IBM AIX Dynamic System Optimizer

Improve performance for large database workloads


IT environments are becoming vastly more complex as technology changes and business demands evolve. Workloads continue to change to reflect new innovations in technology and the demand for integration creates more complex interdependencies. System core counts increase and with that, threading options multiply. Virtualization and workload mobility expand the complexities even more. Tuning such an environment for optimal performance is not trivial and traditional techniques are static in nature and require constant adjustment to reflect changes in workload characteristics. Meanwhile, user expectations have evolved to the point that everything “should just work”. All these pressures drive more focus on IT operations, raising expectations, and eventually, something has to give.

The IBM® AIX® Dynamic System Optimizer (DSO) is designed to solve this challenge. It leverages the performance of POWER7® processors and incorporates IBM experience and expertise to analyze your workloads and make adjustments to your partition settings. It does this dynamically and efficiently while the application is running and works to optimize performance, all without additional time or expertise from the systems administrator. All you have to do is turn it on. Then sit back and relax, knowing that the system is acting on your behalf, using IBM’s built-in expertise to constantly monitor and tune itself for improvements in performance.

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Next generation applications for big data and analytics and cognitive computing are providing unprecedented insights into opportunities, threats and efficiencies. IBM Power Systems is at the forefront of delivering solutions to gain faster insights from analyzing both structured information and unstructured big data. With the secure, flexible and open platform of IBM Power Systems plus solutions and software, organizations can outpace their competitors by delivering faster services, providing differentiated offerings and turning operational cost into investment opportunity.

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