CMG Canada Conference Toronto April th Anthony G. Mungal Senior Consultant

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1 CMG Canada Conference Toronto April th 2015 Anthony G. Mungal Senior Consultant 1

2 Abstract The rapid pace of technology continues to impact every element of the IT Infrastructure in potentially disruptive cycles consistent with the useful lifetimes of said technology. IT Infrastructure exists to satisfy, in a cost optimized manner, the evolving business needs of the Enterprise and in so doing must conform to the short term (tactical) and much longer term (strategic) initiatives set forth. This session looks at the various components of the IT Infrastructure and assesses the impact of current and evolving technologies on each. Hardware and software trends are also considered, especially as they enable enhanced capabilities and simplify management. The evolution from traditional to converged, to hyper-converged, to hybrid Infrastructures incorporating public clouds are carefully examined along with cost parameters which render them attractive. 2

3 About the Author Anthony Mungal is a highly motivated IT professional with over thirty five years of expertise in Large Systems/Enterprise Infrastructure and Architecture areas such as computing, storage, networking, systems management, performance and capacity planning. He has worked with a very large and diverse set of customers spanning financial, retail, utilities, health care, government, entertainment and other sectors, both domestically and internationally. His core competencies include: o Enterprise Infrastructures and Architectures o Storage Operations/Migrations. o Data Center Setup/Migration/Relocation. o System Performance & Tuning (processor, storage, network) o Capacity Planning & Modeling. o Excellent written and oral skills. 3

4 Agenda Traditional Infrastructure and the Growth problem Quantifying growth (unpredictable finite) The rise of Virtualization Converged Infrastructures Hyper-converged Infrastructures Examples Final Thoughts 4

5 IT Infrastructure - Evolution PCs/servers Cloud Minis/Client server Mainframe Technology cycle shortened to 18 to 24 months Usage trends cycle is erratic at about 5 to 10 years and constantly decreasing. 5

6 Why do Infrastructure & Architecture planning? Business Drivers Application intensity continues to increase Data storage (CAGR > 60%) CPU (CAGR > 20%) Network (8Gb going to 16Gb, and higher) Systems Management Business is non-stop (24 x 7 x 365) and highly mobile Gain competitive advantage (1 st to market) Technology and Hardware A robust and resilient infrastructure will facilitate the adoption and integration of new technology pieces brought about by continual change while all the time delivering highly dynamic and seamless access to IT services and resources. Chip technology driven by unprecedented levels of processing Areal densities increasing while form factors are decreasing Proliferation of SSDs ultra high performance Memory rich, multi-tiered, multi-core, multi-threaded processors and diverse workloads. Promise of: performance, improved throughput, lower cost emerging technologies on a constantly shortening cycle time Agility Ability to change quickly Adaptation 6

7 IT Infrastructure Design Budget Assumptions Design Other Factors Other factors - the impact of: Long term vision of SDDC Network Virtualization Storage Virtualization DEVOPS Converged Infrastructure Hyper-converged Infrastructure Technology cycles Business challenges Orthogonal workloads,e.g. Big Data Constraints Requirements 7

8 DEVOPS Driving Factors Agile development process Cross functional collaboration analysis, design, development and QA Business need for accelerated rate of production releases. Wide availability of virtualized and cloud infrastructure internally and externally. Increased data center automation. Increased configuration tools. [Ref: ] 8

9 Traditional Infrastructure - Enterprise Business Applications Systems Management Security Performance Compute Availability Scalability Capacity Planning Key Management: & Role Based Security Data Encryption Workload Management: Response Time Throughput Failover/Continuity: > Distributed Sysplex Capacity: Engines Memory Channels Reporting Security Performance Network Availability Scalability System Configuration Zoning Log In QoS ISL: Load Balancing Replication Remapping Capacity: Engines Memory Channels Policy based resource allocation Single pane of glass management Key Management & Role Based Security: Security Tape & Drive Encryptio n Performance Connectivity: Cache Auto Tiering Partitioning QoS Storage Availability Failover/Continuity: Data Replication Backup & Recovery Scalability Capacity: Disk or Tape Data Dedupe Thin Provisioning 9

