[ippm] Extending TWAMP for Monitoring Service KPIs

[Srivathsa Sarangapani <[e-mail]>]

Hi All,

New versions of the TWAMP Service Monitoring extension drafts are being posted after addressing the comments given by Greg, Qin and others in the mailing list.
We request you all to please go through the documents and reply back with your comments/suggestions.
The documents are in the below path:

Name:         draft-spv-ippm-monitor-methodology-services-kpi
Revision: 02
Title:        Monitoring Service KPIs using TWAMP - Methodology
Document date: 2016-07-17
Group:        Individual Submission
Pages:        20
URL:            https://www.ietf.org/internet-drafts/draft-spv-ippm-monitor-methodology-services-kpi-02.txt
Status:         https://datatracker.ietf.org/doc/draft-spv-ippm-monitor-methodology-services-kpi/
Htmlized:       https://tools.ietf.org/html/draft-spv-ippm-monitor-methodology-services-kpi-02
Diff:           https://www.ietf.org/rfcdiff?url2=draft-spv-ippm-monitor-methodology-services-kpi-02

Abstract:
   The TWAMP protocol provides a common architecture for two way
   measurements in the IP network.  However IP network performance are
   also affected by a set of L4-L7 service deployed in the network.
   Monitoring of these service performance in the IP network also plays
   a vital role in network optimization and application layer traffic
   optimization.  This capability is not supported by the existing TWAMP
   protocol.

   In this document, we extend TWAMP protocol to support service
   performance monitoring and service KPIs calculation.  Some of the
   existing fields in the TWAMP protocol are extended to support new
   modes for calculating these KPIs.  A set of new messages are added in
   the control protocol between TWAMP client (session sender) and the
   TWAMP server (session reflector).  Services here ranging from Layer 4
   to Layer 7 services,such as Http based services, Traffic load
   balancer, DPI, Video caching, real time streaming and IPSec.  The
   KPIs MAY be service latency, liveliness of an application, number of
   flows and sessions per service, load balancer statistics.

   There is a separate Draft[I.D-spv-ippm-monitor-implementation-
   services-kpi] that talks about implementation of monitoring these
   KPIs in the network using TWAMP.  Monitoring of these KPIs in the
   service plane with in a network play a vital role in optimum usage of
   network resources and improving the overall performance and capacity.


Name:         draft-spv-ippm-monitor-implementation-services-kpi
Revision: 02
Title:        KPI Metrics for Service Monitoring using TWAMP
Document date: 2016-07-17
Group:        Individual Submission
Pages:        9
URL:            https://www.ietf.org/internet-drafts/draft-spv-ippm-monitor-implementation-services-kpi-02.txt
Status:         https://datatracker.ietf.org/doc/draft-spv-ippm-monitor-implementation-services-kpi/
Htmlized:       https://tools.ietf.org/html/draft-spv-ippm-monitor-implementation-services-kpi-02
Diff:           https://www.ietf.org/rfcdiff?url2=draft-spv-ippm-monitor-implementation-services-kpi-02

Abstract:
   We are using a new method to calculate services KPIs and metrics in
   the network using TWAMP protocol.  This draft outlines the
   implementation of the service KPIs and there use cases in the service
   plane in the network.  The KPIs discussed in this draft include
   Service Latency and Application Liveliness detection.

   Service latency is defined as the time spent by the packet when it is
   injected in the service module or service card till the time,
   serviced packet is received back by the TWAMP server.  TWAMP server
   records the timestamp of the packet when it is injected into the
   service module and then again record the timestamp when it receives
   the packet afer service is applied in the data plane.

   Application Liveliness detection means whether the application is up
   and running in the network.  In case you want to monitor the http
   application or the dns server and verify if they are up and running,
   this method is applicable.  The implementation can be used for
   liveliness detection of any service in the network.


—
Regards,
Vathsa