Meeting Title: Demilade Agboola’s Zoom Meeting Date: 2025-06-05 Meeting participants: Demilade Agboola, Ryan Luke Daque, Annie Yu


WEBVTT

1 00:00:41.930 00:00:43.520 Ryan Luke Daque: Hello! Again.

2 00:00:44.420 00:00:45.410 Annie Yu: Hello!

3 00:00:47.940 00:00:50.890 Demilade Agboola: It’s been so long welcome back.

4 00:00:51.970 00:00:53.969 Ryan Luke Daque: Yeah. It’s been a while.

5 00:00:59.625 00:01:09.230 Demilade Agboola: Alright. So this is the look that I’m trying to to see.

6 00:01:09.480 00:01:11.689 Ryan Luke Daque: Orders placed by Rot.

7 00:01:11.870 00:01:13.080 Demilade Agboola: Yeah.

8 00:01:16.970 00:01:19.536 Demilade Agboola: Sorry orders placed by holiday.

9 00:01:37.690 00:01:44.910 Demilade Agboola: and I think it’s using Ops in.

10 00:01:53.780 00:01:57.759 Demilade Agboola: It’s an awful basic load. I think that’s the annoying part like, if it was

11 00:01:59.560 00:02:01.910 Demilade Agboola: alphabetical, that would be very helpful.

12 00:02:03.090 00:02:03.880 Ryan Luke Daque: Yeah.

13 00:02:32.550 00:02:33.970 Demilade Agboola: It frustrates.

14 00:02:34.990 00:02:40.470 Demilade Agboola: I can’t wait till we delete, like so many of the unnecessary stuff.

15 00:02:42.180 00:02:47.060 Ryan Luke Daque: Yeah, imagine, like, I can’t imagine the 2,000 looks.

16 00:02:47.560 00:02:49.060 Demilade Agboola: Yeah, it’s just.

17 00:02:50.830 00:02:53.989 Demilade Agboola: And the thing is like they’ve never really stopped to like.

18 00:02:54.100 00:03:04.760 Demilade Agboola: go through stuff and see like what what’s working and like, you know, maintain stuff and audit stuff and prune things and get rid of stuff. So just keep building forward.

19 00:03:07.010 00:03:09.709 Annie Yu: That mean? They’re pretty technical.

20 00:03:11.500 00:03:21.590 Demilade Agboola: I would. I wouldn’t necessarily agree with that, because part of being technical is like, you shouldn’t have 2,000 looks.

21 00:03:22.320 00:03:25.760 Demilade Agboola: I suppose? Yeah, yeah, so.

22 00:03:29.250 00:03:33.449 Demilade Agboola: but yeah, it’s a it’s a so I bring the Dbt person left.

23 00:03:33.690 00:03:37.499 Demilade Agboola: And so someone who was like working in

24 00:03:38.122 00:04:04.689 Demilade Agboola: I mean, Emily used to work in, I think, cost account, but I think customer relations I’m not sure but she used to like do that. The analysis for that kind of stepped into like full time running all of this. So it’s like there isn’t necessarily there hasn’t been like. And the person who left, you know, basically left the shit show. So Emi has just been basically trying to make sense of every single thing that’s happening. But like Dvc. Has strongest suits.

25 00:04:05.835 00:04:11.919 Demilade Agboola: So it’s just a mess, and I think that affected their on Valentine’s Day sales

26 00:04:12.200 00:04:18.040 Demilade Agboola: because they sell flowers. And so Valentine’s Day and Mother’s Day are some of their like their 2 biggest days.

27 00:04:19.260 00:04:19.940 Annie Yu: Yeah.

28 00:04:20.120 00:04:28.380 Demilade Agboola: So going forward, we’re trying to like help them, just like build properly

29 00:04:30.270 00:04:35.940 Demilade Agboola: but their focus before was just finalized, and ensuring that that worked one.

30 00:04:38.210 00:04:40.922 Annie Yu: Is there another one we can try.

31 00:04:41.580 00:04:47.160 Demilade Agboola: I mean, there’s a couple more there. They’re not too many, I mean.

