{"id":"W2461188658","doi":"10.1145/2851613.2851642","title":"Monitoring service level workload and adapting highly available applications","year":2016,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Workload; Provisioning; Elasticity (physics); Computer science; Cloud computing; Distributed computing; Middleware (distributed applications); Server; Computer network; Operating system; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008275128,0.00077565,0.0006356812,0.001142886,0.0003602162,0.001200911,0.0006550146,0.0004663817,0.0007537754],"category_scores_gemma":[0.003099271,0.0003183281,0.0002252142,0.000685394,0.0001611932,0.0009321256,0.0005135427,0.0006734864,0.0006096364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003835771,"about_ca_system_score_gemma":0.0004916987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001183492,"about_ca_topic_score_gemma":0.001035958,"domain_scores_codex":[0.9986039,0.0001910204,0.00009211341,0.0002930065,0.0006961734,0.0001238129],"domain_scores_gemma":[0.9978426,0.0005695685,0.0003022804,0.0003914837,0.0006790422,0.000215074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001122885,0.0007519545,0.09347641,0.0003143444,0.0001576257,0.000588839,0.0007514548,0.03828162,0.5356956,0.002464866,0.003778475,0.3226158],"study_design_scores_gemma":[0.00003068196,0.0005422091,0.1072309,0.00004161607,0.00008457402,0.000730305,0.0003318536,0.6809429,0.1995018,0.002992022,0.007472591,0.00009861806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7893915,0.0006621874,0.195575,0.0003029745,0.000136082,0.0002482373,0.0004115921,0.006818026,0.006454478],"genre_scores_gemma":[0.9805605,0.0001476311,0.0177181,0.00005363837,0.00004472589,0.00005088788,0.000300499,0.0001355371,0.0009884343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001200911,"threshold_uncertainty_score":0.004376352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04366439245796891,"score_gpt":0.2345825499297646,"score_spread":0.1909181574717957,"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."}}