With the popularity of network-attached storage for shared systems, IT shops are increasingly turning to them for SAS^® Grid implementations. Given the high I/O demand of SAS large block processing, how do you ensure good performance between network-attached SAS Grid nodes and storage? This paper discusses different types of network-attached implementations, what works, and what does not. It provides advice for bandwidth planning, types of network technology to use, and what has been practically successful in the field.

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Architects do not see a single architectural solution, such as SAS^® Grid Manager, satisfying the varied needs of users across the enterprise. Multi-tenant environments need to support data movement (such as ETL), analytic processing (such as forecasting and predictive modeling), and reporting, which can include everything from visual data discovery to standardized reporting. SAS^® users have a myriad of choices that might seem at odds with one another, such as in-database versus in-memory, or data warehouses (tightly structured schemes) versus data lakes and event stream processing. Whether fit for purpose or for potential, these choices force us as architects to modernize our thinking about the appropriateness of architecture, configuration, monitoring, and management. This paper discusses how SAS^® Grid Manager can accommodate the myriad use cases and the best practices used in large-scale, multi-tenant SAS environments.

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A United States Department of Defense agency with over USD 40 billion in sales and revenue, 25 thousand employees, and 5.3 million parts to source, partnered with SAS^® to turn their disparate PC-based analytic environment into a modern SAS^® Grid Computing server-based architecture. This presentation discusses the challenges of under-powered desktops, data sprawl, outdated software, difficult upgrades, and inefficient compute processing and the solution crafted to enable the agency to run as the Fortune 50 company that its balance sheet (and our nation's security) demand. In the modern architecture, rolling upgrades, high availability, centralized data set storage, and improved performance enable improved forecasting getting our troops the supplies they need, when and where they need them.

SAS^® Grid Manager, as well as other grid computing technologies, have a set of great capabilities that we, IT professionals, love to have in our systems. This technology increases high availability, allows parallel processing, facilitates increasing demand by scale out, and offers other features that make life better for those managing and using these environments. However, even when business users take advantage of these features, they are more concerned about the business part of the problem. Most of the time business groups hold the budgets and are key stakeholders for any SAS Grid Manager project. Therefore, it is crucial to demonstrate to business users how they will benefit from the new technologies, how the features will improve their daily operations, help them be more efficient and productive, and help them achieve better results. This paper guides you through a process to create a strong and persuasive business plan that translates the technology features from SAS Grid Manager to business benefits.

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Do you know how many different ways SAS^® Studio can run your programs with SAS^® Grid Manager? SAS Studio is the latest and coolest interface to the SAS^® software. As such, we want to use it in most situations, including sites that leverage SAS Grid Manager. Are you new to SAS and want to be guided by a modern GUI? SAS Studio is here to help you. Are you a code fanatic, who wants total control of how your program runs to harness the full power of SAS Grid Manager? Sure, SAS Studio is for you, too. This paper covers all the different SAS Studio editions. You can learn how to connect each of them to SAS Grid Manager and discover best practices for harnessing a high-performance SAS analytics environment, while avoiding potential pitfalls.

Organizations view Hadoop as a lower cost means to assemble their data in one location. Increasingly, the Hadoop environment also provides the processing horsepower to analyze the patterns contained in this data to create business value. SAS^® Grid Manager for Hadoop allows you to co-locate your SAS^® Analytics workload directly on your Hadoop cluster via an integration with the YARN and Oozie components of the Hadoop ecosystem. YARN allows Hadoop to become the operating system for your data-it is a tool that manages and mediates access to the shared pool of data, and manages and mediates the resources that are used to manipulate the pool. Learn the capabilities and benefits of SAS Grid Manager for Hadoop as well as some configuration tips. In addition, sample SAS Grid jobs are provided to illustrate different ways to access and analyze your Hadoop data with your SAS Grid jobs.

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Considering the fact that SAS^® Grid Manager is becoming more and more popular, it is important to fulfill the user's need for a successful migration to a SAS^® Grid environment. This paper focuses on key requirements and common issues for new SAS Grid users, especially if they are coming from a traditional environment. This paper describes a few common requirements like the need for a current working directory, the change of file system navigation in SAS^® Enterprise Guide^® with user-given location, getting job execution summary email, and so on. The GRIDWORK directory has been introduced in SAS Grid Manager, which is a bit different from the traditional SAS WORK location. This paper explains how you can use the GRIDWORK location in a more user-friendly way. Sometimes users experience data set size differences during grid migration. A few important reasons for data set size difference are demonstrated. We also demonstrate how to create new custom scripts as per business needs and how to incorporate them with SAS Grid Manager engine.

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Analyzing massive amounts of big data quickly to get at answers that increase agility--an organization's ability to sense change and respond--and drive time-sensitive business decisions is a competitive differentiator in today's market. Customers will gain from the deep understanding of storage architecture provided by EMC combined with the deep expertise in analytics provided by SAS. This session provides an overview of how your mixed analytics SAS^® workloads can be transformed on EMC XtremIO, DSSD, and Pivotal solutions. Whether you're working with one of the three primary SAS file systems or SAS^® Grid, performance and capacity scale linearly, significantly eliminate application latency, and remove the complexity of storage tuning from the equation. SAS and EMC have partnered to meet customer challenges and deliver a modern analytic architecture. This unified approach encompasses big data management, analytics discovery, and deployment via end-to-end solutions that solve your big data problems. Learn about best practices from fellow customers and how they deliver new levels of SAS business value.

Historically, administration of your SAS^® Grid Manager environment has required interaction with a number of disparate applications including Platform RTM for SAS, SAS^® Management Console, and command line utilities. With the third maintenance release of SAS^® 9.4, you can now use SAS^® Environment Manager for all monitoring and management of your SAS Grid. The new SAS Environment Manager interface gives you the ability to configure the Load Sharing Facility (LSF), manage and monitor high-availability applications, monitor overall SAS Grid health, define event-based alerts, and much, much more through a single, unified, web-based interface.

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This session is an in-depth review of SAS^® Grid performance on IBM Hardware. This review spans our environment's growth over the last four years and includes the latest upgrade to our environment from the first maintenance release of SAS^® 9.3 to the third maintenance release of SAS^® 9.4 (and doing a hardware refresh in the process).