32 00:04:48.510 00:04:51.509 Demilade Agboola: Obviously their looks don’t matter to them. But like

33 00:04:55.950 00:04:59.170 Demilade Agboola: just one of those things, looker.

34 00:04:59.860 00:05:02.720 Demilade Agboola: So that’s hourly sales dash

35 00:05:06.160 00:05:13.179 Demilade Agboola: as orders placed by our let’s look at our sales dashboards if we can find out.

36 00:05:14.840 00:05:17.060 Demilade Agboola: So I think that’s an actual dashboard.

37 00:05:31.340 00:05:33.469 Demilade Agboola: Is this the same dashboard?

38 00:05:36.670 00:05:38.530 Demilade Agboola: Let’s see.

39 00:06:14.480 00:06:17.470 Demilade Agboola: And I think this is it?

40 00:06:23.853 00:06:31.389 Demilade Agboola: Come on so what do I?

41 00:06:35.460 00:06:38.170 Demilade Agboola: Alright, I think I’ve clicked this. What else I.

42 00:06:44.556 00:06:45.650 Annie Yu: And then.

43 00:06:46.240 00:06:47.699 Demilade Agboola: Go ahead month or so.

44 00:06:52.270 00:06:53.190 Demilade Agboola: Hi, Luke.

45 00:06:57.360 00:07:00.359 Ryan Luke Daque: Oh, sorry I was on mute. But yeah, and.

46 00:07:01.400 00:07:02.120 Demilade Agboola: I don’t know exactly what.

47 00:07:02.120 00:07:03.070 Ryan Luke Daque: Good morning!

48 00:07:03.880 00:07:04.919 Demilade Agboola: 12 years.

49 00:07:04.920 00:07:12.660 Ryan Luke Daque: The only yeah, it looks like that’s the only available monitor for looker. It looks like, because interesting

50 00:07:12.660 00:07:14.039 Ryan Luke Daque: Eden, there was.

51 00:07:14.290 00:07:23.790 Ryan Luke Daque: There was source freshness, basically that we needed, which doesn’t seem to be there.

52 00:07:26.135 00:07:27.130 Demilade Agboola: Interesting.

53 00:07:27.410 00:07:31.719 Demilade Agboola: Let’s see. I wonder if it’s just if it’s just sitting on this dashboard.

54 00:07:32.310 00:07:47.379 Demilade Agboola: Or if okay, let’s see if looks have different like volunteer that we can see.

55 00:07:48.060 00:07:50.760 Annie Yu: What’s the difference between looker and looks.

56 00:07:53.910 00:07:55.879 Demilade Agboola: You mean a dash on a look right

57 00:07:59.860 00:08:01.429 Demilade Agboola: like the dashboard, and you look.

58 00:08:03.390 00:08:04.700 Annie Yu: Oh, what does that mean?

59 00:08:08.400 00:08:11.009 Demilade Agboola: Like in looker you can have dash.

60 00:08:11.230 00:08:13.910 Demilade Agboola: so look at is not my favorite tool to be honest.

61 00:08:14.180 00:08:18.340 Demilade Agboola: but you can have looks. You can have explores.

62 00:08:18.550 00:08:20.830 Demilade Agboola: and you can have dashboards or something.

63 00:08:22.440 00:08:27.769 Demilade Agboola: So like the look is kind of like a tableau, like single sheet sort of concept.

64 00:08:29.310 00:08:32.570 Demilade Agboola: Well, like a dashboard, is like a collection of like looks.

65 00:08:32.980 00:08:34.720 Annie Yu: Oh, okay. Okay.

66 00:08:36.409 00:08:37.159 Demilade Agboola: Stuff.

67 00:08:39.789 00:08:43.710 Ryan Luke Daque: But yeah, it looks like, maybe just try a random one.

68 00:08:44.100 00:08:49.279 Ryan Luke Daque: Yeah, add add monitor type. Maybe that’s the only one that they have total views.

69 00:08:49.710 00:08:53.060 Ryan Luke Daque: Yeah, that’s not very helpful. I would think right.

