Automating Research Data Management at Scale with Globus
•
0 j'aime•223 vues
Research computing facilities, such as the national supercomputing centers, and shared instruments, such as cryo electron microscopes and advanced light sources, are generating large volumes of data daily. These growing data volumes make it challenging for researchers to perform what should be mundane tasks: move data reliably, describe data for subsequent discovery, and make data accessible to geographically distributed collaborators. Most employ some set of ad hoc methods, which are not scalable, and it is clear that some level of automation is required for these tasks. Globus is an established service from the University of Chicago that is widely used for managing research data in national laboratories, campus computing centers, and HPC facilities. While its intuitive web app addresses simple file transfer and sharing scenarios, automation at scale requires integrating Globus data management platform services into custom science gateways, data portals and other web applications in service of research. Such applications should enable automated ingest of data from diverse sources, launching of analysis runs on diverse computing resources, extraction and addition of metadata for creating search indexes, assignment of persistent identifiers faceted search for rapid data discovery, and point-and-click downloading of datasets by authorized users — all protected by an authentication and authorization substrate that allows the implementation of flexible data access policies for both metadata and data alike. We describe current and emerging Globus services that facilitate these automated data flows while ensuring a streamlined user experience. We also demonstrate Petreldata.net, a data management portal and gateway to multiple computing resources, that supports large-scale research at the Advanced Photon Source.
Recommandé
Recommandé
Contenu connexe
Tendances
Tendances (20)
Similaire à Automating Research Data Management at Scale with Globus
Similaire à Automating Research Data Management at Scale with Globus (20)
Plus de Globus
Plus de Globus (20)
Dernier
Dernier (20)
Automating Research Data Management at Scale with Globus
- 1. Automating Research Data Management at Scale Vas Vasiliadis Greg Nawrocki SGCI Webinar September 9, 2020
- 2. Globus is … a non-profit service developed and operated by
- 3. Our mission is to… increase the efficiency and effectiveness of researchers engaged in data-driven science and scholarship through sustainable software
- 4. 4
- 5. Fast, reliable file transfer …from any to any system User-initiated, or automated transfer request 1 Instrument, Lab server Compute Facility Globus transfers files reliably, securely 2 Globally accessible multi-tenant service • Fire-and-forget transfers • Optimized speed • Assured reliability • Unified view of storage • Browser, REST API, CLI v Optional notifications 3
- 6. Secure data sharing …from any storage Collaborator logs into Globus and accesses shared files; no local account required; download via Globus2 On-prem or public cloud storage Select files to share, select user or group, and set access permissions 1Globally accessible multi-tenant service Globus controls access to shared files on existing storage Laptop, server, compute facility • Fine-grained access control “overlay” on storage system • Share with any identity, email, group • No need to stage data just for sharing v
- 8. Coming soon… Globus Developed Community Developed
- 9. Use(r)-appropriate interfaces GET /endpoint/go%23ep1 PUT /endpoint/demodoc#my_endpt 200 OK X-Transfer-API-Version: 0.10 Content-Type: application/json … Globus service Web CLI Platform (RESTful APIs)
- 10. Globus Command Line Interface (CLI) • Native application: docs.globus.org/cli • Open source, uses Python SDK • globus login – get access and refresh tokens – Tokens stored locally in ~/.globus.cfg • Service (transfer/auth) invocation uses tokens • globus logout – delete tokens docs.globus.org/cli/examples
- 13. Automated instrument data egress Cryo EM Lightsheet Sequencer ALS/APS …. Local system download Remote analysis, visualization • Reliable, near-real time data access • Automatically set policy based permissions • Self-service access control, management • Federated login for frictionless data access Local policy store --/cohort045 --/cohort096 --/cohort127 v
- 14. v Repository data distribution Bulk data transfer 2 Search, request data of interest 1 • Gateway/data portal/app enables faceted search • Enforces fine-grained authorization • HTTPS download for “small” data • Asynchronous transfer for larger data sets 2 Browser based download Globally accessible multi-tenant service 2
