffer overflow, a packet drop event is triggered.

The export data reduction due to such optimization is substantial. For example, given a single 5-hop 10Gbps path, assume a moderate number of 1 million packets per second are monitored, and the telemetry data plus the export packet overhead consume less than 30 bytes per hop. Without such optimization, the bandwidth consumed by the telemetry data can easily exceed 1Gbps (more than 10% of the path bandwidth), When the optimization is used, the bandwidth consumed by the telemetry data is negligible. Moreover, the pre-processed telemetry data greatly simplify the work of data analyzers.

2.2.3. Dynamic Network Probe

Due to limited data plane resource and network bandwidth, it is unlikely one can monitor 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). DNP is the technique to enable probes for customized data collection in different network planes. When working with an on-path telemetry technique, 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.

2.2.3.1. Block Diagram
            +----------------------------+
            | +----------+  +----------+ |
            | |ACL       |  |YANG      | |
            | |          |  |Model     | |
            | +----------+  +----------+ |
            | +----------+  +----------+ |
            | |Hardware  |  |Software  | |
            | |Function  |  |Function  | |
            | +----------+  +----------+ |
            +----------------------------+
Figure 5: Dynamic Network Probes

Figure 5 shows the block diagram of this component. The Access Control List (ACL) block is available in most hardware and it defines DNPs through dynamically update the ACL policies (including flow filtering and action). YANG models can be dynamically deployed to enable different data processing and filtering functions. Some hardware allows dynamically loading hardware-based functions into the forwarding path at runtime through mechanisms such as reserved pipelines and function stubs. Dynamically loadable software functions can be implemented in the control processors in capable nodes.

2.2.3.2. Examples

Following are some possible DNPs that can be dynamically deployed to support applications.

On-demand Flow Sketch:
A flow sketch is a compact online data structure (usually a variation of multi-hashing table) for approximate estimation of multiple flow properties. It can be used to facilitate flow selection. The aforementioned CountMin Sketch [CMSketch] is such an example. Since a sketch consumes data plane resources, it should only be deployed when actually needed.
Smart Flow Filter:
The policies that choose flows and packet sampling rate can change during the lifetime of an application.
Smart Statistics:
An application may need to count flows based on different flow granularity or maintain hit counters for selected flow table entries.
Smart Data Reduction:
DNP can be used to program the events that conditionally trigger data export.

2.2.4. 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 passport or postcard mode to collect the data; if an application needs to track down where the packets are lost, switching from passport mode to postcard mode should be supported.

IFIT can further integrate multiple data plane monitoring and measurement techniques together and present a comprehensive data plane telemetry solution.

Based on the application requirements and the real-time telemetry data analysis results, new configurations and actions can be deployed.

2.2.4.1. Block Diagram
            +----------------------------------------------+
            | +------------+  +-------------+  +---------+ |
            | |Application |  |Configuration|  |Telemetry| |
            | |Requirements|->|& Action     |<-|Data     | |
            | |            |  |             |  |Analysis | |
            | +------------+  +-------------+  +---------+ |
            +----------------------------------------------+
            | Passport Mode:                               |
            | +----------+   +----------+                  |
            | |IOAM E2E  |   |IOAM Trace|                  |
            | +----------+   +----------+                  |
            | Postcard Mode:                               |
            | +----------+   +----------+   +----------+   |
            | |PBT-M     |   |IOAM DEX  |   |EAM       |   |
            | +----------+   +----------+   +----------+   |
            | Hybrid Mode:                                 |
            | +----------+   +----------+                  |
            | |HTS       |   |Multicast |                  |
            | |          |   |Telemetry |                  |
            | +----------+   +----------+                  |
            +----------------------------------------------+
Figure 6: Technique Selection and Integration

Figure 6 shows the block diagram of this component, which lists the candidate on-path telemetry techniques.

