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The Future of Cloud Computing The Next Ten Years. 4. Dr. Rao Mikkilineni , Kawa Objects, Inc. Vijay Sarathy, Kawa Objects Inc. Kumar Malavalli , Kawa Objects, Inc. Agenda. Lessons from the Past Waterwheel to Power Grid Evolution of Telecom Networks The Present
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The Future of Cloud Computing The Next Ten Years 4 Dr. RaoMikkilineni, Kawa Objects, Inc. Vijay Sarathy, Kawa Objects Inc. Kumar Malavalli, Kawa Objects, Inc.
Agenda • Lessons from the Past • Waterwheel to Power Grid • Evolution of Telecom Networks • The Present • Why the present is not sustainable • What must happen for progress • The Future • Clouds and On-Demand Computing • What it means for innovation
Lessons from the Past Early Power Generation -The Waterwheel The Modern Power Grid The Telecom Network
Lessons from the Past Lesson: Enterprises can not afford 2-5% of revenue spending on IT
What this means for Industry • Commoditization of Computing is going to happen • Disproportionate amount spent on technology rather than business • Existing Management Complexity is not Sustainable • Current Large Technology Incumbents will have to evolve • Universal Access = GDP growth
Today’s Business Drivers for Cloud Computing • Unexpected Demands created by Web 2.0 Consumer and Internet Applications • Explosion of social networking has created wildly fluctuating demand straining the ability of IT infrastructure to scale Web 2.0 Applications • Explosion of Digitized Records and Content • Where we store everything ? • How do we retrieve it reliably ? • How do we secure it ? • How do we delete it ? Electronic Health Records E-mailRecords Digital Records • Ever escalating cost of improving ROI and lowering TCO in the Datacenter • SAN, NAS, Virtualization • HA/DR, Performance Optimization, • Security 1 2 3 Rising Datacenter complexity Rising TCO / Lower ROI
The Cloud must help reset complexity; TCO is getting out of Control Actual TCO Expected TCO Virtualization Bandwidth Inversion Cloud IT TCO ManagementComplexity Server-CentricComputing ResourceConsolidation 2 SAN Features like Windowless Backup 3 1 Self-Contained Shared Storage Cloud IT Virtualized Datacenter 1970 2000 2005 2010 Time ?
Evolution Of Backup and Disaster Recovery RPO Server-CentricComputing SharedStorage Live Migration of Servers Cloud IT RPO Virtualization 2 3 1 Days/Weeks Hours What Next? Minutes/ Seconds 1970 2000 2005 2010 Time ?
Cloud Computing as it is defined today… A XaaS stack… …enables Economies of Scale Compute Resources Compute Resources Web-based Services Software-as-a-Service Application-Components-as-a-Service End-to-endDynamic Resourcing …On-Demand Computing Software-Platform-as-a-Service ..provides a standard interface Virtual-Infrastructure-as-a-Service Physical-Infrastructure-as-a-Service Cloud API What Is Lacking? Server Storage Network
The State of Clouds Today and What is Missing To establish Trust in Cloud Computing, this has to be addressed end-to-end; not just for servers Massive Scalable Reliable For servers Available End-to-end PerformanceOptimization The Cloud For servers End-to-endDynamic Resourcing End-to-end Security Service Mediation No Management Complexity Global Interoperability
Existing Infrastructure Silos and Multiple Inefficiencies Application Specific Administration Application Specific Availability Application Specific Storage Management Application Specific Performance Application Specific Security Server IT Network IT Storage IT Server Virtualization Network Virtualization Storage Virtualization Server IP Networks DAS IP Networks COTSStorage ServerAdministration NetworkAdministration StorageAdministration Cache Management Network Management Storage Management NAS System Management SAN Cache Management Availability Availability Availability SAN Networks Performance Management Performance VolumeManagement Performance Performance VolumeManagement Security Volume Management Security PerformanceManagement PerformanceManagement Security TieredConfiguration
