How To Improve The Fit For Purpose Model At Nationwide It

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1 Nationwide IT Nationwide s Private Cloud Journey Brian Callaghan, AVP IT Engineering -Nationwide Insurance

2 Introduction For over eight years Nationwide has been striving to improve our virtualization and automation capabilities. Like most other firms we realized the initial cost benefits of consolidating underutilized platforms through virtualization (savings on software, hardware, facilities and labor), but we aspired to improve our model even more. The question we sought out to answer: Are we leveraging our platforms in the most cost effective way and can virtualized Linux for System z be price/performance competitive vs. virtualized x86 for our Java application workload? What we found out: We determined that for our environment and our local factors, Linux for System z was price / performance competitive and that we benefited from having multiple platforms. What we created in the process: an agile continuous improvement model for determining the most appropriate platform to run our various workloads (fit for purpose). Unanticipated benefit: the relative ease at which we can move applications between platforms and the number of human steps taken out of our processes. Nationwide IT 2

3 Our journey has enabled an evolution in our capabilities Adoption of Virtualization Significantly better TCO Faster Linux provisioning Improved Disaster Recovery Evolving Capability Fit for Purpose, Private Cloud Capacity management Availability improvements Opportunities at the top of the stack WebSphere automation and standardization Platform optimization Fit for purpose Nationwide IT 3

4 The process to answer our question Conduct fit for purpose method workshop Framework for benchmark, application profiles and weighting factors for TCO. Benchmark Nationwide applications for platform comparisons Benchmark results by profile and platform. Development of total cost of ownership models Technical and financial data. Analysis of data and development of decision tree Nationwide IT 4

5 What we learned from our fit for purpose work We selected four specific workload types (patterns) that exemplified traditional application behaviors at Nationwide. Our Java application portfolio is roughly an 80/20 mix of two different patterns The empirical performance data from the study confirmed that the applications can perform well on both platforms with the 80% pattern offered better price performance on Linux for System z and the 20% pattern better price performance on x86 The IBM middleware automation and tooling was a critical enabler of application mobility Nationwide IT 5

6 Insights gained from TCO Model development phase We examined roughly 30 unit cost variables, which we categorized into 4 categories. This was the most comprehensive examination we have done. Hardware acquisition and maintenance costs for hardware assets Software licensing, subscription and support costs for full software stack Support - personnel to manage environment Datacenter facilities costs Software cost is by far the largest factor in the TCO model. Software licensing models are being challenged by new technology advances and our attempts to bundle and simplify the services we provide. The price performance benefits of platforms are influenced by product release cycles. The vendors are typically out of phase with one another. Nationwide IT 6

7 SHOWCASE FIT FOR PURPOSE 4 PHASE APPROACH DESCRIPTIONS The fit for purpose objective was to create a process based approach for determining the most appropriate platform to run the various Java workloads at Nationwide. Four distinct phases of the journey emerged. Conduct fit for purpose method workshop This phase focused on designing the Nationwide fit for purpose process. This included determining which workload types to examine, evaluating how applications fit into the four defined workload types, identifying important application and operational characteristics, rating these characteristics and integrating total cost of ownership into the process. Benchmarking Nationwide applications for platform comparisons This phase focused on the Nationwide application portfolio and choosing a representative set of applications that fit into the four workload types. The selected applications were then performance benchmarked to collect the performance and operational data points selected in the method workshop. The benchmark tests were run on IBM System z with z/vm and Intel x86 with VMware. Development of total cost of ownership models This phase focused on establishing a consistent total cost of ownership model that takes into consideration unit level costing of operational and capital expenses required to establish and maintain a computing environment for running the x86 and System z platforms. Analysis of data and development of decision tree This phase focused on combining benchmark data, the total cost of ownership model and the key operational characteristics to determine the best price/ performance model for each of the examined workload types on the chosen platforms. The development of analytic data reporting and an application platform placement decision tree are the final outputs for this phase and the fit for purpose journey. Nationwide IT 7

