PanDA, the Production and Distributed Analysis system, is a workload management solution designed for large-scale data processing environments. It is intended to handle data-driven workloads and is built to accommodate evolving computing technologies in areas such as processing, storage, networking, and distributed computing middleware.
The platform offers a variety of components and modules, including a system architecture, database installation procedures, and advanced configuration options. Features highlighted in its documentation include a daemon for managing operations, brokerage for resource allocation, job sizing, dynamic optimization of task parameters, and mechanisms for messaging. PanDA also provides integration capabilities with CRIC and supports deployment of custom identity and access management (IAM) solutions. Additional modules address job retry logic, JEDI watchdogs, site and task classification, and estimation of the carbon footprint associated with PanDA jobs. The system supports analysis workflows through features like the Data Carousel and offers tools for detailed descriptions of task parameters that influence job behavior.
The documentation references specific instances and operations related to the ATLAS experiment, such as PanDA server instances, JEDI instances, and cache instances, indicating its application in scientific computing contexts. Guides are available for users, administrators, and developers, and there is an API for server interactions.
panda-server-source sits in PulseGate's Infrastructure & Backend category. It focuses on managing and orchestrating distributed computing jobs efficiently across large-scale infrastructure. It is built as an open-source project for researchers and developers in distributed computing. panda-server-source is open source under the Apache-2.0 license. It runs on the web and the command line, and it can be self-hosted.
panda-server-source first shipped in 2026. Key capabilities include distributed computing, job management, and task scheduling.
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