MonALISA Grid Monitoring
LISA:
Menu mode: dynamic | fixed
  HOME       CLIENTS       REPOSITORIES       DOWNLOADS       LOOKING GLASS       FAST DATA TRANSFER  
Last update on:
Dec 03, 2015

Uptime: 267 days, 22h, 40m
Number of requests: 5686641
since 28 October 2005

Local Information Service Agent


LISA is a lightweight monitoring agent that runs on any end-user's system (Linux, Windows, or MacIntosh) using Java Web Start technology. The LISA agent detects the architecture on which it is deployed and dynamically loads the binary applications necessary to perform monitoring and end-to-end network performance measurements. It uses MonALISA lookup services to discover and register with the services and applications it needs, based on a set of attributes (see Figure 1). As it monitors the end-system and network state, it reports all the monitored values to the relevant MonALISA services. When using an external MonALISA service, the LISA agent reports the real IP address and domain name of the computer on which the agent is running, and whether a network address translation (NAT) is being used. This allows the external service to contact the end-system as needed.

The LISA Agent provides:

  • Complete monitoring of the end-system (load, CPU usage, memory allocation, disk usage, disk IO, paging, running processes, network traffic and connectivity).
  • Detection of hardware devices on the system and the drivers used by the kernel to control them.
  • Measurements of end-to-end network performance using different applications (IPERF, WEB100, Ping), which are reported to the user.
  • A user friendly GUI to present all the measured values and the system parameters.
  • Filters to trigger actions when predefined conditions are detected.
In the EVO case, LISA discovers the running reflectors (i.e., the Panda servers) that are good possible candidates to be used by the (Koala) client. This is done by detecting network proximity (Panda servers in the same network, region or country) as well as the load on each of the candidate servers and the current number of clients each one is serving. It creates a short list of candidate "best" reflectors, taking the load on each reflector as well as the network connectivity to it into account.

End-to-end network performance measurements are performed periodically with the reflectors on the short list, and based on these measurements the LISA agent provides the best candidate to the application program. These measurements are continuously performed in the background and in case the connectivity with the .best service. changes, it will notify the application to reconnect to the new "best service". This process is shown schematically in Figure 1.

Figure 1: A schematic view of how LISA agents discover MonALISA services, then use the MonALISA services to connect to the best candidate application instance (a Panda server in the case of EVO). As the selection process proceeds, the MonALISA services perform dynamic load balancing by considering the load on each server.