Located in the logically centralized controller, this component makes all the control and configuration dynamically to the capable nodes in the domain which will affect the future telemetry data. The configuration and action decisions are based on the inputs from the application requirements and the realtime telemetry data analysis results. Note that here the telemetry data source is not limited to the data plane. The data can come form all the sources mentioned in [I-D.ietf-opsawg-ntf], including external data sources.

2.3. Relationship with Network Telemetry Framework (NTF)

[I-D.ietf-opsawg-ntf] describes a Network Telemetry Framework (NTF). One dimension used by NTF to partition network telemetry techniques and systems is based on the three planes in networks plus external data sources. IFIT fits in the category of forwarding-plane telemetry and deals with the specific on-path technical branch of the forwarding-plane telemetry.

According to NTF, an on-path telemetry application mainly subscribes event-triggered or streaming data. The key functional components of IFIT match the components in NTF. "On-demand Technique Selection and Integration" is an application layer function, matching the "Data Query, Analysis, and Storage" component in NTF; "Flexible Flow, Packet, and Data Selection" matches the "Data Configuration and Subscription" component; "Flexible Data Export" matches the "Data Encoding and Export" component; "Dynamic Network Probe" matches the "Data Generation and Processing" component.

2.4. IFIT for Reflective Telemetry

The above components can work together to support reflective telemetry, as shown in Figure 7.

                        +---------------------+
                        |                     |
                 +------+    Applications     |<------+
                 |      |                     |       |
                 |      +---------------------+       |
                 |         Technique Selection        |
                 |         and Integration            |
                 |                                    |
                 |Flexible                   Flexible |
                 |Flow,     reflection-loop      Data |
                 |Packet,                       Export|
                 |and Data                            |
                 |Selection                      +----+----+
                 V                              +---------+|
           +----------+ Encapsulation          +---------+||
           |  Head    | and Tunneling          |  Path   |||
           |  Node    |----------------------->|  Nodes  ||+
           |          |                        |         |+
           +----------+                        +---------+
               DNP                                DNP

Figure 7: IFIT-based Reflective Telemetry

An application may pick a suite of telemetry techniques based on its requirements and apply an initial technique to the data plane. It then configures the head nodes to decide the initial target flows/packets and telemetry data set, the encapsulation and tunneling scheme based on the underlying network architecture, and the IFIT-capable nodes to decide the initial telemetry data export policy. Based on the network condition and the analysis results of the telemetry data, the application can change the telemetry technique, the flow/data selection policy, and the data export approach in real time without breaking the normal network operation. Many of such dynamic changes can be done through loading and unloading DNPs.

The reflective telemetry enabled by the IFIT allows numerous new applications suitable for future network operation architecture. Two examples are provided below.

2.4.1. Intelligent Multipoint Performance Monitoring

[RFC8889] describes an intelligent performance management based on the network condition. The idea is to split the monitoring network into clusters. The cluster partition that can be applied to every type of network graph and the possibility to combine clusters at different levels enable the so-called Network Zooming. It allows a controller to calibrate the network telemetry, so that it can start without examining in depth and monitor the network as a whole. In case of necessity (packet loss or too high delay), an immediate detailed analysis can be reconfigured. In particular, the controller, that is aware of the network topology, can set up the most suited cluster partition by changing the traffic filter or activate new measurement points and the problem can be localized with a step-by-step process.

An application on top of the controllers can manage such mechanism, whose dynamic and reflective operations are supported by the IFIT framework.

2.4.2. Intent-based Network Monitoring


                      User Intents
                            |
                            V          Per-packet
                      +------------+   Telemetry
               ACL    |            |   Data
             +--------+ Controller |<--------+
             |        |            |         |
             |        +--+---------+         |
             |           |       ^           |
             |           |DNPs   |Network    |
             |           |       |Information|
             |           V       |           |
      +------+-------------------+-----------+---+
      |      |                                   |
      |      V                      +------+     |
      | +-------+                  +------+|     |
      | | Head  |                 +------+||     |
      | | Node  |                 |Path  ||+     |
      | |       |                 |Nodes |+      |
      | +-------+                 +------+       |
      +------------------------------------------+
Figure 8: Intent-based Monitoring

In this example, a user can express high level intents for network monitoring. The controller translates an intent and configure the corresponding DNPs in capable nodes which collect necessary network information. Based on the real-time information feedback, the controller runs a local algorithm to determine the suspicious flows. It then deploys ACLs to the head node to initiate the high precision per-packet on-path telemetry for these flows.