10 A Single Infrastructure fulfilled all needs s/360 announced on 4/7/64. s/370 announced on 6/30/70 s/390 announced 9/5/90. The above evolutionary infrastructure extended with XA, ESA and system z is still functional today. CONFIDENTIAL Copyright 2015 A. G. Mungal. All rights reserved.fully functional. 10

11 Today s Main Enterprise and Cloud compute Technologies Cisco UCS B460 M4 Blade Server IBM z13 Enterprise Server Also, many other x86 based architectures from Dell, HP, and more. IBM Power 7/8 11

12 Domain Capabilities 5 Main Areas Performance E.g. Leverage multi-level processor caching, network QoS, automated storage tiering. Availability E.g. Business continuity versus recovery (workloads and data) Scalability E.g. Leverage horizontal and vertical scaling across the stack Systems Management E.g. Simplification of Complex Systems and Workload Management Capabilities across the stack Security E.g. Comprehensive in flight/at rest data protection, role based functions and key management 12

13 Advantages / Disadvantages Advantages Easy to scale any domain to meet current needs. Domain scalability was asymmetric with respect to the other domains. Future needs was accommodated subject to certain constraints. This gave rise to the piecewise distributed model aka stove-piped model Disadvantages Forecasting required usage data and specialized training (Capacity Planning expertise) on each domain. Infrastructure Capacity and performance obeyed the well-understood step function. Forecasting had to stay ahead of saturation. Cost was incurred well ahead of target need. Overbuying. High impact to CapEX and OpEx. 13

14 Traditional Infrastructure stovepiped, piece-wise distributed Business Application Business Application Business Application Business Application... Business Application COMPUTE COMPUTE COMPUTE COMPUTE... COMPUTE NETWORK NETWORK NETWORK NETWORK... NETWORK STORAGE STORAGE STORAGE STORAGE... STORAGE 14

15 Advantages / Disadvantages Advantages Shorter procurement cycle. Cheaper (CapEX and OpEx) Dedicated use platforms. Departmental/LOB ownership The stage was now set for mass virtualization the decoupling of Infrastructure services from the physical assets on which they reside. Disadvantages Little or no forecasting, beyond initial requirement. Infrastructure Capacity and Performance obeyed a homogeneous step function. Saturation (the pain experience) dictated upgrades. Cost was lowered, but still incurred well ahead of target need. Overbuying. Noticeable impact to CapEX, but lowered OpEx. 15

16 Virtualization Mainframe Processor Virtualization Amdahl s Multiple Domain facility (MDF) on the 580 series processors in IBM s PR/SM on the 3090 series processors in Power Series Virtualization (PowerVM) EAL4+ certified virtualization of CPU, memory and networking for IBM AIX, IBM i and Linux. x86 Architecture Virtualization VMware in (EMC purchased VMware in 2004) Provisioning of: vcpu, vram, and vnic via software (hypervisor) Storage Virtualization virtualization techniques applied to different storage functions e.g. physical storage, RAID groups, logical unit numbers (LUNs), LUN subdivisions, storage zones, logical volumes, and more. Network Virtualization Reproduces the complete L2-L7 virtual network topology (logical switches, logical routers L2-L3, logical load balancers, logical firewalls L4-L7, and more) 2 main players VMware with NSX; Cisco with ACI 16

17 Server and Network Virtualization Ref: Helund, B., What is Network Virtualization?, 2013, 17

18 Converged Infrastructures Convergence is about optimally combining server, storage, networking and management facilities to achieve interoperability using common resource pools, common platform and unified management tools, policies and processes. What the pundits say: IDC convergence is THE next IT cycle will drive IT purchasing decisions for the next 10 years. Gartner - by 2015, one third of all servers shipped will be as a converged infrastructure. Forrester - study indicated that 28% planned on implementing converged infrastructure in the next 12 months, and another 28% in a year or more. 18

