{"id":"W2910940173","doi":"10.48550/arxiv.1901.04946","title":"Kubernetes as an Availability Manager for Microservice Applications","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Microservices; Computer science; Stateful firewall; Orchestration; Provisioning; Architectural style; Cloud computing; Leverage (statistics); Architecture; High availability; Service (business); Stateless protocol; Service-oriented architecture; Distributed computing; World Wide Web; Computer network; Operating system; Web service; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002132921,0.0006313213,0.000435988,0.0007734579,0.0006223595,0.001520097,0.001704697,0.0005175311,0.003406759],"category_scores_gemma":[0.00391726,0.0005942106,0.0003794609,0.0004231833,0.0005207649,0.001860983,0.001722644,0.001365953,0.0009554587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007258647,"about_ca_system_score_gemma":0.00111364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002027677,"about_ca_topic_score_gemma":0.001383337,"domain_scores_codex":[0.9983934,0.0003189257,0.0001764318,0.0002869293,0.0006168777,0.000207481],"domain_scores_gemma":[0.9975368,0.0006630479,0.0003340448,0.0006531597,0.0004555778,0.0003574693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00648115,0.001964774,0.04901445,0.00205616,0.0006740635,0.003495426,0.005004535,0.08766627,0.2790288,0.06052499,0.06369819,0.4403912],"study_design_scores_gemma":[0.0004704967,0.001257367,0.04064105,0.0002421711,0.0003706397,0.001949806,0.0008285447,0.5412373,0.1987261,0.01349134,0.2003257,0.0004594741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3385125,0.00184413,0.4165199,0.0007393277,0.0005237187,0.0008502707,0.0009442308,0.2169701,0.02309586],"genre_scores_gemma":[0.8901876,0.0003382341,0.09652396,0.0002509255,0.0001034542,0.0002710175,0.0008438601,0.002763772,0.008717226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003406759,"threshold_uncertainty_score":0.01139677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04292096687603732,"score_gpt":0.2027153481552182,"score_spread":0.1597943812791809,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}