INCREASINGLY, CALCULATIONS ARE based on timed
events originating at many sources. By comparing,
contrasting, joining, and noodling over these inputs,
you can derive some interesting results. If the
inputs to these calculations come from disparate
computers (or sensors), you can’t always be sure of
how quickly the information will propagate. Hence,
you can’t be sure when you will get an answer to the
If you can’t promise when you will get the answer,
what are you going to do? You can wait to get the
perfect answer, or you can give an imperfect answer
more promptly by basing it on partial knowledge.
How can you meet your SLAs (service-level agreements)?
Sometimes, it’s not an easy and seamless continuum of
options but more of a discontinuum.
Events and time. In many systems, events come with
a timestamp. These may come from temperature
sensors, motion detectors, factory floors, your cable box,
your security system, automated tollbooths on the
freeway, and much more. One source of information
that is increasingly important is the
monitoring of events in datacenters.
These events may be used by an auto-
mated management system or by hu-
mans in complex error spelunking. It
is common to try to see which events
happened close in time to another par-
ticular event. Patterns in time proxim-
ity are essential to controlling these
Events and space. Now, all this is
cool except when the information
you want is “over there.” In a distributed system, if the stuff is not “here,”
it’s “over there.” When something is
far away and over there, it may take a
loooonnng time to get information in
and out. It can be kind of like when the
only road up the canyon gets washed
out in a flood. I refer to remote nodes
as being “over yonder” whether they
are in the same rack in the datacenter
or thousands of miles away.
Space, Distance, and Traffic Jams
If it’s over there with an open queuing
network, it will usually get here in a
timely fashion. Almost all modern
networks are open queuing networks.
In such a network, there’s no practical limit to the amount of stuff that
may try to share the network. Highway
101 through San Francisco is an open
Article development led by
Combining data from many sources
may cause painful delays.
BY PAT HELLAND