Today, companies are increasingly utilizing analytics to discover new revenue and cost-saving opportunities. Many business professionals turn to SAS, a leader in business analytics software and service, to help them improve performance and make better decisions faster. Analytics are also being employed in risk management, fraud detection, life sciences, sports, and many more emerging markets. However, to maximize the value to the business, analytics solutions need to be deployed quickly and cost-effectively, while also providing the ability to readily scale without degrading performance. Of course, in today's demanding environments, where budgets are still shrinking and mandates to reduce carbon footprints are growing, the solution must deliver excellent hardware utilization, power efficiency, and return on investment.
To help solve some of these challenges, Red Hat and SAS have collaborated to recommend the best practices for configuring SAS 9 running on Red Hat Enterprise Linux. The scope of this document will cover Red Hat Enterprise Linux 6 and 7. Areas researched include the I/O subsystem, file system selection, and kernel tuning, both in bare metal and virtualized (KVM) environments. Additionally we now include Grid based configurations running with Red Hat Resilient Storage (GFS2 clusters).
The document has recently been updated to version 1.3. Some of the notables changes (not an exhaustive list):
- Virtual Memory
- Power Management