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Route analytics technologies could help solve many enterprise companies' network management and performance problems, Forrester Research says.
While the network takes the lion's share of the blame when it comes to downtime, Forrester's recent report says the network hardware often isn't to blame. The research firm found in a survey that 15% of respondents pointed to the network as the cause for failures: but just 2% of failures were determined to be hardware-related, while 13% resulted from human error, unmanaged changes, misconfigurations, routing failures and problems with network software. Report author and Forrester analyst Thomas Mendel in part blames the inherent nature of networks.
"IP is to blame. IP was designed primarily for resilience. It was never meant to provide end-to-end quality of service for response-time sensitive applications," the report states. "Routers provide intelligence by dynamically selecting different routes for the packets. Unfortunately, this makes running the network a challenge."
Mendel says route analytics products address the shortcomings of traditional network management products when addressing the challenges routing poses to performance. Mendel identifies the four fundamental shortcomings in network management software: "they are not real-time; they are not scalable; they are weak at root-cause analysis; and they are unable to plan the routing impact of future network growth and change."
According to Mendel, route analytics products from companies such as Packet Design, Ipsum Networks and Bluewave Networks can help deliver optimal performance over WANs and the Internet. The market for this product by year-end could reach $10 million, Forrester says, and it is projected to grow at about an 80% compound annual growth rate by 2008 as route analytics features become integral to the network and configuration management portfolios of the leading vendors.
The benefits of route analytics include the technology's ability to make possible end-to-end service visibility, to discover routing anomalies, to predict the results of configuration changes and to provide performance baselines for applications and services.

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