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Ubiquitous Resource Monitoring with GridRM

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Sensors (specialised devices, Web cam, microphone) ... The gateway is selected and we now want to see data sources... a better Web interface - GridSphere ... – PowerPoint PPT presentation

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Title: Ubiquitous Resource Monitoring with GridRM


1
Ubiquitous Resource Monitoring with GridRM
  • Mark Baker and Garry Smith
  • Distributed Systems Group
  • University of Portsmouth, UK
  • http//gridrm.org/

2
Outline
  • Background.
  • Overview.
  • Architecture.
  • The GridRM Portal.
  • Summary.
  • Further Work.

3
Background
  • Lack of knowledge about the status of the
    resources in any distributed system will hamper
    strategies for optimal scheduling, allocation and
    usage.
  • There is a need for a flexible framework that
    provides information about the health and status
    of Grid resources
  • Gathering resource information, such as
  • Compute (nodes, CPU, memory),
  • Network (inter-site communications links, network
    devices),
  • Sensors (specialised devices, Web cam,
    microphone),
  • Software services (information services,
    schedulers).
  • Need a generic system that does not need another
    local agent, but can utilise whatever exists
  • SNMP, Network Weather Service, NetLogger,
    Ganglia, /proc, MDS,

4
Overview
  • GridRM is resource monitoring system that
    provides
  • A scalable monitoring architecture,
  • A standards-based information system that is
    independent of underlying middleware,
  • A means of harvesting heterogeneous data and
    presenting it in a homogeneous form,
  • An abstract means of data collection,
  • An extensible infrastructure that can be bound to
    diverse data sources (legacy, and emerging ones),
  • A means of gathering data that can be used for a
    range of purposes such as scheduling, autonomic
    computing, verification of SLA, and creating
    higher-level knowledge

5
Architecture
6
Global Layer
7
jGMA
  • Needed a lightweight implementation of the GGF
    Grid Monitoring Architecture in Java.
  • Used jGMA, a Java-based version of the GMA for
    details see
  • Mini-Workshop Grid Performability Modelling and
    Measurement
  • Friday 3 September 2004
  • 1110 - 1315 - Parallel Session 6
  • Room Auditorium

8
Local Layer
9
Data Management Issues
10
Solutions Simple API
  • Producing an API is fairly simple, but creating
    one that will be taken up and accepted is another
    matter.
  • We using an API based on JDBC from Java.
  • Example of API
  • Agent Driver Interface
  • forName(GridRM.sql.driver.NWSDriver)
  • forName(GridRM.sql.agent.SNMPv1Driver)
  • Connection Interface
  • String agentURL gridrm//barney5550/GLUECE_ho
    st
  • Connection con DriverManager.getConnection(agent
    URL)
  • Statement Interface
  • Statement stmt con.createStatement()
  • ResultSet rs stmt.executeQuery(SELECT FROM
    ProcessorLoad)
  • Manipulating Results
  • ResultSet is another interface contains a handful
    of methods for manipulating the data returned
    from the agent.

11
Solutions XML Schema
  • No single naming schema for this area at the
    moment.
  • We needed something to mark-up the information
    that can be gathered by the local agents
  • Static and dynamic information
  • Name/IP/OS/Processor/NIC/
  • CPU load/memory available/disk space/network/
  • Did not want to produce our own schema, so chose
    an emerging one that is increasingly being used -
    Grid Laboratory Uniform Environment (GLUE)
    schema
  • A schema that defines the attributes of computer
    system resources (CE/NE/)
  • Others, CIM, UNICORE, etc..

12
GridRM Drivers and Manager
  • The GridRM Driver Manager locates appropriate
    drivers for underlying agents
  • Passes SQL requests to drivers and returns
    normalised results
  • The Driver Manager also provides other
    functionality that is particular to GridRM such
    as configuration, caching, streaming or
    pushing/pulling data to/from clients.

13
Local Layer Use of SQL
  • SQL used extensively throughout the framework.
  • All resources are seen as databases and queried
    using SQL.
  • Resource queries enter the framework as SQL
    syntax.
  • Pluggable resource drivers are implemented as
    JDBC drivers
  • Translate SQL requests into native protocol.
  • Normalise results according to selected schema.
  • Framework benefits from a single, flexible
    approach to resource interaction.
  • Makes for a simple, extensible framework.

14
GridRM Portal
  • The GridRM Portal (gridrm.org) is a demonstration
    of gateways, data sources, SQL and data
    normalisation.
  • An example of the use of GridRM, particularly its
    ability to discover and utilise resource data.
  • An example of a GridRM client which
  • Allows the use of GridRM with no knowledge of the
    underlying technologies.
  • Hides details like SQL, XML, etc
  • Provides an abstraction everyone can use
    clickerity click!).

