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Session18 Madduri


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Session18 Madduri

  1. 1. Service Oriented Architecture and Globus Toolkit Ravi K Madduri Argonne National Laboratory University of Chicago
  2. 2. Agenda q Principles of Service Oriented Architecture q The Globus Toolkit q Web Services Basics q Grid Services q What people punt on ? x Intro to Globus Security, Service Registries q Workflows we created q Lessons learned
  3. 3. Principles of Service Oriented Architecture q Guiding principles define the ground rules for development, maintenance, and usage of the SOA x Reuse, granularity, modularity, composability, componentization and interoperability x Standards compliance (both common and industry-specific) x Services identification and categorization, provisioning and delivery, and monitoring and tracking
  4. 4. Architectural Principles q Service encapsulation – Many web services are consolidated to be used under the SOA. q Service loose coupling – Services maintain a relationship that minimizes dependencies and only requires that they maintain an awareness of each other q Service contract – Services adhere to a communications agreement, as defined collectively by one or more service description documents q Service abstraction – Beyond what is described in the service contract, services hide logic from the outside world
  5. 5. Architectural Principles q Service reusability – Logic is divided into services with the intention of promoting reuse q Service composability – Collections of services can be coordinated and assembled to form composite services q Service autonomy – Services have control over the logic they encapsulate
  6. 6. Architectural Principles q Service optimization – All else equal, high- quality services are generally considered preferable to low-quality ones q Service Discoverability - Services are designed to be outwardly descriptive so that they can be found and assessed via available discovery mechanisms q Service Relevance – Functionality is presented at a granularity recognized by the user as a meaningful service
  7. 7. Globus Software: Globus Projects OGSA-DAI GT4 MPICH- G2 Java Data Replica Delegation MyProxy Runtime Rep Location GridWay C GSI- CAS GridFTP MDS4 Runtime OpenSSH Incubator Reliable Mgmt Python C Sec GRAM File GT4 Docs Runtime Transfer Common Execution Info Security Data Mgmt Other Runtime Mgmt Services
  8. 8. Web Service Basics q Web Services are basic distributed computing technology that let us construct client-server interactions Borja Sotomayor ,
  9. 9. Web Service Basics 2 q Web services are platform independent and language independent x Client and server program can be written in diff langs, run in diff envt’s and still interact q Web services describe themselves x Once located you can ask it how to use it q Web services are ideal for loosely coupled systems x Unlike CORBA, EJB, etc.
  10. 10. WSDL: Web Services Description Language Define expected messages for a service, and their (input or output parameters) An interface groups together a number of messages (operations) Bind an Interface via a definition to a specific transport (e.g. The network location where the service is HTTP) and messaging (e.g. implemented , e.g. http://localhost:8080 SOAP) protocol
  11. 11. Real Web Service Invocation Discover Describe Invoke Borja Sotomayor ,
  12. 12. Web Services Server Applications q Web service – software that exposes a set of operations q SOAP Engine – handle SOAP requests and responses (Apache Axis) q Application Server – provides Container “living space” for applications that must be accessed by different clients (Tomcat) q HTTP server- also called a Web server, handles http messages Borja Sotomayor ,
  13. 13. Let’s talk about state q Plain Web services are stateless Borja Sotomayor ,
  14. 14. However, Many Grid Applications Require State Borja Sotomayor ,
  15. 15. Keep the Web Service and the State Separate q Instead of putting state in a Web service, we keep it in a resource q Each resource has a unique key Borja Sotomayor ,
  16. 16. Resources Can Be Anything Stored Web Service + Resource = WS-Resource Address of a WS- resource is called an end-point reference
  17. 17. Web Services So Far q Basic client-server interactions q Stateless, but with associated resources q Self describing using WSDL q But we’d really like is a common way to x Name and do bindings x Start and end services x Query, subscription, and notification x Share error messages
  18. 18. Standard Interfaces q Service information q State representation x Resource GetRP x Resource Property GetMultRPs q State identification SetRP x Endpoint Reference Client Web QueryRPs Service q State Interfaces Subscribe x GetRP, QueryRPs, GetMultipleRPs, SetRP SetTerm Time q Lifetime Interfaces Destroy x SetTerminationTime x ImmediateDestruction q Notification Interfaces x Subscribe x Notify q ServiceGroups
  19. 19. WSRF & WS-Notification q Naming and bindings (basis for virtualization) x Every resource can be uniquely referenced, and has one or more associated services for interacting with it q Lifecycle (basis for fault resilient state management) x Resources created by services following factory pattern x Resources destroyed immediately or scheduled q Information model (basis for monitoring & discovery) x Resource properties associated with resources x Operations for querying and setting this info x Asynchronous notification of changes to properties q Service Groups (basis for registries & collective svcs) x Group membership rules & membership management q Base Fault type
  20. 20. WSRF vs XML/SOAP q The definition of WSRF means that the Grid and Web services communities can move forward on a common base q Why Not Just Use XML/SOAP? x WSRF and WS-N are just XML and SOAP x WSRF and WS-N are just Web services q Benefits of following the specs: x These patterns represent best practices that have been learned in many Grid applications x There is a community behind them x Why reinvent the wheel? x Standards facilitate interoperability