70 00:08:53.230 00:08:54.779 Demilade Agboola: Yeah, I don’t think that’s very helpful.

71 00:08:54.780 00:08:59.129 Ryan Luke Daque: Yeah, it’s just like how many viewed. But I guess that can

72 00:08:59.970 00:09:04.150 Ryan Luke Daque: that can show us which dashboards aren’t being used out of the app.

73 00:09:05.530 00:09:10.730 Ryan Luke Daque: Or maybe it’s because it’s a look. Maybe if it’s a dashboard, then it has a floor specialist.

74 00:09:10.730 00:09:12.009 Demilade Agboola: Yeah, but I I.

75 00:09:12.010 00:09:12.800 Ryan Luke Daque: That’s done.

76 00:09:12.800 00:09:14.159 Demilade Agboola: I checked the dash as well, thought.

77 00:09:14.160 00:09:15.480 Ryan Luke Daque: Oh, it’s the same.

78 00:09:15.480 00:09:16.610 Demilade Agboola: Yeah, it’s the same.

79 00:09:17.160 00:09:19.349 Ryan Luke Daque: Oh, that’s yeah. That sucks.

80 00:09:19.900 00:09:23.660 Ryan Luke Daque: Yeah. It’s not very helpful. Then.

81 00:09:23.660 00:09:24.100 Demilade Agboola: Yeah.

82 00:09:24.100 00:09:25.290 Ryan Luke Daque: This case.

83 00:09:29.030 00:09:29.830 Ryan Luke Daque: Yeah.

84 00:09:30.270 00:09:36.780 Ryan Luke Daque: And maybe we we don’t do any looker monitors.

85 00:09:39.460 00:09:42.399 Demilade Agboola: Yeah, we’ll see. Oh, maybe I don’t know.

86 00:09:44.010 00:09:45.440 Demilade Agboola: Where did you?

87 00:09:45.750 00:09:50.690 Demilade Agboola: Where did you add things in the stock data stack.

88 00:09:50.690 00:09:54.369 Ryan Luke Daque: Yeah, that one. So you can add connection there at the top. Right? Yeah.

89 00:09:54.750 00:10:00.560 Ryan Luke Daque: Anything else that we can add, I guess.

90 00:10:01.960 00:10:05.319 Ryan Luke Daque: Like, there’s 5 grand Within haven’t tried that.

91 00:10:05.790 00:10:07.980 Ryan Luke Daque: If they’re using like 5 grand.

92 00:10:08.880 00:10:11.310 Demilade Agboola: No, no, they’re not using 5. Tran.

93 00:10:11.920 00:10:12.950 Ryan Luke Daque: Oh, okay.

94 00:10:13.370 00:10:18.329 Demilade Agboola: It’s just this interesting.

95 00:10:18.330 00:10:22.470 Annie Yu: The Dbt. Cloud was successful, though.

96 00:10:23.690 00:10:24.920 Ryan Luke Daque: Yeah, can we check that?

97 00:10:27.450 00:10:28.330 Ryan Luke Daque: Right?

98 00:10:28.925 00:10:29.520 Annie Yu: Wait.

99 00:10:29.520 00:10:30.699 Ryan Luke Daque: Oh, yeah. Nice.

100 00:10:31.287 00:10:34.892 Annie Yu: Looks like it. Yeah. So yeah, it was able to see all the

101 00:10:35.930 00:10:38.050 Ryan Luke Daque: Recent job runs.

102 00:10:39.320 00:10:41.600 Ryan Luke Daque: The testing models.

103 00:10:42.150 00:10:44.669 Ryan Luke Daque: And that’s like the job duration.

104 00:10:45.490 00:10:46.250 Demilade Agboola: Yeah.

105 00:10:46.900 00:10:50.080 Ryan Luke Daque: For each of the job. Run the best 7 days.

106 00:10:50.600 00:10:53.240 Ryan Luke Daque: Yeah, that’s like one spike. For some reason.

107 00:10:53.480 00:10:54.030 Demilade Agboola: Yeah.

