Migrating Scientific Applications from Grid and Cluster Computing into the Cloud Issues & Challenges



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Transcription:

Migrating Scientific Applications from Grid and Cluster Computing into the Cloud Issues & Challenges T S Mohan, PhD Principal Researcher, E&R ISGC2011-24 March 2011 2010 Infosys Technologies Limited

Overview Dilemma of Scientists Use existing Grid / Cluster Applications, Libraries and Infrastructures Start from Scratch & Develop Application for the Cloud Migrating Scientific Applications into the Cloud Challenges, Issues and Trends Our Methodology and Approach Relevant to certain classes of Scientific Applications Best Practices 2

What is the Difference? Grid or Cluster based Scientific Applications Vs Scientific applications leveraging existing Cloud Services Grid/Cluster Scientific Applications Use Existing Libraries Use Existing VOs and Infrastructure Stagnant Development Limited Not efficient Incompatible Non-Interoperable Cloudonomics OPEX vs CAPEX Governmental Funding.. Scientists & Core Competencies MindSet Change Models to use 3

Can Scientists used to Grids Leverage the Cloud Effectively? Cloudonomics Pay per use Lower Cost Barriers On Demand Resources Autoscaling CAPEX vs OPEX No CAPEX & Only OPEX. SLA driven operations Much Lower TCO Better Availability and Reliability Technology Infinite Elastic availability Compute/ Storage/ Bandwidth Automatic Usage Monitoring and Metering Jobs / Tasks Virtualized and Transparently Movable Integration and interoperability support for hybrid ops Transparently encapsulated & abstracted IT features. 4

Cloud Computing Software Development Lifecycle For Certain Kinds of Scientific Applications for the Cloud Requirements Customize Architect Monitor Cloud Oriented Development Life Cycle Design & Align Policies Deploy Assemble and implement Test, Verify, Validate At what level (Code) do we migrate? What kind of cloud do we migrate into? 5

What is Migration into the Cloud? Cloud - Integration / Adoption / Migration Migration : Code, Design, Architecture, Usage where is the Application before migration is the Application after migration either into a cloud or hybrid cloud is the Application after migration and optimized to leverage the advantages of the cloud Technical Challenges Portability of Architecture, Design, Code, Usage as well as Public, Private & Hybrid Cloud Environment we wish to migrate into. Only certain classes of Scientific Applications are appropriate Data parallel Applications Unpredictable Run times to completion either too much demand on computational resources or none - no fixed time runs. No unstructured message passing or too much dependence on Virtual Organizations Secure sharable data or data that is already in public 6

The Middle Path! Mindset Change! Migrate core parts of existing Grid Applications / Libraries to leverage Cloud Benefits Leverage Grid Patterns for Cloud Compute, Storage & Communications Cloudonomics! Our Neutral Approach The 7 Step Migration Model Applicable Across Cloud Services (Private &/or Hybrid) AWS, Azure, GAE, Eucalyptus, Hadoop oriented Apps 7

The 7-Step Migration Model Infosys Research 1. Conduct Cloud Migration Assessments 2. Isolate the Dependencies 3. Map the Messaging & Environment 4. Re-architect & Implement the lost Functionality 5. Leverage Cloud Functionalities & Features 6. Test the Migration 7. Iterate and Optimize 8

The 7-Step Migration Model in Brief Infosys Research Assess Isolate Map Rearchitect Augment Test Optimize Assess Isolate Map Re-Architect Augment Test Optimize Cloudonomics Migration Costs Recurring Costs Database data segmentation Database Migration Functionality migration NFR Support Runtime Environment Licensing Libraries Dependency Applications Dependency Latencies Bottlenecks Performance bottlenecks Architectural Dependencies Messages mapping: marshalling & demarshalling Mapping Environments Mapping libraries & runtime approximations Approximate lost functionality using cloud runtime support API New Usecases Analysis Design Exploit additional cloud features Seek Low-cost augmentations Autoscaling Storage Bandwidth Security Augment Test Cases and Test Automation Run Proof-of- Concepts Test migration strategy Test new testcases due to cloud augmentation Test for Production Loads Optimize rework and iterate Significantly satisfy cloudonomics of migration Optimize compliance with standards and governance Deliver best migration ROI Develop roadmap for leveraging new cloud features 9

The 7-Step Migration Model Explained Conduct Cloud Migration Assessments Cloudonomics : Migration Costs and Long-Term Recurring costs Database data segmentation, security & migration Functionality migration and Non-Functional Requirements support Isolate the Dependencies Runtime Environment Virtual Organizations and Policies Licensing Libraries, Application and Code Communication latency & Performance dependencies Architectural dependencies 10

The 7-Step Migration Model Explained.. Contd Map the Messaging and Environment Marshalling /demarshalling & mapping parameters of communication - Adapters Environment parameters approximation maps Libraries and runtime mapping exploiting data parallelism where possible Keep it as loosely-coupled and coarse-grained Re-Architect and Implement the lost functionality Approximate the lost functionality in terms cloud support Not all grid features can be migrated Need Mindset Change for that! Re-architect bridges and new code Leverage Cloud Functionalities and Features Augment application to exploit cloud features Low cost - big impact cloud features enhance usage 11

The 7-Step Migration Model Explained.. Contd Test the Migration Augment test cases and test automation Run Proof of Concepts & then scale to production size Augment test cases suite with cloud functionality usage Validate both the migration strategy and augmentation Optimize Optimize the migration strategy rework & iterate Satisfactory Cloudonomics for a broad range of usage? Standards compliance & Governance issues Develop a roadmap for leveraging new cloud features Iterate to deliver best ROI 12

Best Practices for Migrating into a Cloud Best Practices Design for failures underlying cloud systems are commodity items Avoid Single Points of Failure in your Applications Develop loose coupling between applications / code / services Exploit key cloud features: scaling, elasticity, network locality and location independence, anonymity, support for hybrid clouds, etc Build security, reliability and other non-functional requirements at every level and layer Rethink architectural constraints to avail cloud benefits Iterate and Optimize Beware of Vendor-Lock ins, Data Security Issues, SLAs and Pricing Honeypots Migrating into the Cloud is not a trivial task Leverage best practices EMI, DCI etc Migrating into the cloud major activity amongst most software firms and IT departments of various enterprises Lots of individual experiences IP challenges Migration Complexities are software engineering challenges Approaches exist! Optimal Migration yield best ROI for using Cloud offerings Data and Application migration is pretty popular while more challenging is the Architecture and Design migration for PAAS and SAAS platforms it is still evolving.

THANK YOU!