Augur's performance is designed to scale with today's multi-core hardware. And its capabilities scale via plug-ins.
Augur uses threads extensively, so Augur’s capacity tends to grow linearly across CPUs. (Competitors are often bottlenecked by single-threaded databases.)
Augur runs on every modern operating system, including Solaris, Linux, Mac OS X, and Windows. That goes for both the client and server software. Mixed environments are fine too.
Many customers can do fine with one Augur server. If you need more, an Augur cluster is the answer.
From a hot-swap backup scenario (two Augurs) to a distributed enterprise (dozens of Augurs), Augur's cluster technology networks all Augur servers together, as if they were one. The effect is transparent. End-users cannot tell there is more than one Augur, and there is still a single configuration to manage. Yet the design scales because the load is truly distributed to all Augur servers in your cluster.
Configuration is mirrored and synchronized so that any Augur server can quickly take over for a failed server. Even the cluster itself is controlled by a redundant pair of servers.
You won't find this level of scalability and fault tolerance in any other monitoring product.
Plug-in technology extends Augur via an open API.
Handlers extend Augur’s rule engine via subscribed call-outs. This approach is very efficient. You can customize Augur's rules with less concern about performance impact. There are thousands of uses. Some examples:
Each connector plug-in implements a protocol for receiving events. Examples: sockets, SNMP, log files, SQL queries, and your proprietary interfaces too (e.g. RMI, CORBA, etc.)
Not just script commands, menu plug-ins are code executed directly by Augur. Examples: ping a device, draw a custom graph, or launch a custom trouble-ticket interface. Even Augur's own Alert Viewer is implemented as a plug-in. Coming next update.
A messenger implements a notification protocol, such as Email. Coming next update. (Current messengers are built-in.)
Software for managing data and event streams