3. Guidance for Solution Developers

Having a high-level framework covering a class of related techniques also promotes a holistic approach for standard development and helps to avoid duplicated efforts and piecemeal solutions that only focus on a specific technique while omitting the compatibility and extensibility issues, which is important to a healthy ecosystem for network telemetry.

A complete IFIT-based solution needs standard interfaces for configuration and data extraction, and standard encapsulation on various transport protocols. It may also need standard API and primitives for application programming and deployment. The draft [I-D.ietf-ippm-ioam-deployment] summarizes some current proposals on encapsulation and data export for IOAM. Solution developers need to consider the following aspects from the protocol point of view.

3.1. Encapsulation in Transport Protocols

Since the introduction of IOAM, the IOAM option header encapsulation schemes in various network protocols have been proposed. Similar encapsulation schemes need to be extended to cover the other on-path telemetry techniques. Meanwhile, the encapsulation schemes for some popular protocols, such as MPLS and IPv4, are noticeably missing. It is important to provide solutions for these protocols because they are still prevalent in carrier 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. While there are some proposals which allow new header encapsulation in MPLS packets (e.g., [I-D.song-mpls-extension-header]) or in IPv4 packets (e.g., [I-D.herbert-ipv4-eh]), they are still in their infancy stage and require significant future work. Before standards are available, in a confined domain, pre-standard encapsulation approaches may be applied.

3.2. Tunneling Support

In carrier networks, it is common for user traffic to traverse various tunnels for QoS, traffic engineering, or security. Both the uniform mode and the pipe mode for tunnel support are required and 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.

3.3. Deployment Automation

In addition, standard approaches that automates the function configuration, and capability query and advertisement, could either be in a centralized fashion or a distributed fashion. The draft [I-D.ietf-ippm-ioam-yang] provides the YANG model for IOAM configuration. Similar models needs to be defined for other techniques. It is also helpful to provide standards-based approaches for configuration in various network environments. For example, in segment routing networks, extensions to BGP or PCEP can be defined to distribute SR policies carrying on-path telemetry information, so that telemetry behavior can be enabled automatically when the SR policy is applied. [I-D.chen-pce-sr-policy-ifit] proposes to extend PCEP policy for on-path telemetry configuration in segment routing networks. [I-D.ietf-idr-sr-policy-ifit] proposes to extend BGP policy in segment routing networks. Additional capability discovery and dissemination will be needed for other types of networks.

To realize the potential of on-path telemetry, programming and deploying DNPs are important. ForCES [RFC5810] is a standard protocol for network device programming, which can be used for DNP deployment. Currently some related works such as [I-D.wwx-netmod-event-yang] and [I-D.bwd-netmod-eca-framework] have proposed to use YANG model to define the smart policies which can be used to implement DNPs. In the future, other approaches for hardware and software-based functions can be development to enhance the programmability and flexibility.

4. Security Considerations

In addition to the specific security issues discussed in each individual document on on-path telemetry, this document considers the overall security issues at the system level. This should serve as a guide to the on-path telemetry application developers and users. General security and privacy considerations for any network telemetry system are also discussed in [I-D.ietf-opsawg-ntf].

5. IANA Considerations

This document includes no request to IANA.

6. Contributors

Other major contributors of this document include Giuseppe Fioccola, Daniel King, Zhenqiang Li, Zhenbin Li, Tianran Zhou, and James Guichard.

7. Acknowledgments

We thank Diego Lopez, Shwetha Bhandari, Joe Clarke, Adrian Farrel, Frank Brockners, Al Morton, Alex Clemm, Alan DeKok, Benoit Claise, and Warren Kumari for their constructive suggestions for improving this document.

