{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:UNKD7WFYH3AUUUJAYRW6M7DEVB","short_pith_number":"pith:UNKD7WFY","schema_version":"1.0","canonical_sha256":"a3543fd8b83ec14a5120c46de67c64a8798e73060e1b1550df25544d4b092b84","source":{"kind":"arxiv","id":"1411.7955","version":1},"attestation_state":"computed","paper":{"title":"Leveraging Cloud Data to Mitigate User Experience from \"Breaking Bad\"","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Arun Kejariwal, David S. Matteson, Nicholas A. James","submitted_at":"2014-11-28T17:57:35Z","abstract_excerpt":"Low latency and high availability of an app or a web service are key, amongst other factors, to the overall user experience (which in turn directly impacts the bottomline). Exogenic and/or endogenic factors often give rise to breakouts in cloud data which makes maintaining high availability and delivering high performance very challenging.\n  Although there exists a large body of prior research in breakout detection, existing techniques are not suitable for detecting breakouts in cloud data owing to being not robust in the presence of anomalies.\n  To this end, we developed a novel statistical t"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1411.7955","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"stat.ME","submitted_at":"2014-11-28T17:57:35Z","cross_cats_sorted":[],"title_canon_sha256":"897b2f7431888501d5549e6ab4d45154481735b0b6028d19cdd353b1eb06989e","abstract_canon_sha256":"c7d0d1847a4caa5d9ae352d9f72dc93ffeb73d35014a6a59967beef74d216e94"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:32:31.962004Z","signature_b64":"erCRVzH/oJRROUf9sPX+4jnQnIvoWa5TITOLJ7mkYURJKfve0jcsnSlHj53HirYXH9EZv9eNVapc+3UyyIEVDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a3543fd8b83ec14a5120c46de67c64a8798e73060e1b1550df25544d4b092b84","last_reissued_at":"2026-05-18T02:32:31.961627Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:32:31.961627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Leveraging Cloud Data to Mitigate User Experience from \"Breaking Bad\"","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Arun Kejariwal, David S. Matteson, Nicholas A. James","submitted_at":"2014-11-28T17:57:35Z","abstract_excerpt":"Low latency and high availability of an app or a web service are key, amongst other factors, to the overall user experience (which in turn directly impacts the bottomline). Exogenic and/or endogenic factors often give rise to breakouts in cloud data which makes maintaining high availability and delivering high performance very challenging.\n  Although there exists a large body of prior research in breakout detection, existing techniques are not suitable for detecting breakouts in cloud data owing to being not robust in the presence of anomalies.\n  To this end, we developed a novel statistical t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1411.7955","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1411.7955","created_at":"2026-05-18T02:32:31.961677+00:00"},{"alias_kind":"arxiv_version","alias_value":"1411.7955v1","created_at":"2026-05-18T02:32:31.961677+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1411.7955","created_at":"2026-05-18T02:32:31.961677+00:00"},{"alias_kind":"pith_short_12","alias_value":"UNKD7WFYH3AU","created_at":"2026-05-18T12:28:52.271510+00:00"},{"alias_kind":"pith_short_16","alias_value":"UNKD7WFYH3AUUUJA","created_at":"2026-05-18T12:28:52.271510+00:00"},{"alias_kind":"pith_short_8","alias_value":"UNKD7WFY","created_at":"2026-05-18T12:28:52.271510+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB","json":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB.json","graph_json":"https://pith.science/api/pith-number/UNKD7WFYH3AUUUJAYRW6M7DEVB/graph.json","events_json":"https://pith.science/api/pith-number/UNKD7WFYH3AUUUJAYRW6M7DEVB/events.json","paper":"https://pith.science/paper/UNKD7WFY"},"agent_actions":{"view_html":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB","download_json":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB.json","view_paper":"https://pith.science/paper/UNKD7WFY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1411.7955&json=true","fetch_graph":"https://pith.science/api/pith-number/UNKD7WFYH3AUUUJAYRW6M7DEVB/graph.json","fetch_events":"https://pith.science/api/pith-number/UNKD7WFYH3AUUUJAYRW6M7DEVB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB/action/storage_attestation","attest_author":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB/action/author_attestation","sign_citation":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB/action/citation_signature","submit_replication":"https://pith.science/pith/UNKD7WFYH3AUUUJAYRW6M7DEVB/action/replication_record"}},"created_at":"2026-05-18T02:32:31.961677+00:00","updated_at":"2026-05-18T02:32:31.961677+00:00"}