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An Active Events Model for Systems Monitoring. Philip Gross Columbia University Programming Systems Lab Director: Gail Kaiser. Motivation: Loose Coupling. Want to maximize ease of distributed programming Not only should middleware deliver events…

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An active events model for systems monitoring

An Active Events Model for Systems Monitoring

Philip Gross

Columbia University

Programming Systems Lab

Director: Gail Kaiser


Motivation loose coupling
Motivation: Loose Coupling

  • Want to maximize ease of distributed programming

  • Not only should middleware deliver events…

  • It should completely shield participants from knowledge of each other

  • Information goes into the cloud, information comes out of the cloud

2


Problem no event context
Problem: No Event Context

  • Consumers get data that they’re “supposed” to get

  • Confusion and ambiguity can be major problems

3


Example stock trading program
Example: Stock Trading Program

  • Sub (MSFT > 80) // sell and cash in

  • Event published with MSFT = 60: ignored

  • Event published with MSFT = 1515: received, all shares sold

  • Are we rich yet?

  • Unfortunately no: was appointment with MS sales rep at 3:15pm

4


We conclude that
We Conclude That…

  • We need to associate semantics with event data

  • Somehow saying “this is what I mean,” or “here’s how to interpret me”

  • Events that explicitly indicate semantics, we call Active Events, or ActEvents

  • They’re not just passive data containers

5


Two flavors of information bus
Two Flavors of Information Bus

  • Light model: information is carried by a notification service

    • High speed, low latency, simple behavior

  • Heavy model: information is carried by self-transmitting software agents

    • Lower speed, higher latency, more sophisticated behavior

6


And two flavors of actevents
And Two Flavors of ActEvents

  • By reference or by value

  • By reference: SmartEvents

    • Data includes structured tags

    • External processor maps tags to semantics

  • By value: Gaugents

    • Agent ferries not just data…

    • But also mobile code that has semantic knowledge

7


Smartevent implementation
SmartEvent Implementation

  • XML embedded in event

  • Certain tags “exposed” for routing

  • XML annotated to provide syntactic and semantic information

  • FleXML (Flexible XML) enables dynamic runtime schema and semantics discovery and composition

8


Initial smartevents
Initial SmartEvents

  • Language recognition problem

  • Validate against Schema

  • When unknown element encountered, ask “Semantic Server” for

    • New schema fragment

    • Processing modules (Tag Processors)

  • Tag Processors give higher-level events

  • Supports dynamic schema composition

9


Newer smartevents
Newer SmartEvents

  • XML is described with multiple namespaces

  • Namespaces provide direct syntactic identification

  • Which allows lookup of Tag Processors

  • Semantics still looked up dynamically

  • Still supports dynamic schema composition

  • Tag Processors can maintain state over event streams

10


Two flavors of information bus1
Two Flavors of Information Bus

  • Light model: information is carried by a notification service

    • High speed, low latency, simple behavior

  • Heavy model: information is carried by self-transmitting software agents

    • Lower speed, higher latency, more sophisticated behavior

11


Gaugent implementation
Gaugent Implementation

  • Specialization of Worklets mobile agents

  • Worklet Virtual Machine (WVM) installed at each participating node

  • Java bytecode based

  • Routing can be altered on the fly

  • Carries data and processing code

12


Gaugents continued
Gaugents Continued

  • Worklets normally carry one junction for each WVM they plan to visit

    • Encapsulates computation to be performed at that location

    • Contains semantic information

  • May carry jackets

    • Provide a mini-workflow for a particular junction, e.g. repetition, start/exit constraints, etc.

    • Contain manipulable routing information

13




Future directions
Future Directions

  • New event system

  • Extended FleXML

  • Web services

16


Future event system
Future Event System

  • MEEP? CHIEF?

  • Native XML

  • Scalability, survivability, performance

  • VPENs: Virtual Private Event Networks

    • Event diodes for Multi-Level Security

  • Content-based routing, but with significant optimizations for topic-based advertisements

  • GPL

17


Conclusions
Conclusions

  • Semantic annotation of events is essential for loosely coupled architectures

  • Different solutions are appropriate for different types of information exchange

  • We have built two implementations

  • More experimentation needed

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Extended flexml
Extended FleXML

  • Currently one interpretation per incoming event per Metaparser

  • Multiple consumers may need multiple interpretations

  • Thus sets of Tag Processors may be applied to produce multiple high-level “interpretations”

20


Web services
Web Services

  • Juggernaut: Sun, IBM, Microsoft all pushing it hard

  • Has significant implications for service interoperability projects

  • In particular: SOAP and WSDL

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An active events model for systems monitoring
SOAP

  • Very nice encapsulation

  • Future probe-gauge standard?

<env:Envelope xmlns:env="http://www.w3.org/2001/09/soap-envelope">

<env:Header>

<n:alertcontrol xmlns:n="http://example.org/alertcontrol">

<n:priority>1</n:priority>

<n:expires>2001-06-22T14:00:00-05:00</n:expires>

</n:alertcontrol>

</env:Header>

<env:Body>

<m:alert xmlns:m="http://example.org/alert">

<m:msg>Pick up Mary at school at 2pm</m:msg>

</m:alert>

</env:Body>

</env:Envelope>

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An active events model for systems monitoring
WSDL

  • Web Services Description Language

  • Useful for where Pub/Sub meets RPC

    • Types/Messages

    • Operation: organize into inputs and outputs

    • PortType: collection of Operations

    • Binding: mapping of PortType to e.g. SOAP

    • Service: set of bound PortTypes at an actual location

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