Vision For a Next Generation Cloud based on Telecom History Dynamic Composition & Management of distributed Logical Resources Service Users Service Developers Distributed Service Creation Platform Distributed Service Delivery Platform Services Fabric Distributed Service Assurance Platform Management Fabric Service Operators Distributed Service Mediation (Latency Based Connection FCAPS) Virtual Computing QOS &Dynamic FCAPS Management Network QOS & Dynamic FCAPS Management Distributed Storage QOS & Dynamic FCAPS Management Server Resources COTS Storage IP Distributed Hypervisors Storage Virtualization Network Virtualization Server Resources Fiber Channel COTS Storage Server Resources iSCSI COTS Storage COTS Storage Server Resources Multi-CPU & Multi-Core Servers Multi-Latency Networks Multi-Latency Storage Elements Infiniband Infrastructure Fabric
The IT struggle today is about… • IT Management • SANs • Proprietary HW with advanced features • Complexity • Human Latency End-to-end Visibility & Control Costs (Infrastructure, Management and Operations) • Clouds • Virtualization • Commodity HW • Simplicity ...balancing need for visibility & control with cloud scale & economics
Cloud Computing Predictions for the next 10 Years Co-existing Private & Public Clouds Expected TCO CPU / Memory Virtualization End-to-end Visibility Globally interoperable, massively scalable service assurance, creation, & delivery platforms Storage Dynamic Provisioning TCO End-to-end Control End-to-end Connection FCAPS Optimization 2 1 XaaSin the cloud CPU to Spindle Connection FCAPS Management Dynamic Storage capacity, Bandwidth and Throughput Tuning 3 Workflow / Service SLA No Application SLA Storage SLA CPU / Memory SLA 2009 2012 2015 2018 Time 4
Customer Quote “ I don’t care who provides my infrastructure even for my mission critical applications as long as I have visibility into the cloud and have control of my application response time, I/O, throughput, availability, latency, security …and I have the ability to adjust it based on my business priority and changing workloads “ - IT Business Alignment Manager at a Large Energy Company that is actively re-architecting their datacenter around clouds
App1 App 2 App 3 App 6 App 5 App 4 OS OS OS OS OS OS What does Enabling End-to-End Visibility Mean? Application-Centric Visibility Virtual Appliances Hypervisor Hypervisor Servers Server 1 Server 2 Network SAN NAS IP Storage Storage 1 Storage 2
1 4 2 3 What does Enabling End-to-End Control Mean? App B • Need to dynamically match Application/Business requirements to resources Every app has different resource needs AppA Latency Throughput Data Pipe IOPS ( IO operations/sec ) Resource Capacity
Business Profile RPO RTOBusiness Priority ………. ………. 1 1 2 3 1 3 2 3 2 Coexistence of Private & Public Clouds External At Customer Site Public Cloud 1 Services / Applications Application /Service Profile Console Server A Server C CPU CacheStorage IOPS ………. ………. ServerB ServerD KawaDIME Mediation & Control Public Cloud 2 PrivateCloud StorageA StorageC KawaDIME StorageB StorageD Kawa Storage Server E ServerF
Business Profile RPO RTO………. ………. ………. ………. 1 1 3 3 2 2 1 3 2 Coexistence of Private & Public Clouds External At Customer Site Public Cloud 1 Services / Applications Application /Service Profile Console Server A Server C CPU CacheStorage IOPS ………. ………. ServerB ServerD KawaDIME Mediation & Control Public Cloud 2 PrivateCloud StorageA StorageC KawaDIME StorageB StorageD Kawa Storage Server E ServerF
Vision For a Next Generation Cloud based on Telecom History Service Developers Service Users Business Services Dial Tone Business Services Fabric Distributed Service Creation Platform Distributed Service Delivery Platform Service Operators Distributed Service Assurance Platform Management Services Fabric Distributed Service Mediation (Latency Based Connection FCAPS) Infrastructure Services Fabric Management Services Dial Tone Virtual Computing QOS &Dynamic FCAPS Management Network QOS & Dynamic FCAPS Management Distributed Storage QOS & Dynamic FCAPS Management Computing Services Dial Tone Distributed Hypervisors Network Virtualization Storage Virtualization
The Need for Open Standards, Global interoperability and Massive Scaling Power Distribution Grids Standards/Regulatory Bodies ANSI IEEE ASME FERC Scale: Billions of consumers Telecom Networks Standards Body ITU Scale: Billions of users Internet Standards Body IETF Scale: Billions of devices Standards Body Cloud Computing ??? Applications Scale: Trillions of services
Thank You!{ Questions } 4 rao@kawaobjects.comvijay@kawaobjects.com