© 2007 IBM Corporation | Workshop on Middleware for Next Gen Apps IBM TJ Watson Research Center Middleware Challenges for the Emerging Application Environments Giovanni Pacifici

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 2 Emerging Application Environments Pervasive connections Everyone is a web app developer N 2 World Multimodal applications Time critical events Business agility Real-Time Enterprise Software stack complexity becoming unmanageable Exploding number of apps Exploding Interdependence Heterogeneous environments Complexity

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 3 Enable Infrastructure Scalability, Simplification and Responsiveness Simplified Scalable Responsive Abstraction, Encapsulation, Virtualized Policy Driven Event Driven Autonomic Peer to Peer Plug and Play

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 4 Client L7 Switch AMFA Node 4 AMST Node 1 FAST Node 2 AMFA Node 3 Client L4 Switch Configuration Manager Centralized management model Specialized nodes Significant administrative overhead to grow or shrink a deployment Not scalable communication infrastructure Centralized and not scalable performance management controllers Current Scalability Limitations of Middleware and Multi-Tier Architectures

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 5 Node 5 Node 4 Node 3 Node 2 Node 1 Client AM FA ST AM FA AM ST AM ST Client L4 Switch no specialization of nodes decentralized model self-configurable infrastructure scalable architecture and management Middleware Self-Organization Approach to Scalability

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 6 Middleware Scalability: Challenges peer Key Functionalities –Request routing and load balancing –Self-organizing –Self-healing –Configuration data dissemination –Single-console system monitoring

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 7 Enable Infrastructure Scalability, Simplification and Responsiveness Simplified Scalable Responsive Abstraction, Encapsulation, Virtualized Policy Driven Event Driven Autonomic Peer to Peer Plug and Play

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 8 Application Architecture Complexity

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 9 How Do We Deal with This Mess? Virtualization: A technique for hiding the physical characteristics of computing resources from the way in which other systems, applications, or end users interact with those resources Dominant benefit of virtualization going forward –Abstraction of physical interfaces –Isolation

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 10 Reducing Complexity Through Virtualization Virtual resources and their configurations are decoupled and insulated from physical environment –Durability: limits the impact of physical changes –Pre-built virtual resources serve as the units of product distribution and provisioning Greater flexibility for allocating computing resources when needed and where needed –Deploy to Resource pools –Goal-based management Virtualization will be extended in scope from single server to aggregations of servers, storage, and network components. –From making partitioning technology a large system look like many – partitioning technology –Into make many small systems look like one from a management perspective Physical Environment Virtualization Virtual Environment Virtual Storage Virtual Application Server Virtual Networks Virtual Servers Fixed sizes, limited ports/slots, incompatible versions, rigid configurations, workloads bound to boxes, … SMP Servers Network Hardware Storage Servers and Storage Blades Decouples Virtual and Physical Environments

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 11 Virtualization is a Disruptive Technology Will transform data center management –Virtualization will extend beyond single systems to multi-system pools consisting of servers, network and storage, thus creating a new platform for integrated management and optimization of data center resources. Will transform desktop management –The Enterprise desktop will become a virtual machine image, standardized by the IT staff, secured by Enterprise policies, and streamable to hosted servers or client machines. Will transform software lifecycle management –Virtual appliances will become the unit of software distribution, licensing, maintenance, archival and service/support. Will drive new hardware, software and services technologies –Hardware support for virtualization, new programming models, new licensing models, new service & support models.

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 12 Virtual Software Appliances Virtual Appliances: pre-wired, pre-configured, production-ready software stack packaged inside virtual machine images designed to run under a VM hypervisor –Contains customization logic –May contain management agents –Associated meta-data manifest describing capabilities and requirements Marrying Appliances with Virtualization –Appliances: ease of use, purposed –Virtualization: fast replication, isolation, consolidation Change the way enterprise software is packaged and distributed, allowing for the development of self-contained application stacks that are easy to deploy and more reliable than traditional methods Change the way enterprise software is managed by including management intelligence into an appliance thereby making it easy to manage from the outside Emerging Technologies and Research Areas –Best of breed self-managing virtual appliances focusing on multi-image ones (end-to- end solution) –Develop tools to create, configure, provision and life-cycle manage virtual appliances –Develop techniques to manage virtual appliances at runtime to ensure high performance, availability, and electrical power conservation Appliances Middleware Operating System Image Resource Definition Middleware Operating System Image Resource Definition Integrated software stacks for easier production usage by partners and customers Preinstall and configured Common management enablement Common patterns Management functionality Virtualization Virtual Machine Virtual Appliance

