WEBVTT 00:00.090 --> 00:00.580 Excellent. 00:00.690 --> 00:06.300 So we have this we have telegraph running on the influx based server, and it's connecting to three 00:06.300 --> 00:12.540 different S&P Demons one local one on Mega-fauna server, which is 10 one three three zero three and 00:12.540 --> 00:15.440 one of my Moscow 10 one three three zero four. 00:15.450 --> 00:21.030 The Telegraph is requesting data from each of the SMP days, using UDP on four one six one. 00:21.040 --> 00:26.520 So I've created firewall rules on each of those servers to allow the IP address of this influx DB server, 00:26.550 --> 00:30.890 because that's where Telegraph is running to connect to those SMP demons and request. 00:30.900 --> 00:31.870 Okay, so that works. 00:31.890 --> 00:37.290 So just to prove that I'm on my influx DB server, I can run an SNP walk command. 00:40.890 --> 00:45.450 Do S&P walk Virgin to public on my local computer and I'll get a response. 00:45.720 --> 00:50.520 I can also run that for the cafe on a server there 10 one three three zero three. 00:52.180 --> 00:53.290 And that gets a response. 00:54.400 --> 00:56.710 Also, the same for 10 one three three zero four. 00:57.970 --> 01:02.770 There's a response now each of the S&P Demons on those servers was configured to return. 01:04.220 --> 01:11.060 Our kids starting at that prefix, that's much more data than would be returned if I just had those 01:11.060 --> 01:15.230 two configured, because that also includes that and that. 01:16.160 --> 01:17.060 Plus a lot more. 01:17.540 --> 01:23.870 And also, one telegraph configuration is hauling each of those three S&P diamonds because you can also 01:23.870 --> 01:30.920 verify that in influx DB by going to the Explore tab in your influx DB select interface. 01:33.120 --> 01:35.850 Search for source and I can see my three service. 01:37.070 --> 01:43.120 Excellent set now means I can import a pre-built dashboard, so on my documentation import and Typekit 01:43.130 --> 01:46.730 dashboard for influx DB and telegraph this year this fall, Jason here. 01:46.760 --> 01:48.620 Copy that that's copied to Clipboard. 01:48.630 --> 01:55.370 Go into Safana dashboards, manage import, paste that into their and press load. 01:55.550 --> 01:57.260 It's called snappy interfaces. 01:57.380 --> 01:57.920 Import. 01:58.700 --> 02:02.190 OK, now I'm going to set that down to last five minutes. 02:02.450 --> 02:06.020 OK, so we have some things already set up for us. 02:06.020 --> 02:06.680 So up here. 02:06.720 --> 02:11.920 Influx DB mice will bafana it found those automatically that's using a dashboard variable. 02:11.930 --> 02:13.890 We'll look into that in future videos. 02:13.910 --> 02:14.990 There is a table here. 02:15.020 --> 02:15.910 Easy to edit. 02:15.920 --> 02:20.600 You can use these queries as reference if you want to create your own dashboards from different influx 02:20.600 --> 02:22.040 DB data sources. 02:22.070 --> 02:25.820 The important thing here is this map line here for just delete that. 02:25.970 --> 02:28.250 Then the headings don't look so right. 02:28.250 --> 02:29.540 So if I just put that back. 02:30.980 --> 02:32.840 Then the column headings look much better. 02:33.230 --> 02:37.340 These are the ones I'm looking for in Octopussy for each device. 02:37.430 --> 02:41.290 If I press a to edit that, it's not one I'm using map again down here. 02:41.300 --> 02:46.790 So if I just delete that, then all the series names are quite long and hard to read. 02:46.790 --> 02:51.350 So I'm using the map function down here to make the series names much smaller. 02:51.560 --> 02:57.410 It's also using what's called a derivative non-negative, and that is making the graph shows differences 02:57.410 --> 02:58.580 between each timestamp. 02:58.580 --> 03:04.490 Support took that away and zoomed out six hours, maybe 12 hours. 03:04.820 --> 03:09.290 It's just forever increasing, so that's what the non-negative derivative is doing, showing us the 03:09.290 --> 03:09.890 difference. 03:10.340 --> 03:12.680 Can I put that back to five minutes apply. 03:12.710 --> 03:16.310 Then you can see that I'm just looking at different interface properties on these crops up time. 03:16.520 --> 03:19.070 So each of my different services have a different up time. 03:19.490 --> 03:21.860 I'm doing mathematical equation on the result. 03:21.860 --> 03:23.150 They're using the map function. 03:23.150 --> 03:25.550 So I took that away shows that this is incorrect. 03:25.880 --> 03:26.390 That's better. 03:26.900 --> 03:32.180 So use those queries and the queries from the other influx DB dashboard as well that we imported earlier. 03:32.180 --> 03:35.390 So that was influx DB system there as reference. 03:35.420 --> 03:41.420 Note, though, that influx DB too, since it uses the flux query language is much more complicated 03:41.420 --> 03:43.210 than the old influx que el query language. 03:43.220 --> 03:48.350 If you look on dashboards on Gravano, you'll notice there aren't very many dashboards for influx DB 03:48.350 --> 03:48.710 to. 03:48.710 --> 03:51.590 I think a lot of people struggle with influx DB to be aware of that. 03:51.650 --> 03:52.510 It's not easy. 03:52.520 --> 03:57.610 You might have to find a specialized course in influx DB to if you want to continue with it. 03:57.620 --> 03:58.670 And also another thing too. 03:58.670 --> 04:00.370 I found it quite fragile. 04:00.380 --> 04:06.230 If you do queries for six hours or more, the influx DB server starts to slow down very, very quickly. 04:06.260 --> 04:07.550 Not always, but occasionally. 04:07.550 --> 04:13.040 Sometimes you have to go onto the server and restart the service, so keep your influx DB queries shorter 04:13.040 --> 04:16.330 time spans while you're setting them up or experimenting. 04:16.340 --> 04:23.420 So it's not that influx DB one wasn't such a fancy system didn't come with an in-built fancy user interface 04:23.420 --> 04:25.390 like this, and the crude language was much simpler. 04:25.400 --> 04:26.900 But as you can see, it's come a long way. 04:26.930 --> 04:29.750 For example, data here got a lot of choices. 04:31.380 --> 04:34.860 But just be aware that influx, Debbie, is quite complicated in itself. 04:35.020 --> 04:40.290 So you may need to do a specialized course in it anyway, so there's plenty of information for you to 04:40.320 --> 04:43.080 use as a reference if you continue with the influx, Debbie. 04:43.080 --> 04:43.950 So excellent.