8 Work Stream 2 Fit For Purpose Outcome The project team selected four specific workload types (patterns) that exemplified traditional application behaviors at Nationwide. These patterns are based on IBM research and included the following: Type A: Data Intensive - Workload is IO intensive and has a high degree of thread interaction. (e.g.: High volume OLTP databases) Type B: Workload is highly threaded, moderate thread interaction and moderate to high CPU demand. (e.g.: large JEE applications). Type C: Workload is discrete applications lower demand for IO and CPU, fewer thread interaction. (e.g.: web deployable unit) Type D: Analytics - Workload has low IO and high sustained CPU demand. (e.g.: Grid Computing). Java application portfolio is roughly an 80/20 mix of Type C and Type B workloads. Nationwide had no significant Java applications in use for Type A or D workloads. Middleware tooling enabled Java workload mobility between z Series and x86 platforms. The empirical performance data from the study confirmed that Type B and Type C applications can run on both platforms, with a Type B preference for x86 and Type C preference for Linux for System z. Nationwide IT 8

9 Unit Cost Variables Below is a list of each of the unit cost items utilized in our TCO model. Host Equipment Cost Blade and IFL Costs Number of Hosts Number of Cores Memory Costs Amount of Memory PVU Counts Cost of WebSphere Cost of Operating System Cost of Hypervisors Cost of WebSphere Maintenance Cost of Operating System Maintenance Cost of Hypervisor Maintenance Fiber Channel Port Rate Number of Fiber Channels DASD Rate DASD Amount Power Consumption Cost of Power Network Ports Number of Network Ports FICON Rate Number of FICON Ports Host Admin Rate Host FTEs OS Admin Rate OS Admin FTE WAS Admin Rate WAS Admin FTE Nationwide IT 9

10 Work Stream 3 Middleware tools The Middleware tools stream enabled capabilities for rapid environment capture and recreation and further optimized infrastructure standards. WebSphere Virtual Enterprise Hypervisors IBM Workload Deployer Middleware Tools DataPower XC10 Ra5onal Automa5on Framework IBM Workload Deployer Automates provisioning and de- provisioning of virtual servers Ra1onal Automa1on Framework Manages and automates middleware applica7on configura7ons WebSphere Virtual Enterprise Dynamically scales Middleware components; improves manageability and availability Hypervisors Exis7ng Na7onwide z/vm and VMware DataPower XC10 Session database; services response cache Nationwide IT 10

11 What Nationwide Built We will continue this talk with a overview of what the environment looked like before and what the new environment now looks like We will talk more about the hardware and software used Look at sample configurations of the environment Conclusion Nationwide IT 11

12 Before / After Technology Stack Current State Java Hosting Pres Application Data Pres Application Data Web JVM Web Dynamic JVM IWD IHS WAS Sess DB IHS WAS WVE XC10 DB RAF Linux Linux for System Intel z Linux Linux for System z Intel Linux Linux Pool of Linux Servers Pooled Virtualized Hardware Linux for System z (80%) VMWare (20%) Linux Infrastructure is statically defined (isolated to a single platform). Session DB s not implemented consistently Built in silos with little automation SME s heavily required by technology and app/environment during provisioning Configuration updated in place manually Sub-optimized used of physical tier Infrastructure is dynamic and follows Fit for Purpose methodology Session DB s consistently implemented with XC10 Heavily automated with integrated technology stacks Less SME effort during provisioning Configuration for infrastructure is treated as code and is stored in a repository and can be recreated easily Optimized use of physical tier

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16 Conclusions The advancements in automation and tooling allows us to better utilize our highly skilled and experienced resources with technical subject matter expertise. Our fit-for-purpose process has enabled us to better understand our workloads and the price / performance characteristics of our existing platforms. This process has allowed us to make better financial decisions on our technology investments. The application mobility capabilities built on the IBM technology has significantly reduced the risk of improperly placing applications on a less than optimal platform. Nationwide IT 16

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