OTRS

Make Customers Smile in 7 Easy Steps with OTRS - Part 4

In Part 3, you learned how to accept, open and close tickets, and use the OTRS interface to communicate with customers and internal team members through the ticket resolution workflow. more>>

Make Customers Smile in 7 Easy Steps with OTRS - Part 3

In Part 2, you learned about agents, customers and queues, and you also got a brief look under OTRS' hood, by learning how to customize the customer self-ervice portal with your own theme and logo. The customer portal is more than just a pretty face, however. more>>

Make Customers Smile in 7 Easy Steps with OTRS - Part 2

In Part 1, I introduced you to OTRS and guided you through the process of installing and configuring oTRS on your system. At the end of Part 1, you were able to log in to the OTRS Dashboard, which serves as the central point for all OTRS operations. more>>

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Make Customers Smile in 7 Easy Steps with OTRS

Back in the old days, if a customer had a problem with a product or service, he'd pick up the phone and dial the service provider or vendor responsible. In most cases, he'd be attended to by a technical expert, who'd ask for details and then attempt to diagnose and resolve the problem. more>>

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Fabric-Based Computing Enables Optimized Hyperscale Data Centers

Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.

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Red Hat White Paper: Using an Open Source Framework to Catch the Bad Guy

Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6

Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.

Learn more about catching the bad guy in this free white paper.

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Sponsored by DLT Solutions