Serializing Web Application Requests
Queuing requests with GNQS allows another interesting option which we may pursue in the future as our processing demands increase. Instead of migrating the server again to an even more powerful machine or to the complexity of an array of web servers, we could retain the existing web server as a front-end server. Without any changes in the CGI scripts on the web server, GNQS could be reconfigured to distribute queued jobs across as many additional machines as necessary to meet our response time requirements. Since GNQS can also do load balancing, expansion can be done easily, efficiently and dynamically with no server down time. The number of queue servers would be completely transparent to the web server.
There are a number of ways to handle web applications which require significant back-end processing time. Optimizing application servers requires different techniques than optimizing servers for high hit rates. For application servers, the limiting resource may be CPU, memory or disk I/O, rather than network bandwidth. Response times to given requests are expected to be relatively slow, and informing waiting users of the status of their jobs is important. Queuing requests with GNQS and referring the user to a results page has proven to be an effective, easily implemented and robust technique.
Colin C. Wilson has been programming and administering UNIX systems since 1985. He has been happily playing with Linux for the past four years while employed at the University of Washington, developing DNA analysis software and keeping the systems up at the Human Genome Center. When he's not busy recovering from the latest disaster, he can be reached at colin@u.washington.edu.
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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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.
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Free Webinar: Linux Backup and Recovery
Most companies incorporate backup procedures for critical data, which can be restored quickly if a loss occurs. However, fewer companies are prepared for catastrophic system failures, in which they lose all data, the entire operating system, applications, settings, patches and more, reducing their system(s) to “bare metal.” After all, before data can be restored to a system, there must be a system to restore it to.
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