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 13 Configuration and Lifecycle Management Developer VSA Engineer Deployer Datacenter Vendor Environment Customer Environment Application Structure Logical Topology Virtual Software Resources (VSR) Deployed, configured and running instance of VSA VSA Repository VSA Factory VSA Repository VSR Registry Register Internet Virtual Software Appliance (VSA) VSR VSA Deployment Manager VSA

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 14 Deployment and Activation of Virtual Appliances OS Middleware Application VSA Stack Configuration VSA OS Configuration OS Middleware Application VSA Stack Configuration VSA OS Configuration Deployment Configuration Parameters VM Hypervisor Physical Node CMDB VSA Topology validation and resolution logic VSA Model Capability Requirements VSA Model Capability Requirements Deployment Manager VSA Master Image VSA Clone

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 15 Drag and Drop VSAs Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 16 Drag and Drop Logical App Structure Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 17 Create LAS VRST Hosting Links Configuration of both containers auto updated based on requirements from LAS Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 18 Save Topology Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 19 Drag and Drop Physical Resources (VM Hosts) Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 20 Create VSRT VM Hosting Links Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 21 Deploy Topology to Physical Resources Model Driven Deployment: Adding Application to Middleware VSAs

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 22 Life Cycle Management of Virtual Appliances Two approaches: –update by replacement – a new version of appliance is created by vendor and shipped to customer –internal update – each VM is individually updated with patches of its software stack Update by replacement: –state management problem – new appliance does not include the state acquired by the old appliance customization parameters business application installs runtime data (caches, cookies, sessions, etc.) –downtime problem – old appliance must be brought down before new appliance may be started Internal update –difficult to generalize as different software stacks may require different match mechanisms Hybrid approaches possible

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 23 Classification – Flow Control - Routing On Demand Router AMST Node 2 FAST Node 3 Node 4 Node 1 Placement Executions Stock Trading Account Mngmt Financial Advice AM FAST FAST Runtime Management: from JVMs to Virtual Appliance Management Runtime management in existing middleware infrastructures –goal oriented resource management for web application environments Supports multi-tiered applications where each request uses multiple resources distributed Supports multiple applications deployed and replicated on different but overlapping subsets of machines Expand to manage Virtual Software Appliances and heterogeneous workloads –Manage both request/response workloads and long-running workloads like batch jobs on same pool –Leverage virtualization technology to enable anywhere placement of any workloads –Leverage new control knobs: migration, suspension, resource control –Make many small systems look like one from a management perspective 100% 0% 50% 55%* Utilized Servers Virtual Resource Pool

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 24 Anywhere Placement of Workloads Blade 1 Blade 2 Blade 3 Blade 4 Virtual Server Resource Repository Suspended VSRs VSR OS WAS App Job Scheduling and Placement Controller Web Request Flow Controller Job Submission and Monitoring DB Inst B J2EE App Lucene Povray Blast J2EE App DB Inst A DB Inst B DB Inst A Povray

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 25 Merging Job Scheduling and Placement Decides when, where, and how may instances of each container should run –Application characterized by memory and CPU requirements –Resource Requirements derived from performance goals Average response time goal for web applications Completion time goal for long running jobs –Server machine characterized by memory and CPU capacity Application placement algorithms –Bases on multi-dimensional bin packing techniques Constraints –Memory used by applications and their containers does not exceed a threshold on any server –CPU usage of applications and their containers does not exceed a threshold on any server –Constraints on the number of servers where an application should run, on the number of instances of an application that may be started on a node, etc. –Collocation restrictions and allocation restrictions Objectives –Fairness – equalize application utility whenever possible –Minimize the number of placement changes

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 26 powered off CPU-intensive workload(s) w/ allocation limited by hypervisor CPU usage (MHz) Power usage (watts) Hypervisor only 1 VM running (idle) 4 VMs running (idle) Power vs. Performance prototypical example Use Virtualization for Power Management Key observations: The majority of the power used by a blade is static (i.e., used before workload is started) Can be as much as ~80% An (over)simple calculation: 2 blades, each 40% busy: ~170 watts 1 blade, 80% busy: ~95 watts Savings = ~44% Power usage grows with workload intensity: linearly or as a convex function (when frequency scaling is implemented) Key energy-saving strategies: Workload consolidation and machine shut- down Workload reduction (via flow control) Workload distribution

IBM TJ Watson Research Center Where is Middleware Going © 2007 IBM Corporation 27 Summary Middleware infrastructures must address key challenges –Scalability no specialization Self-configuration –Complexity Achieve simplification using pre-configured software stacks inside virtual containers Model-driven tools to simplify deployment, provisioning and change management –Flexibility Enable seamless and anywhere placement of heterogeneous workloads through isolation, migration, suspension and resume techniques Make many small systems look like one from a management perspective Future Challenges –Manage software updates –Integrate security concerns –Physical and virtual configuration and connectivity –Software stack proliferation

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