8. References

8.1. Normative References

[RFC2119]
Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, , <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, , <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, , <https://www.rfc-editor.org/info/rfc8174>.

8.2. Informative References

[CMSketch]
Cormode, G. and S. Muthukrishnan, "An improved data stream summary: the count-min sketch and its applications", , <http://dx.doi.org/10.1016/j.jalgor.2003.12.001>.
[I-D.bwd-netmod-eca-framework]
Boucadair, M., Wu, Q., Wang, M., King, D., and C. Xie, "Framework for Use of ECA (Event Condition Action) in Network Self Management", Work in Progress, Internet-Draft, draft-bwd-netmod-eca-framework-00, , <https://www.ietf.org/archive/id/draft-bwd-netmod-eca-framework-00.txt>.
[I-D.chen-pce-sr-policy-ifit]
Chen, H., Yuan, H., Zhou, T., Li, W., Fioccola, G., and Y. Wang, "PCEP SR Policy Extensions to Enable IFIT", Work in Progress, Internet-Draft, draft-chen-pce-sr-policy-ifit-02, , <https://www.ietf.org/archive/id/draft-chen-pce-sr-policy-ifit-02.txt>.
[I-D.herbert-ipv4-eh]
Herbert, T., "IPv4 Extension Headers and Flow Label", Work in Progress, Internet-Draft, draft-herbert-ipv4-eh-01, , <https://www.ietf.org/archive/id/draft-herbert-ipv4-eh-01.txt>.
[I-D.ietf-idr-sr-policy-ifit]
Qin, F., Yuan, H., Zhou, T., Fioccola, G., and Y. Wang, "BGP SR Policy Extensions to Enable IFIT", Work in Progress, Internet-Draft, draft-ietf-idr-sr-policy-ifit-02, , <https://www.ietf.org/archive/id/draft-ietf-idr-sr-policy-ifit-02.txt>.
[I-D.ietf-ippm-ioam-data]
Brockners, F., Bhandari, S., and T. Mizrahi, "Data Fields for In-situ OAM", Work in Progress, Internet-Draft, draft-ietf-ippm-ioam-data-15, , <https://www.ietf.org/archive/id/draft-ietf-ippm-ioam-data-15.txt>.
[I-D.ietf-ippm-ioam-deployment]
Brockners, F., Bhandari, S., Bernier, D., and T. Mizrahi, "In-situ OAM Deployment", Work in Progress, Internet-Draft, draft-ietf-ippm-ioam-deployment-00, , <https://www.ietf.org/archive/id/draft-ietf-ippm-ioam-deployment-00.txt>.
[I-D.ietf-ippm-ioam-direct-export]
Song, H., Gafni, B., Zhou, T., Li, Z., Brockners, F., Bhandari, S., Sivakolundu, R., and T. Mizrahi, "In-situ OAM Direct Exporting", Work in Progress, Internet-Draft, draft-ietf-ippm-ioam-direct-export-07, , <https://www.ietf.org/archive/id/draft-ietf-ippm-ioam-direct-export-07.txt>.
[I-D.ietf-ippm-ioam-yang]
Zhou, T., Guichard, J., Brockners, F., and S. Raghavan, "A YANG Data Model for In-Situ OAM", Work in Progress, Internet-Draft, draft-ietf-ippm-ioam-yang-01, , <https://www.ietf.org/archive/id/draft-ietf-ippm-ioam-yang-01.txt>.
[I-D.ietf-mboned-multicast-telemetry]
Song, H., McBride, M., Mirsky, G., Mishra, G., Asaeda, H., and T. Zhou, "Multicast On-path Telemetry Solutions", Work in Progress, Internet-Draft, draft-ietf-mboned-multicast-telemetry-01, , <https://www.ietf.org/archive/id/draft-ietf-mboned-multicast-telemetry-01.txt>.
[I-D.ietf-opsawg-ntf]
