{"id":"W2582224660","doi":"10.1109/cloudcom.2016.0051","title":"Efficiency Analysis of Provisioning Microservices","year":2016,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Microservices; Cloud computing; Computer science; Software deployment; Provisioning; Scalability; Leverage (statistics); Flexibility (engineering); Software engineering; Distributed computing; Operating system","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":[0.003386415,0.0008588904,0.001090489,0.001069718,0.0005954836,0.001635225,0.001405372,0.0007958566,0.002681838],"category_scores_gemma":[0.01362141,0.0004181301,0.0005304923,0.0009754792,0.0008701261,0.002038964,0.000977702,0.0007698382,0.0002903064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003042741,"about_ca_system_score_gemma":0.002051465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004768958,"about_ca_topic_score_gemma":0.002575103,"domain_scores_codex":[0.9976537,0.0008073625,0.00006338702,0.0002635304,0.0006187896,0.0005933408],"domain_scores_gemma":[0.9894973,0.0077871,0.0007081764,0.0007864647,0.0009233094,0.0002976742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001512302,0.0000807193,0.001818863,0.0001044335,0.00002783937,0.00006047666,0.00005098773,0.9608307,0.00402288,0.01676799,0.0009437424,0.01513998],"study_design_scores_gemma":[0.000003391569,0.00002592891,0.0003319651,0.000005003569,0.000006183003,0.00001335608,0.00002885427,0.9963611,0.0009163417,0.002162065,0.0001425268,0.000003277305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5691944,0.001727085,0.4010772,0.001354796,0.00008196554,0.0002229574,0.0003209333,0.0009142072,0.02510644],"genre_scores_gemma":[0.9855428,0.000192937,0.01317933,0.00004624064,0.00001339431,0.00003924179,0.0000729094,0.00008243222,0.0008307859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004768958,"threshold_uncertainty_score":0.02207673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007321636476551508,"score_gpt":0.2256713540220082,"score_spread":0.2183497175454567,"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."}}