  21. 21. WS Core Enables Frameworks: E.g., Resource Management Applications of the framework (Compute, network, storage provisioning, job reservation & submission, data management, application service QoS, …) WS-Agreement WS Distributed Management (Agreement negotiation) (Lifecycle, monitoring, …) WS-Resource Framework & WS-Notification (*) (Resource identity, lifetime, inspection, subscription, …) Web services (WSDL, SOAP, WS-Security, WS-ReliableMessaging, …) * An evolution of Open Grid Services Infrastructure (OGSI)
  22. 22. Globus and Web Services User Applications Globus (e.g., Apache Axis) Globus Container and Admin WSRF Web Registry Services WS-A, WSRF, WS-Notification WSDL, SOAP, WS-Security Globus Core: Java , C (fast, small footprint), Python
  23. 23. Globus and Web Services User Applications Custom Globus (e.g., Apache Axis) Globus Container and Admin WSRF Web Registry Custom WSRF Web Services Services Services WS-A, WSRF, WS-Notification WSDL, SOAP, WS-Security Globus Core: Java , C (fast, small footprint), Python
  24. 24. Globus Security q Extensible authorization framework based on Web services standards x SAML-based authorization callout q Security Assertion Markup Language, OASIS standard q Used for Web Browers authentication often q Very short-lived bearer credentials x Integrated policy decision engine q XACML (eXtensible Access Control Markup Language) policy language, per-operation policies, pluggable
  25. 25. Delegation Service q Higher level Hosting Environment service Service1 q Authentication Service2 Resources protocol EPR Delegation Service independent Service3 Delegate Refresh q Refresh interface Refresh q Delegate once, EPR Delegate share across services and Client invocation Rachana Ananthakrishnan
  26. 26. Delegation q Secure Conversation x Can delegate as part of protocol x Extra round trip with delegation x Types: Full or Limited delegation x Delegation Service is preferred way of delegating q Secure Message and Secure Transport x Cannot delegate as part of protocol Rachana Ananthakrishnan
  27. 27. Globus’s Use of Security Standards Supported, Supported, Fastest, but slow but insecure so default
  28. 28. Monitoring and Discovery System (MDS4) q Grid-level monitoring system x Aid user/agent to identify host(s) on which to run an application x Warn on errors q Uses standard interfaces to provide publishing of data, discovery, and data access, including subscription/notification x WS-ResourceProperties, WS-BaseNotification, WS-ServiceGroup q Functions as an hourglass to provide a common interface to lower-level monitoring tools
  29. 29. Taverna A sample caGrid workflow caGrid Scavenger with semantic/ metadata based caGrid service query
  30. 30. Sample Workflow with caDSR q Scientific value Workflow input x To find all the UML packages related to a given context (‘caCore’). caGrid services x Not a real scientific experiment. q Simple. “Shim” q Important in caGrid. services q Steps x Querying Project object. x Do data transformation. x Querying Packages object Workflow output and get the result.
  31. 31. Protein sequence information query q Scientific value x To query protein sequence information out of 3 caGrid data services: caBIO, CPAS and GridPIR. x To analyze a protein sequence from different data sources. q Steps x Querying CPAS and get the id, name, value of the sequence. x Querying caBIO and GridPIR using the id or name obtained from CPAS.
  32. 32. Microarray clustering* q Scientific value x A common routine to group genes or experiments into clusters with similar profiles. x To identify functional groups of genes. q Steps x Querying and retrieving the microarray data of interest from a caArrayScrub data service at Columbia University x Preprocessing, or normalize the microarray data using the GenePattern analytical service Workflow in/output at the Broad Institute at MIT caGrid services x Running hierarchical clustering using the geWorkbench others “Shim” services analytical service at Columbia University *Wei Tan, Ravi Madduri, Kiran Keshav, Baris E. Suzek, Scott Oster, Ian Foster. Orchestrating caGrid Services in Taverna. ICWS 08.
  33. 33. Execution Execution result as trace xml 1936 gene expressions
  34. 34. Lymphoma prediction type prediction q Scientific value * x Using gene-expression patterns associated with DLBCL and FL to predict the lymphoma type of an unknown sample. x Using SVM (Support Vector Machine) to classify data, and predicting the tumor types of unknown examples. q (Major) steps x Querying training data from experiments stored in caArray. x Preprocessing, or normalize the microarray data. x Adding training and testing data into SVM service to get classification result. *Fig. from MA Shipp. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nature medicine,
  35. 35. Querying Preprocessing Classifying & predicting
  36. 36. Lymphoma type prediction q Result snippet *Classification errors are highlighted. Acknowledgement: Juli Klemm, Xiaopeng Bian, Rashmi Srinivasa (NCI) Jared Nedzel (MIT)
  37. 37. Lessons Learned q Service abstraction not applicable to everything q Virtual Organization concepts still good q Web services is one way to create service oriented architectures but not always the best way q Make implementation agnostic of tools underneath q True value in ability to create workflows
  38. 38. Service-Oriented Science q People create services (data or functions) … q which I discover (& decide whether to use) … q & compose to create a new function ... q & then publish as a new service. q  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers! !! q  I hope that this “someone else” can manage security, reliability, scalability, … “Service-Oriented Science”, Science, 2005
  39. 39. Questions ?