Song, H., Qin, F., Martinez-Julia, P., Ciavaglia, L., and A. Wang, "Network Telemetry Framework", Work in Progress, Internet-Draft, draft-ietf-opsawg-ntf-09, , <https://www.ietf.org/archive/id/draft-ietf-opsawg-ntf-09.txt>.
[I-D.mirsky-ippm-hybrid-two-step]
Mirsky, G., Lingqiang, W., Zhui, G., and H. Song, "Hybrid Two-Step Performance Measurement Method", Work in Progress, Internet-Draft, draft-mirsky-ippm-hybrid-two-step-11, , <https://www.ietf.org/archive/id/draft-mirsky-ippm-hybrid-two-step-11.txt>.
[I-D.song-ippm-ioam-tunnel-mode]
Song, H., Li, Z., Zhou, T., and Z. Wang, "In-situ OAM Processing in Tunnels", Work in Progress, Internet-Draft, draft-song-ippm-ioam-tunnel-mode-00, , <https://www.ietf.org/archive/id/draft-song-ippm-ioam-tunnel-mode-00.txt>.
[I-D.song-ippm-postcard-based-telemetry]
Song, H., Mirsky, G., Filsfils, C., Abdelsalam, A., Zhou, T., Li, Z., Shin, J., and K. Lee, "Postcard-based On-Path Flow Data Telemetry using Packet Marking", Work in Progress, Internet-Draft, draft-song-ippm-postcard-based-telemetry-10, , <https://www.ietf.org/archive/id/draft-song-ippm-postcard-based-telemetry-10.txt>.
[I-D.song-mpls-extension-header]
Song, H., Li, Z., Zhou, T., Andersson, L., and Z. Zhang, "MPLS Extension Header", Work in Progress, Internet-Draft, draft-song-mpls-extension-header-05, , <https://www.ietf.org/archive/id/draft-song-mpls-extension-header-05.txt>.
[I-D.wwx-netmod-event-yang]
Wu, Q., Bryskin, I., Birkholz, H., Liu, X., and B. Claise, "A YANG Data model for ECA Policy Management", Work in Progress, Internet-Draft, draft-wwx-netmod-event-yang-10, , <https://www.ietf.org/archive/id/draft-wwx-netmod-event-yang-10.txt>.
[I-D.zhou-ippm-enhanced-alternate-marking]
Zhou, T., Fioccola, G., Liu, Y., Lee, S., Cociglio, M., and W. Li, "Enhanced Alternate Marking Method", Work in Progress, Internet-Draft, draft-zhou-ippm-enhanced-alternate-marking-07, , <https://www.ietf.org/archive/id/draft-zhou-ippm-enhanced-alternate-marking-07.txt>.
[passport-postcard]
Handigol, N., Heller, B., Jeyakumar, V., Mazieres, D., and N. McKeown, "Where is the debugger for my software-defined network?", , <https://doi.org/10.1145/2342441.2342453>.
[RFC5810]
Doria, A., Ed., Hadi Salim, J., Ed., Haas, R., Ed., Khosravi, H., Ed., Wang, W., Ed., Dong, L., Gopal, R., and J. Halpern, "Forwarding and Control Element Separation (ForCES) Protocol Specification", RFC 5810, DOI 10.17487/RFC5810, , <https://www.rfc-editor.org/info/rfc5810>.
[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, , <https://www.rfc-editor.org/info/rfc7011>.
[RFC8889]
Fioccola, G., Ed., Cociglio, M., Sapio, A., and R. Sisto, "Multipoint Alternate-Marking Method for Passive and Hybrid Performance Monitoring", RFC 8889, DOI 10.17487/RFC8889, , <https://www.rfc-editor.org/info/rfc8889>.

Authors' Addresses

Haoyu Song
Futurewei
2330 Central Expressway
Santa Clara,
United States of America
Fengwei Qin
China Mobile
No. 32 Xuanwumenxi Ave., Xicheng District
Beijing, 100032
P.R. China
Huanan Chen
China Telecom
Jaehwan Jin
LG U+
South Korea
Jongyoon Shin
SK Telecom
South Korea