Trust is the really thorny issue. The WS-Security specification jointly written by IBM and Microsoft addresses signature and encryption only, not ways to establish or verify trust. Microsoft and the Sun-backed Liberty Alliance are busily cooking up separate schemes to federate trust across sets of Web services. Grand Central Networks offers a short-term fix, routing Web services within a zone of trust that it creates. Before the dust settles, another chapter in the long and painful saga of PKI (public key infrastructure) may yet be written.
Developers newly converted to Web services may feel that loose coupling is a bait and switch -- that the rules are shifting before the game has really started. But loose coupling is a design style, not a technology. There's more than one way to do it. Although no one has all the answers, the approaches BEA has taken in WebLogic Workshop are important steps in the right direction.
This whitepaper explains the terminology and concepts behind Data Replication technologies and establishes some sizing rules through worked examples. Learn the new paradigm in disaster tolerance—protect data anywhere.
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Server virtualization is a popular option for dealing with mounting datacenter costs. Another equally promising approach is the use of an Application Delivery Controller. Citrix NetScaler provides a low-cost way for organizations to reduce their server count and accrue cost savings from a reduction in space, cooling, power and personnel.
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The emergence of WLANs has created a new breed of security threats to enterprise networks.
Included in HP ProCurve WLAN solutions is security technology that alleviates threats from WLANs through:
* Monitoring wireless activity inside and out of the enterprise
* Classifying WLAN transmissions into harmful and harmless
* Preventing transmissions that pose a security threat to the enterprise network
* Locating participating devices for physical remediation
Effectively address data protection challenges, implementing solutions that help store and protect business–critical data while cutting costs and improving efficiency and reliability.
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