What is the output of `kapacitor stats ingress`? On Tuesday, October 18, 2016 at 2:11:13 PM UTC-6, A Sun wrote: > > I didn't see any error in the kapacitor.log file about not being able to > write to log files. I tried the telegraf/influxdb/kapacitor cpu_alert > example, which worked. So I think the problem is that the test data > generator wasn't able to write to the recording stream. I always got > "running" but not "finished" status on the recording stream. > > 5d954874-dff8-4a86-adc0-009a011c40f7 stream running 0 B 18 Oct > 16 10:24 CDT > > On Tue, Oct 18, 2016 at 2:56 PM, <nath...@influxdb.com <javascript:>> > wrote: > >> Based on the stats from the show output it looks like all three alert >> nodes have produced at least some alerts. Does the directory /tmp/test >> exist? Is it writable by the kapacitord process? Are there any errors in >> the logs about not being able to write to the log files? >> >> >> >> On Tuesday, October 18, 2016 at 9:43:19 AM UTC-6, A Sun wrote: >>> >>> Hi, I'm new to kapacitor. I tried to follow the steps in custom anomaly >>> detection example ( >>> https://docs.influxdata.com/kapacitor/v1.0/examples/anomaly_detection/) >>> >>> However, I don't see any alert log files after running the task. >>> >>> The data stream seems to be empty after running the test data generator, >>> >>> >>> ID Type Status Size Date >>> >>> 8724ca17-7ff5-4694-8b66-aae14d4be7f4 stream running 0 B 18 >>> Oct 16 10:28 CDT >>> >>> >>> >>> Here's output from "kapacitor show print_temps". It seems some events >>> were processed but no alerts were logged. >>> >>> { >>> "link": { >>> "rel": "self", >>> "href": "/kapacitor/v1/tasks/print_temps" >>> }, >>> "id": "print_temps", >>> "template-id": "", >>> "type": "stream", >>> "dbrps": [ >>> { >>> "db": "printer", >>> "rp": "autogen" >>> } >>> ], >>> "script": "// This TICKscript monitors the three temperatures for a >>> 3d printing job,\n// and triggers alerts if the temperatures start to >>> experience abnormal behavior.\n\n// Define our desired significance >>> level.\nvar alpha = 0.001\n\n// Select the temperatures measurements\nvar >>> data = stream\n |from()\n .measurement('temperatures')\n >>> |window()\n .period(5m)\n .every(5m)\n\ndata\n // Run our >>> tTest UDF on the hotend temperature\n @tTest()\n // specify the >>> hotend field\n .field('hotend')\n // Keep a 1h rolling >>> window\n .size(3600)\n // pass in the alpha value\n >>> .alpha(alpha)\n |alert()\n .id('hotend')\n .crit(lambda: >>> \"pvalue\" \u003c alpha)\n >>> .log('/tmp/test/hotend_failure.log')\n\n// Do the same for the bed and air >>> temperature.\ndata\n @tTest()\n .field('bed')\n >>> .size(3600)\n .alpha(alpha)\n |alert()\n .id('bed')\n >>> .crit(lambda: \"pvalue\" \u003c alpha)\n >>> .log('/tmp/test/bed_failure.log')\n\ndata\n @tTest()\n >>> .field('air')\n .size(3600)\n .alpha(alpha)\n |alert()\n >>> .id('air')\n .crit(lambda: \"pvalue\" \u003c alpha)\n >>> .log('/tmp/test/air_failure.log')\n", >>> "vars": {}, >>> "dot": "digraph print_temps {\ngraph [throughput=\"0.00 >>> points/s\"];\n\nstream0 [avg_exec_time_ns=\"0\" ];\nstream0 -\u003e from1 >>> [processed=\"86402\"];\n\nfrom1 [avg_exec_time_ns=\"225.328µs\" ];\nfrom1 >>> -\u003e window2 [processed=\"86402\"];\n\nwindow2 >>> [avg_exec_time_ns=\"160.576µs\" ];\nwindow2 -\u003e tTest7 >>> [processed=\"288\"];\nwindow2 -\u003e tTest5 [processed=\"288\"];\nwindow2 >>> -\u003e tTest3 [processed=\"288\"];\n\ntTest7 >>> [avg_exec_time_ns=\"196.929082ms\" ];\ntTest7 -\u003e alert8 >>> [processed=\"214\"];\n\nalert8 [alerts_triggered=\"9\" >>> avg_exec_time_ns=\"9.05µs\" crits_triggered=\"6\" infos_triggered=\"0\" >>> oks_triggered=\"3\" warns_triggered=\"0\" ];\n\ntTest5 >>> [avg_exec_time_ns=\"179.950039ms\" ];\ntTest5 -\u003e alert6 >>> [processed=\"211\"];\n\nalert6 [alerts_triggered=\"4\" >>> avg_exec_time_ns=\"23.838µs\" crits_triggered=\"3\" infos_triggered=\"0\" >>> oks_triggered=\"1\" warns_triggered=\"0\" ];\n\ntTest3 >>> [avg_exec_time_ns=\"114.502568ms\" ];\ntTest3 -\u003e alert4 >>> [processed=\"214\"];\n\nalert4 [alerts_triggered=\"4\" >>> avg_exec_time_ns=\"43.406µs\" crits_triggered=\"2\" infos_triggered=\"0\" >>> oks_triggered=\"2\" warns_triggered=\"0\" ];\n}", >>> "status": "enabled", >>> "executing": true, >>> "error": "", >>> "stats": { >>> "task-stats": { >>> "throughput": 0 >>> }, >>> "node-stats": { >>> "alert4": { >>> "alerts_triggered": 4, >>> "avg_exec_time_ns": 43406, >>> "collected": 214, >>> "crits_triggered": 2, >>> "emitted": 0, >>> "infos_triggered": 0, >>> "oks_triggered": 2, >>> "warns_triggered": 0 >>> }, >>> "alert6": { >>> "alerts_triggered": 4, >>> "avg_exec_time_ns": 23838, >>> "collected": 211, >>> "crits_triggered": 3, >>> "emitted": 0, >>> "infos_triggered": 0, >>> "oks_triggered": 1, >>> "warns_triggered": 0 >>> }, >>> "alert8": { >>> "alerts_triggered": 9, >>> "avg_exec_time_ns": 9050, >>> "collected": 214, >>> "crits_triggered": 6, >>> "emitted": 0, >>> "infos_triggered": 0, >>> "oks_triggered": 3, >>> "warns_triggered": 0 >>> }, >>> "from1": { >>> "avg_exec_time_ns": 225328, >>> "collected": 86402, >>> "emitted": 86402 >>> }, >>> "stream0": { >>> "avg_exec_time_ns": 0, >>> "collected": 86402, >>> "emitted": 86402 >>> }, >>> "tTest3": { >>> "avg_exec_time_ns": 114502568, >>> "collected": 220, >>> "emitted": 214 >>> }, >>> "tTest5": { >>> "avg_exec_time_ns": 179950039, >>> "collected": 217, >>> "emitted": 211 >>> }, >>> "tTest7": { >>> "avg_exec_time_ns": 196929082, >>> "collected": 221, >>> "emitted": 214 >>> }, >>> "window2": { >>> "avg_exec_time_ns": 160576, >>> "collected": 86402, >>> "emitted": 864 >>> } >>> } >>> }, >>> "created": "2016-10-17T21:33:16.176203257-05:00", >>> "modified": "2016-10-18T10:28:00.685262934-05:00", >>> "last-enabled": "2016-10-18T10:28:00.685262934-05:00" >>> } >>> >> -- >> Remember to include the version number! 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