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ONLINE: Southwest CMG – Performance & Cost Optimization
April 20, 2020 @ 10:00 am - 2:00 pm CDT
Join us for a virtual meeting of the Southwest CMG. We have three presentations that look at system performance and cost optimization from different application perspectives.
Check out the Recordings!
Note: To view the video you must have a CMG membership. Sign up today! Click here to join for as low as $20/month.
#1 – VPN is the New Toilet Paper – Leveraging Helix Optimize to Understand the Impact of Employees Working from Home on Businesses due to COVID-19
April 20 @ 10:00 am – 11:00 am CDT
Speaker: Karen Hughes, Sr. Principle Software Consultant, BMC Software
Abstract: COVID-19 has completely disrupted the location of where employees work. Organizations that used to require employees to come to the office now are forced to have them work remotely, and they have little experience in understanding the impact it will have on their networks. Other organizations have experience with some employees working from home, but not 100% of their workforce. In this session we will discuss how to manage, plan, and validate your network with Helix Optimize. It will show 4 actual use cases that BMC IT leveraged in order to properly plan for the increase in remote workers, understand the impact on their network, and model business continuity scenarios. Learn what data and metrics are needed to be collected, where to get the from, and how to analyze them.
About the Speaker: Karen Hughes has worked with the BMC TrueSight Capacity Optimization product line since 1996. During that time Karen has had many roles including QA, development, marketing and solution engineering. Prior to BMC, Karen worked for AGFA, a division of the Bayer Corporation as a software developer, (utilizing her bachelor’s degree in Computer Science) and focused her efforts on coding automation tools for their engineering department. Karen has tremendous domain knowledge, is a subject matter expert on Capacity Planning and is certified by ITIL as an ITIL Capacity Management Practitioner.
#2 – Save MSUs and Reduce Run-Times for Analytics and MXG Reporting
April 20 @ 11:00 am – 12:00 pm CDT
Speaker: Paul Massengill, Systems Engineer, Mainframe Analytics Specialist, Luminex Software
Abstract: The mainframe team of a Fortune 500 Transportation Provider was tasked with conflicting goals: (1) increase the frequency and variety of reporting and analytics, and (2) avoid an upgrade of their already overtaxed mainframe. Learn how you can apply their success with off-host processing to your operations for faster analytics and MXG reporting, all while retaining mainframe control of scheduling, execution and security.
About the Speaker: Paul Massengill has spent most of this 30-year IT career in Solutions Architecture and Data Analytics for Mainframe and Open Systems. He spent his early years in IT working for top tier banks in Storage Administration, Capacity Planning and Performance Tuning. For the last two decades, Paul has specialized in using Data Analytics coupled with customer business forecasts to bring Enterprise solutions to many TOP 100 customers. He provided these solutions while working for companies such as Wachovia, Bank of America, StorageTek, SUN, Oracle, Hitachi and currently Luminex Software.
#3 – How to Apply Modeling and Optimization to Select the Appropriate Cloud Platform
April 20 @ 12:00 pm – 1:00 pm CDT
Speaker: Dr. Boris Zibitsker, CEO of BEZNext
Abstract: Organizations want to take advantage of the flexibility and scalability of Cloud platforms. By migrating to the Cloud, they hope to develop and implement new applications faster with lower cost. Amazon AWS, Microsoft Azure, Google, IBM, Oracle and others Cloud providers support different DBMS like Snowflake, Redshift, Teradata Vantage, and others. These platforms have different architecture, mechanism of allocation and management of resources, and sophistication of DBMS optimizers which affect performance, scalability and cost. As a result, the response time, CPU Service Time and the number of I/Os for the same query, accessing the similar table in the Cloud could be significantly different than On Prem.
In order to select the appropriate Cloud platform, we use modeling and optimization.
- First, we perform a Workload Characterization for On Prem Data Warehouse. Each Data Warehouse workload represents a specific line of business and includes activity of many users generating concurrently simple and complex queries accessing data from different tables. Each workload has different demand for resources and different Response Time and Throughput Service Level Goals.
- Secondly, we must collect measurement data for standard TPC-DS benchmark tests performed in AWS Vantage, Redshift and Snowflake Cloud platform for different sizes of the data sets and different number of concurrent users.
- During third step we use the results of the workload characterization and measurement data collected during the benchmark to modify BEZNext On Prem Closed Queueing model to model individual Clouds.
- And finally, during the fourth step we use the Model to take into consideration differences in concurrency, priorities and resource allocation to different workloads. BEZNext Capacity Planning optimization algorithms incorporate Graduate search mechanism to find the AWS instance type and minimum number of instances which will be required to meet SLGs for each of the workloads. Publicly available information about the cost of the different AWS instances is used to predict the cost of supporting workloads in the Cloud month by month during next 12 months.
About the Speaker: Dr. Boris Zibitsker is a CEO of BEZNext. His focus is on the development of performance assurance, performance engineering, dynamic performance management and long-term capacity planning software tools for big data, data warehouse and cloud applications. He is a member of SPEC Big Data Research Group. Boris consults with many Fortune 500 companies, and he manages Capstone projects for graduate students in MS in Analytics at University of Chicago. Boris a Honorable Doctor of BGUIR and during last 5 years he was a co-chairman of Big Data Advanced Analytics Conference.
April 20 @ 1:00 pm – 2:00 pm CDT
Speaker: Kareem Mroue, HelpSystems
Abstract: The medical device manufacturing field is one of high risk and high demand. Manufacturers often experience peaks and valleys in the demand for their products and therefore are required to remain flexible in their operations to accommodate these fluctuations. Indeed, the situation that we are in right now show that these peaks can be massive and unexpected. Additionally, these companies are highly averse to risk. Producing defective products will not only cost a company the confidence and loyalty of medical professionals in the field but could also initiate costly regulatory infractions and in some case can even cost the lives of patients. For these reasons it is imperative that a medical device manufacturer possess the tools and abilities necessary to educate themselves regarding their needs in personnel, materials and equipment for various levels of demand.
Our presentation aims to show a case study from last year, interestingly many months before the current crisis, for creating a plan regarding the management of the technical equipment associated with highly risk averse manufacturing. The case study will use Capacity Management methodologies (including tools) within an enterprise environment to aid in the what-if planning of on-premise equipment augmentations as well as the utilization of public-cloud platform elasticity. The desired outcome and deliverables being an understanding of the investment necessary to accommodate various peaks in demand, as well as a method in providing the needed documentation to execute such an investment within an enterprise environment.