Hi, I'm new to kapacitor. I tried to follow the steps in custom anomaly 
detection example 

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!
You received this message because you are subscribed to the Google Groups 
"InfluxData" group.
To unsubscribe from this group and stop receiving emails from it, send an email 
to influxdb+unsubscr...@googlegroups.com.
To post to this group, send email to influxdb@googlegroups.com.
Visit this group at https://groups.google.com/group/influxdb.
To view this discussion on the web visit 
For more options, visit https://groups.google.com/d/optout.

Reply via email to