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Research and Development

Research and Development. R&D Agenda. Security Bulk Data Movement Data Replication and Mirroring Monitoring Metrics Versioning Product Services. Security: Single Sign-On Solutions. Goal: Single Sign-On (SSO) across browsers and non-browser clients Public Key Infrastructure (PKI) SSO

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Research and Development

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  1. Research and Development

  2. R&D Agenda • Security • Bulk Data Movement • Data Replication and Mirroring • Monitoring • Metrics • Versioning • Product Services

  3. Security: Single Sign-On Solutions Goal: Single Sign-On (SSO) across browsers and non-browser clients Public Key Infrastructure (PKI) SSO SSO for non-browser applications, like GridFTP SSO through X.509 public key certificates issued by MyProxy Online Certification Authority (CA) with username/password Auto-provisioning of trust configuration Web SSO SSO for http/https applications through OpenID OpenID Identity Provider (IdP) with username/password Web-SSO & PKI-SSO share username/password DB Single primary authentication mechanism for end user

  4. Security: Integrated WebSSO & PKI-SSO

  5. Security: MyProxy as Online CA • MyProxy: Open Source software from NCSA • Online CA is one of its many capabilities • Different primary authentication mechanisms through standardized Pluggable Authentication Module (PAM) • Shipped with Globus Toolkit, supported on various platforms • Client package as separate deployment, including Java clients and API Earth System Grid Center for Enabling Technologies: (ESG-CET)

  6. Security: Auto-Provisioning • PKI-SSO solutions require configuration of trust-roots • Identity providers (IdPs), Certification Authorities (CAs) • Revocation lists • Up-to-date configuration required at servers and clients • Scalability issues with large numbers of clients • MyProxy provides auto-provisioning option • Integrated with login • Transparently updates CAs and CRLs • Is extended to use for server-provisioning also

  7. Security: OpenID OpenID provides SSO across multiple servers and can leverage multiple IdPs OpenID satisfies ESG security requirements OpenID uses standard HTTP/HTTPS protocol Use ESG-specific OpenID profile to ensure safe deployment All communication with IdP requires SSL ClientIdP and IdpRP Yadis IDs (URIs) for OpenID identifiers Resource Providers (RP) enforce a white list of IdPs

  8. Security: OpenID4Java OpenID4Java: Open Source software ESG developers contribute enhancements back Deployable as independent package into standard application servers Integrates well with ESG’s application server software Built-in support: SSL (encrypted communication) User attributes push Java API to write authentication filters and identity providers Extended to support attributes and multiple identity providers

  9. Requirements Access all data holdings through uniform interfaces, including disk pools and mass storage systems on various nodes, using various security models Allocate space quotas to users dynamically on gateways in order to serve files to client Manage file lifetimes in the allocated spaces, and automatically clean up spaces for reuse Provide easy-to-use user facilities to download many files Manage large-scale robust data movement for replication of core data between nodes Storage Resource Management (SRM) tools support these requirements in ESG Bulk Data Movement

  10. Bulk Data Movement: SRM Technology, and BeStMan Storage Resource Managers (SRM) are middleware components over shared distributed storage components, that provide: Dynamic space allocation Dynamic file management in spaces Uniform interface to all storage systems The Berkeley Storage Manager (BeStMan) is an implementation of the SRM standard The SRM specification is an OGF (Open Grid Forum) standard that was developed over the last 7 years BesStMan is used in ESG, several High-Energy-Physics (HEP) experiments, and other applications BeStMan in ESG (see figure next slide) Used for coordinating space allocation and transparent access and file movement between ESG nodes and the gateway Currently interfaces to HPSS in NERSC and ORNL, to MSS at NCAR, and to disk systems at LLNL and LANL Also used to manage space on the NCAR gateway

  11. Bulk Data Movement: Use of BeStMan in ESG BeStMan at Gateway accesses all other BeStMan in nodes to get requested files (highlighted in purple)

  12. DataMoverLite (DML): Simplifying Data Movement to Clients Goal: automate pulling of files into user’s workstation • Using various transfer protocols (GridFTP, bbcp, https, …) • Have a GUI that shows transfer progress, or summary progress with command line • Supports entire directory transfers • Supports suspend/resume operations • DML available onLinux, PC, MAC • GUI shows info on completed, active, pendingtransfers • Also, file sizes,transfer times,transfer speed

  13. Bulk Data Movement Service Requirements Move terabytes to petabytes (many thousands of files) Asynchronous long-lasting operation Recovery from transient failures and automatic restart Take advantage of (dynamic) network provisioning Use GridFTP, other protocols if necessary Space verification at target Support for data checksums On-demand transfer status information On-demand completion time estimates Statistics collection For security reasons bulk data movement needs to be done in “pull mode”

  14. Workflow for Future Bulk Data Movement Service Initialization Replicate directory structure Initial request estimation Request submission Generate plan using statistics Verify storage at Target Execution On-demand status Multi-file request coordinator Compose request for failed files Dynamic progress estimation Monitor and generate statistics Recovery and restart File transfer client Suspend and resume Checksum comparison

  15. Data Replication and Mirroring Requirement: several mirror sites around the world want to host key subsets (called a “core”) of ESG data sets This is a new requirement for ESG Replication of climate data sets was not originally an ESG goal Originally considered impractical because of large size of climate data sets With increasing importance of the IPCC data, international sites want to replicate or “mirror” key data sets Give scientists in a geographical region access to a “local” copy Reduce wide area latencies for data access Provide increased fault tolerance and disaster protection, since data sets are available at multiple sites