15
GridRM Portal
16
Portal Simple Queries
  • Query resources across configured gateways.
  • Pre-defined query options point click!
  • A Web form shields the user from SQL syntax and
    other low-level details.
  • An example query
  • Retrieve details of all compute resources
  • The user is authorised to use,
  • From the selected Grid sites,
  • That meet specified constraints for
  • Memory, processor load, architecture.

17
Portal Simple Query Form (2)
18
Portal Simple Query Results
19
Portal Simple Query Results
  • Comparative views of resource processor loads
    from the query in the previous slide
  • Missing bars indicate idle machines.

20
Portal SQL Interface
  • Aim Query a given data source, using SQL, for
    performance attributes, but without knowing the
    monitoring protocol it natively supports.
  • The SQL commands can
  • show gateways Get a list of registered gateways.
  • use gateway Select a gateway to query DSG
    Workgroup Gateway.
  • show datasources Get a list of all data sources
    registered with the gateway.
  • use datasource Select a particular data source -
    homer.dsg.port.ac.uk
  • show databases Retrieve a list of naming schemas
    supported by this data source driver.
  • use GLUECE_host Query a host resource data using
    the GLUE Computing Element schema.

21
Portal SQL Interface
  • show tables Observe the way the naming schema
    partitions resource data.
  • desc architecture Describe what an architecture
    table will provide.
  • select from Architecture Read the
    architecture type for this data source.
  • select Last5min, Last15min from ProcessorLoad
    Read the 5 and 15 minute load averages.

22
Portal SQL Interface
  • show gateways Get a list of registered gateways
  • We need to find the list of gateways currently
    available to us.
  • Enter show gateways into the command line

23
Portal SQL Interface
  • The list of gateways is returned.
  • Select a gateway to query with the use gateway
    syntax
  • We enter the DSG gateway.

24
Portal SQL Interface
  • The show datasources command returns a list of
    all data sources registered with the gateway
  • The gateway is selected and we now want to see
    data sources
  • We choose the holly data source

25
Portal SQL Interface
  • We decide to go ahead and query host resource
    data using the GLUE Computing Element schema.
  • Select the database use GLUECE_host.
  • Display the tables available to us show tables
    (on the chosen GLUECE_host database).
  • The translation schema partitions the retrieved
    data into tables.
  • We can select all fields or individual named
    fields in each table.

26
Portal SQL Interface
  • Get the table definition desc Architecture

27
Portal SQL Interface
  • Query the resource driver for Architecture and
    CPU load averages for last 5 and 15 minute
  • select from Architecture
  • select Last5min, Last15min from ProcessorLoad

28
Summary
  • Heterogeneous information returned from a diverse
    range of possible data sources.
  • Need to harvest data into a homogeneous form
  • Hide underlying complexity from clients.
  • Provide data in a format that meets a clients
    requirements.
  • Combine legacy resources with modern cluster and
    Grid information servers to provide
  • An over-arching Grid information system.
  • Independent of particular middleware and
    services.
  • GridRM promotes homogeneity through
  • JDBC-like data source driver,
  • Standard SQL syntax,
  • The GLUE naming schemas,
  • Request translation and result normalisation,
  • GLUE XML encoded results.

29
Future Work
  • Provide an example of a job submission system
    using GridRM, several options
  • Other schedulers, Condor, SGE,
  • Further security
  • Integrate UK e-Science certificates for resource
    access control.
  • Performance and scalability testing.
  • More translation schema for different resource
  • DBMS, telescope, surf conditions!
  • Use of portlet technologies to provide a better
    Web interface - GridSphere
  • Secure interface for remote Gateway
    administration.

30
More Information
  • GridRM, http//gridrm.org
  • jGMA, http//dsg.port.ac.uk/projects/jGMA/
  • GMA WG, http//www-didc.lbl.gov/GGF-PERF/GMA-WG/
  • GLUE, http//www.hicb.org/glue/glue.htm
  • JDBC, http//java.sun.com/products/jdbc/
  • Ganglia, http//ganglia.sourceforge.net/
  • SNMP, http//net-snmp.sourceforge.net/
  • NetLogger, http//www-didc.lbl.gov/NetLogger/
  • NWS, http//nws.cs.ucsb.edu

31
Testbed Status (1)
  • Currently have 12 sites across 8 countries

32
Testbed Status (2)
  • List of sites and status http//gridrm.org/testbe
    d.html
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