Historical Analysis
In real life, it's impossible to go back in time, but in the world of operations
management, AutoNOC makes time travel possible!One attribute of AutoNOC is that it works like a black box, or a
flight recorder storing a detailed by minute history of everything happening across the
network in all systems and applications. When a problem occurs, troubleshooting it is
little more than looking back in time to see what, where, and when it happened. In many
cases the recorded, categorized, and hierarchically organized information will provide
enough clues into why and how the problem occurred!
The following screenshot shows an
example high-resolution archive of traffic data for the internal AutoNOC network.

The Recoiling Database (RDB)
Managing, archiving, and accessing the vast volumes of information AutoNOC acquires is
certainly a non-trivial exploit. Legacy management solutions have used SQL servers, text
files, and other third party forms of storage to try and maintain the vast quantities of
data a long term historical record of network activity requires.
AutoNOC's compressing recoiling database
technology solves the data warehousing problems customers often have to deal with when
using legacy systems. Recoiling database technology collects data in memory and than,
based on an interval "recoils" the database. A spring stretches out over time
and when released it snaps back into a tight coil. Recoiling database technology works in
much the same way. It collects the typically sparse data over time and then "tightens
the coil" periodically.
This automated, background process works
extremely well for the type of data that AutoNOC acquires (sparse with all records growing
simultaneously).
AutoNOC can typically store about 1 year
of high resolution probe data in about a megabyte of disk storage. The database is indexed
and provides high performance windowed access to the information stored within the
recoiling database. This architecture has proven ideal for the types of reads and writes
that occur within real world operations management scenarios. |