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    OPAL: Leveraging Open Source

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    ITC_2022_22-15-03.pdf
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    Author
    Ogden, Eddge
    Call, Kenneth
    Myers, Isaac J.
    Ma, Zayd L.
    Lowe, Daniel
    Affiliation
    309th SWEG
    Air Force Materiel Command Hill AFB, UT
    Avionics Test and Analysis Corporation
    Issue Date
    2022-10
    
    Metadata
    Show full item record
    Citation
    Ogden, E., Call, K., Myers, I. J., Ma, Z. L., & Lowe, D. (2022). OPAL: Leveraging Open Source. International Telemetering Conference Proceedings, 57.
    Publisher
    International Foundation for Telemetering
    Journal
    International Telemetering Conference Proceedings
    URI
    http://hdl.handle.net/10150/666979
    Additional Links
    http://www.telemetry.org/
    Abstract
    The current explosion of test and evaluation data being collected from various systems has exposed a strong need for low-cost digital infrastructure to facilitate scalable analytics across all available data. Private industry and academic research have built such systems utilizing Open-Source Software (OSS) with tremendous success. The 309th Software Egineering Group (SWEG) developed OPAL (Open Platform for Advanced Learning) platform is a government owned and developed solution to address this gap and provide data discovery, analytics, and warehousing all license free. OPAL leverages best-in-breed Open-Source Software including JupyterLab (Python analysis environment), MinIO (S3-compliant, redundant and object-versioning data backend), Postgres (Data cataloging), and Dask (scalable compute), among others. In addition to Open-Source tooling, custom integration and software piping are used to further lower the analysts’ barrier to available data: custom Chapter 10 parsing and translating at high speed (10GB/min) into Apache Parquet format, a web-based data catalog for discovery, and lightweight arbitrary object storage organization. This paper will delineate design choices, our DevOps paradigm, benchmarking numbers, and results against a publicly available commercial flight dataset.
    Type
    Proceedings
    text
    Language
    en
    ISSN
    1546-2188
    0884-5123
    0074-9079
    Sponsors
    International Foundation for Telemetering
    Collections
    International Telemetering Conference Proceedings, Volume 57 (2022)

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