  16. Impact of Data Replication/Mirroring This work will make ESG data sets more accessible to climate scientists outside of the ESG-CET project Initial planned mirror sites: UK’s British Atmospheric Data Centre (BADC) Germany’s Max Planck Institute for Meterology (MPIM) Both have participated in design discussions for mirroring functionality Others mirror sites likely (e.g., in Asia) Global network topology considerations Impact will be to increase the use of ESG and CMIP5 data sets by scientists around the world, thus advancing climate science discoveries

  17. Requirements for Data Mirroring Newly published data set(s) are added to a common core produced at a gateway A mirror site replicates some or all of the data sets from the common core published by a gateway Changes to existing data sets (additions, deletions, replacements, modifications) are propagated from publishing gateway to mirror sites

  18. Data Mirroring Plans Going Forward Implementation plan (currently in progress) involves integration of several key ESG components and new functionality Choose among available source replicas for data and metadata Invoke the Bulk Data Movement component to copy data sets reliably to the mirror site’s data node Use existing ESG metadata API operations to query the relevant metadata at the publishing node Use a modified version of the ESG publication client to publish newly replicated data sets at the mirror site’s gateway Identify updates that need to be propagated to mirror sites using versioning functionality. Technical objectives In the next year: complete initial implementation and deployment; evaluate data mirroring at sites in ESG, Europe Add functionality, including support for automatic subscription and notification of mirrored data sets

  19. Replication Architecture (1)

  20. Replication Architecture (2)

  21. Monitoring • Monitoring has contributed significantly to the robustness of the ESG infrastructure • Based on the Globus Monitoring and Discovery System (MDS) • ESG uses MDS to monitor the status of components in the distributed system • GridFTP data transfer services • Storage Resource Managers (SRMs) • NCAR portal • HTTP data services • OpenDAP services • Replica Location Services (RLSs)

  22. Globus Monitoring and Discovery System • MDS Index Service • Collects status information from information providers at each component • Report whether a particular service being monitored is currently working correctly • MDS Trigger Service • Takes actions based on monitored conditions • Sends emails to the Earth System Grid administrators’ mailing list when components fail

  23. Impact of Monitoring and Future Plans • Has resulted in much faster recovery of failed services in the distributed ESG infrastructure • Lower downtime of our infrastructure • The ESG team is quickly informed when components fail • Allows the team to quickly restart failed services • Often before failures are encountered by users • We plan to deploy yet more sophisticated monitoring • ESG infrastructure increasingly distributed, federated • Also want to monitor status of mirror sites worldwide • Monitor service performance as well as availability • Investigating NetLogger, PerfSONAR

  24. Metrics Metrics are required to track and record users interactions with the ESG enterprise system Reporting is required to show the benefits of the ESG enterprise system to the scientific community at large ESG Gateway requests metric data from its Data Nodes An ESG Gateway will periodically download metrics data (SRM, OPeNDAP, LAS, server hardware performance) gathered by a Data Node for a give interval of time Returned metrics data will then be stored at the ESG Gateway for future metrics reports

  25. Metrics Requirements

  26. Metrics Requirements

  27. Metrics progress The gathering of important metrics for the ESG Gateway has been completed • User registrations • User logins • File downloads • User clickstreams • Browser type usage Report generation for key metrics has been completed • Total users registered, including monthly trends • Total files downloaded, including monthly trends

  28. Metrics Plan Going Foward Several improvements are required in the near term for Metrics • Design and development of the Data Node “black box” metrics gathering software • Design and development of auto generated report notifications via email • Design and development of a star schema for the metrics database

  29. Data Versioning • Data changes, even after publication • Errors in simulation, processing, metadata, etc. • Critically important that data publishers and consumers can identify which version of data they are working with • Changes to data may affect results of analyses • Versioning previously handled manually • Adequate for moderate amounts of closely controlled data (current production archives) • Insufficient for global scale, especially with replication (key driver) • Now putting versioning on formal footing • In collaboration with BADC, MPIM • Initial focus on identification of key use cases, developing and evaluating preliminary software designs

  30. Proposed Versioning Software Design

  31. Product Services: Delivering Visualization and Analysis to Users • Product Services provide a web-based easy-to-use interface to a vast array of interactive, science-relevant information products • Make plots in 1 and 2 dimensions along any axis or combination of two axes including animation along the time axis • Control plot appearance • Launch external tools either via scripts to access data in desktop tools or direct launch of Google Earth • Compare different data sets and variables in specialized user interface • Request server-side analysis and view the results • Supports plots of curvilinear data grids and on-the-fly re-gridding to rectangular grids • Web-based administrative interface for cache management

  32. Product Services Architecture Designed to integrate many data types and products from many legacy applications into a unified user-controlled environment Combines incoming request with metadata to learn where the data are; what protocol is needed to read them and instructs backend services to read the data and create products

  33. Product Services Offer Diverse Capabilities (1/2) Product Services provide a Web-based easy-to-use interface to a vast array of interactive, science-relevant information products Launch external tools like Google Earth, Matlab and others Compute on-the-fly analysis via efficient server-side functions and plot the result

  34. Product Services Offer Diverse Capabilities (2/2) Make comparisons along an axes and/or between data sets Make comparisons along different cutting planes and/or between data sets

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