19 Converged Infrastructures Customer needs: Easier Faster Seamless Preserve current investment (no rip-replace) Cloud enablement Potential benefits: Efficiency Innovation Agility Lower costs (acquisition and operational) Reduced complexity single pane of glass management 19

20 Converged Infrastructures - Examples VCE Vblock, Vxblock Cisco - Unified Computing System (UCS) HP HP Converged system NetApp Flexpod Dell - vstart and Active System 800 models Nutanix NX series Simplivity Omnicube IBM Pureflex VMware EVO:RAIL 20

21 Hyper-Converged Infrastructures A single software stack that assimilates the functionality of multiple traditional IT infrastructure elements into a single shared x86 resource pool. 1 Important continuation and maturation of convergence. Main players today: Nutanix NX series Simplivity Omnicube Scale Computing VMware EVO:RAIL?? 1 21

22 Hyper-Converged Infrastructures The Building Block Cloud enablement Integration of compute, network, storage, server virtualization, primary storage data deduplication, compression, WAN optimization, storage virtualization and data protection. Full pooling and sharing of all resources. Performance through built in auto-tiering, caching and capacity optimization. No separate flash arrays etc. Scale out to web scale locally and globally as a single system image. Manageable from one or more locations. Automation to hasten deployment and management times VM centricity full visibility and manageability at the VM level. 22

23 Hyper-Converged Infrastructures The Building Block cont d Policy-based data protection and resource allocation at a VM level. Built-in cloud gateway, allowing the cloud to become a genuine, integrated tier for storage or compute, or both. 23

24 Simplivity Omnicube Example Hyperconvergence A single software stack that assimilates the functionality of multiple traditional IT infrastructure elements into a single shared x86 resource pool. Data Virtualization Platform Performs inline data deduplication, compression and optimization on all data at inception. Data granularity of 4-8 KB. Uses the OmniStack Accelerator Card for enterprise class performance. specialized PCIe card - offloads compute intensive tasks, enabling OmniCube to deliver Global Federated Management using vcenter One user can manage the entire global infrastructure through one, simple interface. An intelligent network of collaborative systems that manages billions of fine grained data elements. Enabling data movement and sharing across the globe, as well as global VM centric management. 24

25 OmniCube Family of Models [Ref: ] 25

26 Nutanix NX Family Ref: 26

27 Final Thoughts CapEx and OpEx will continue to drive adoption. Growth rates: CapEx steadily decreasing; OpEx steadily increasing Converged and Hyper-converged Infrastructures May be all that is needed in many SMB environments. Enterprise environments will incorporate it in increasing percentages leading to very robust hybrid infrastructures Asymmetric resource consumption is a natural consequence of access skew. Somewhat problematic for converged and hyper-converged infrastructures, given the building block nature of the architectures. Partially solvable through overprovisioning and clever use of virtualization. Entering into the era of moving from cloud adoption to cloud acceleration. Mobile/ubiquituous computing re-defining infrastructure capabilities Orthogonal workloads (e.g. big data) requirement of high density computing and ultra-dense data storage. Massive scaleability: nx vertically; n 2 x horizontally (generalized n k x, k, k > 1, k R.) Back to the Future? At what point does hyper-converged infrastructures converge to what was known as the mainframe the old is new again? 27

28 Final Thoughts continued Capacity Planning (CP) is not dead! it is being re-written CP for n k x is drastically different from nx Regression to time-series to fractal analysis. The probability of need (acquisition probability) of any infrastructure component becomes a joint function as follows: f (diminishing value of long historical data) X (emphasized value of most recent data) Infrastructure Management tools (e.g. vsphere, vcentreops, etc) Trending. Capacity modeling. Performance. engineered in taken for granted? High dependence on Infrastructure Management tools. Single pane of glass - highly summarized. Pro-active increased use of predictive analytics. Operationally - lower skill set requirement. Diagnostically experts only requirement. Still NO free lunch! 28

29 29

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