Mainframe Performance Optimization Solutions

Your mainframe systems are being asked to do more every year. Part of that is due to business growth in a busy economic environment, which continually drives up operations costs. But it doesn’t stop there; the introduction of mobile has made a significant contribution as well – easier access breeds increased transaction workloads.

DataKinetics mainframe performance optimization can be applied quickly, and can help you to manage those ever-increasing workloads, no matter what the cause. Traditional performance improvement techniques like tuning or migration are highly risky, ineffective or very costly. DataKinetics mainframe performance optimization solutions are very low-risk, low-complexity and highly effective.

When applied where needed, you will be able to realize significant performance improvements without having to invest heavily on infrastructure change.

We’ve helped 20% of the Fortune 50 with improving mainframe performance, and we can help you, too.

Mainframe Performance Improvement

The mainframe is widely regarded as the best platform on the planet for running large-scale transaction processing because that is what it was designed for. No other platform can compete with the throughput performance of the mainframe. But workloads are increasing year-by-year, and the mainframe needs to keep pace.

There are several ways to improve mainframe performance – the most popular being a systems upgrade – meaning upgrade to a newer model mainframe (for example, from a zEnterprise 196 to a z14 mainframe system), or adding processors and memory to an existing system. These can be costly solutions, but frankly need to be done from time to time in a growing business environment.  But there are techniques that can be used to augment the upgrade cycle, and to reduce the frequency of upgrades – resulting in improved performance at a lower cost.

Increased resource demand necessitating upgrades

Are there really techniques that improve the performance of a mainframe processor or its memory or buses? No. However, by optimizing applications, they can use far less system resources (I/O and CPU), allowing them to run faster, and potentially present a smaller impact on operational cost. This virtually improves the performance of the application. And by optimizing several applications (even in several different ways), there can be a significant and measurable system-wide performance improvement. Similarly, if several database applications are optimized, there will be an apparent (and measurable) database performance improvement – even though the database has not been changed in any way.

High-performance in-memory technology

In-memory technology augments your DBMS and its buffering facilities.  The reference data that is used most often by your applications—a very small amount of data—is copied from the DBMS into high-performance in-memory tables, where it is accessed using a simple and tight API.  To get the most out of in-memory technology, you must identify applications that perform repetitive accesses (in the order of thousands) of read-only reference data – and you must identify that data.

The reason is that a small amount of data is responsible the most accesses to your databases, and if you can replace those calls with in-memory calls – eliminating I/O, CPU and database overhead – that can make a significant difference in overall performance of your mainframe system.

You may think that buffering is enough in-memory technology, but you can obtain a far higher performance benefit from high-performance in-memory technology. And the key to that is the difference in code path between this technology and your database buffers. This image shows the difference – a typical DBMS call to buffered data consumes from 10,000 to 100,000 machine cycles, whereas a call to data contained in a high-performance in-memory table consumes about 400 machine cycles.

Tests and comparisons have been completed by both independent third-party testing organizations, and DataKinetics customer IT organizations using tableBASE high-performance in-memory technology. In all cases, systems augmented using tableBASE allow data to be accessed by applications at a rate considerably superior to any other technique.  Actual customer systems (using Db2, Db2 buffers augmented by tableBASE) out-perform systems employing only Db2 + Db2 buffer optimization by a wide margin: up to 3000% faster.

Conclusion

These solutions are low-risk and budget-friendly; independently, they provide good performance improvement, but together they provide very significant improvements.  They can help to decrease the frequency of your system upgrades. They also provide short-term ROI immediately, coupled with long-term cost savings and improved efficiency, enabling improved overall IT cost control and strategic business flexibility. Just the prescription needed for the malady of ever-increasing IT costs.

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Controlled resource demand reducing need for upgrades