{"schema_version":"onlylabs.public_signal.v1","title":"Amazon (Nova) Repo: amazon-science/Distributed-Search-Engine-Simulator","description":"Amazon (Nova) repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/c5a6c2e9-4674-4ec9-af7c-73fcc30d6dc1","json_url":"https://onlylabs.fyi/signals/c5a6c2e9-4674-4ec9-af7c-73fcc30d6dc1/signal.json","generated_at":"2026-06-11T02:52:58.511414+00:00","org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/amazon","dossier_json_url":"https://onlylabs.fyi/labs/amazon/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/c5a6c2e9-4674-4ec9-af7c-73fcc30d6dc1","signal_json":"https://onlylabs.fyi/signals/c5a6c2e9-4674-4ec9-af7c-73fcc30d6dc1/signal.json","source":"https://github.com/amazon-science/Distributed-Search-Engine-Simulator","lab_dossier":"https://onlylabs.fyi/labs/amazon","lab_dossier_json":"https://onlylabs.fyi/labs/amazon/dossier.json","analysis":"https://onlylabs.fyi/analysis/amazon","analysis_json":"https://onlylabs.fyi/analysis/amazon/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/amazon/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"Amazon (Nova) published amazon-science/Distributed-Search-Engine-Simulator (Python). 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Overview This simulator models the behavior of search engine clusters, including workers, shards, indices, and resource management. It provides an environment for developing and testing RL agents that make scaling decisions based on workload patterns and system metrics. Features - **Discrete-Event Simulation**: Async-based event-driven architecture for efficient simulation - **Resource Modeling**: Simulates CPU, memory, disk, and network resources with configurable parameters - **Workload Generation**: Built-in generators for synthetic workload patterns (sinusoidal, custom) - **RL Agent Framework**: Abstract agent interface for implementing custom scaling policies - **Profiling & Metrics**: Comprehensive metrics collection and CSV export for analysis - **HTTP..."},"evidence_pages":[{"url":"https://github.com/amazon-science/Distributed-Search-Engine-Simulator","final_url":"https://github.com/amazon-science/Distributed-Search-Engine-Simulator","title":"amazon-science/Distributed-Search-Engine-Simulator repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T02:52:58.511414+00:00","bytes":20097,"raw_path":"949b867dae1c00821f7a3feee0fb2ef08b4f5f5f67b28e0fa6a7f47e1848b031.json","content_hash":"df70b1de609842587c37dd690f10f6392355ebe40aded8c579297e6cd11ea404","excerpt_chars":1200,"truncated":true,"excerpt":"amazon-science/Distributed-Search-Engine-Simulator Language: Python License: NOASSERTION Stars: 2 Forks: 0 Open issues: 0 Created: 2026-02-16T11:28:15Z Pushed: 2026-03-09T20:44:25Z Default branch: main Fork: no Archived: no README: Distributed Search Engine Simulator (Python) A discrete-event simulation framework for distributed search engines designed for reinforcement learning research and capacity planning optimization. Overview This simulator models the behavior of search engine clusters, including workers, shards, indices, and resource management. It provides an environment for developing and testing RL agents that make scaling decisions based on workload patterns and system metrics. 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