- 15. --/run123/output (r) Output data staged with access control 2 Data staging for compute --/run123/input (rw) Compute service v • User securely uploads data for analysis • Results available with fine- grained permissions • Automated setup/tear down of folders, permissions 3 User accesses, downloads results 1 Input data upload
- 16. Automation Examples • Syncing a directory – bash script; calls the Globus CLI – Python module; run as script or import as module • Staging data for distribution – bash and Python variants • Removing directories after files are transferred – Python script 16 github.com/globus/automation-examples
- 17. …but scripting only gets us so far… 17
- 18. Globus platform services • Identity and Access Management (IAM): Auth, Groups • Data Services: Connect, Transfer, Manifest* • Search • Identifiers (collaboration with DataCite) • Flows* 18
- 20. Globus Automate A platform service for defining, applying, and sharing distributed research automation flows • Triggers start flows based on subscribed events • Flows call Action Providers to perform tasks
- 21. Globus automation architecture • Built on AWS Step Functions – JSON-based state machine language – Conditions, loops, fault tolerance, etc. – Propagates state through the flow • Standardized API for integrating custom event and action services – Actions: synchronous or asynchronous – Custom Web forms prompt for user input • Actions secured with Globus Auth
- 22. Automation Action Providers Delete ACLs Search DLHub User Form Notification Expression Evaluation Describe Web FormIdentifier Transfer Ingest Xtract funcX Globus action providers Custom action providers
- 23. funcX action provider funcX: FaaS platform for HPC • funcX endpoints deployed at resources • Service routes requests to endpoints • Parsl acquires resources • Singularity containers run functions • Globus Auth secures communication funcX
- 24. Xtract action provider Xtract: Derive rich metadata on-demand Xtract
- 26. UChicago Kasthuri Lab: Brain aging and disease • Construct connectomes—mapping of neuron connections • Use APS synchrotron to rapidly image brains – Beam time available once every few months – ~20GB/minute for large (cm) unsectioned brains • Generate segmented datasets/visualizations for the community • Perform semi-standard reconstruction on all data across HPC resources
- 27. Argonne JLSEUChicago Argonne Leadership Computing FacilityAPS Publication7 Neurocartography Imaging1 Lab Server 1 Acquisition2 Lab Server 2 Pre-processing3 Preview/Center4 Reconstruction6Visualization8 User validation5 Science!9 Neuroanatomy reconstruction pipeline
- 28. Automating neurocartography Web form User input Search Ingest Share Set policy Identifier Mint DOI funcX Auth Get credentials Automate Run job Describe Get metadata Transfer Transfer data funcX Run job Transfer Transfer data
- 29. XPCS: X-ray Photon Correlation Spectroscopy Data Portal Storage Argonne Leadership Computing Facility Advanced Photon Source Publication5 Imaging1 Lab Server 1 Acquisition2 Plot results4 XPCS-Eigen3 Science!6
- 30. Automating XPCS Search Ingest funcX Auth Get credentials Automate Plot Results Transfer Transfer HDF5 Transfer Transfer IMM funcX Run Corr ACLs Set policy Transfer Return Results
- 31. Materials Data Facility > 35 TB of data > 320 authors> 400 datasets • Accept data from many locations with flexible interfaces • Index dataset contents in science-aware ways • Dispatch data to the community • Using Automate to simplify building composable flows of services
- 32. MDF Data Publication Automation Ingest Bulk Ingest Auth Get Credentials Automate Transfer Transfer Dataset XTract Extract Metadata Share Set permissions Transfer Move metadata Transfer Transfer Dataset Transfers Transfer Dataset Identifier Mint DOI Web form Metadata Notify Notify Curator Web form Curation Notify Notify user
- 33. Petrel data services • Data service providing simple, self-managed project-based data and sharing capabilities (https://petreldata.net) • Flexible user-managed search index and discovery portal
- 34. PaaS: develop custom action providers • Directly use the platform to build and run extensible flows • Develop action providers – Fit for purpose – Developed and deployed by the project – Plugged into their flows • Action Provider Development toolkit 36
- 35. SaaS: instrument data management • Templated solution • Configurable… – Set transfer triggers – Select destination(s) – Define metadata • Extensible… – Add/remove actions – Change action providers • No development required Cryo EM Lightsheet Sequencer …. Indexing for search Image reconstruction, analysis, visualization Automated egress from device --/cohort045 --/cohort096 --/cohort127 Transfer funcXXtract
- 36. SaaS: Data Management Plans • “Turnkey” DMP enablement • Select dataset (collection)… • …add metadata for indexing • …generate persistent ID (DOI, ARK, etc.) 38 Transfer Identifier Ingest “Point & Click” to findable and accessible data
- 37. Thank you, funders... U . S . D E P A R T M E N T O F ENERGY