108 00:10:54.030 00:10:56.759 Ryan Luke Daque: 1 min to like 4 min or something.

109 00:10:57.370 00:10:59.950 Demilade Agboola: Yeah, 4 h.

110 00:11:00.690 00:11:03.389 Ryan Luke Daque: Hours. Yeah, that’s that’s weird.

111 00:11:07.370 00:11:12.419 Demilade Agboola: Last 30 days, and it’s a big client.

112 00:11:13.020 00:11:14.410 Ryan Luke Daque: 2 h here.

113 00:11:14.410 00:11:19.400 Demilade Agboola: Yeah, in 2 min was back to 6 min.

114 00:11:21.180 00:11:21.930 Ryan Luke Daque: Cool.

115 00:11:24.230 00:11:24.925 Demilade Agboola: Yeah.

116 00:11:25.780 00:11:28.509 Ryan Luke Daque: Yeah. And then we can also add monitors there.

117 00:11:31.880 00:11:32.690 Ryan Luke Daque: Yeah.

118 00:11:34.220 00:11:35.330 Ryan Luke Daque: And

119 00:11:39.640 00:11:40.730 Ryan Luke Daque: yeah, that’s the weekend.

120 00:11:40.730 00:11:41.850 Ryan Luke Daque: Alright source.

121 00:11:42.640 00:11:45.679 Annie Yu: Already there from from Dbt.

122 00:11:46.980 00:11:48.769 Ryan Luke Daque: Yeah, it. Looks like it.

123 00:11:49.740 00:11:50.540 Demilade Agboola: Yeah.

124 00:11:52.170 00:11:58.710 Ryan Luke Daque: So those those are all all the models looks like, and the tests all of them would be there.

125 00:12:02.380 00:12:05.629 Ryan Luke Daque: I guess, if you also use like semantic layers.

126 00:12:06.670 00:12:12.020 Ryan Luke Daque: semantic models, and stuff like that should also theoretically be there.

127 00:12:15.580 00:12:18.530 Demilade Agboola: So add monitors, job monitors.

128 00:12:23.940 00:12:27.710 Ryan Luke Daque: Just maybe select one.

129 00:12:28.090 00:12:29.921 Demilade Agboola: Okay, let me, just

130 00:12:30.380 00:12:35.619 Ryan Luke Daque: Just do a random one are are those all.

131 00:12:36.130 00:12:38.480 Ryan Luke Daque: or maybe choose a March model? One

132 00:12:39.010 00:12:44.450 Ryan Luke Daque: cause I don’t think we want to add, like staging a monitor still staging.

133 00:12:44.680 00:12:45.500 Ryan Luke Daque: That’s.

134 00:12:46.580 00:12:49.769 Demilade Agboola: Sure. But I mean, almost like all things, run like

135 00:12:52.040 00:12:55.770 Demilade Agboola: all like from stage into March, like the jobs.

136 00:12:57.860 00:12:59.179 Ryan Luke Daque: Oh, those are jobs.

137 00:12:59.180 00:13:00.410 Demilade Agboola: Yeah, these are jobs.

138 00:13:02.340 00:13:05.920 Ryan Luke Daque: Are there and then models

139 00:13:08.070 00:13:14.390 Ryan Luke Daque: showing looks like all our jobs. Yeah, so jobs. I guess we can only monitor the duration.

140 00:13:14.850 00:13:16.520 Demilade Agboola: Yeah.

141 00:13:20.590 00:13:21.560 Ryan Luke Daque: One month.

142 00:13:25.820 00:13:31.080 Ryan Luke Daque: I still wonder if it’s the unverified email, though.

143 00:13:32.570 00:13:36.179 Ryan Luke Daque: If I if I look at, let me log into the even one

144 00:13:42.520 00:13:45.699 Ryan Luke Daque: it’s in Eden we were able to see all the

145 00:13:49.820 00:13:51.090 Ryan Luke Daque: What do you call this?

146 00:13:52.000 00:13:53.340 Ryan Luke Daque: All the models.

147 00:13:54.970 00:14:00.390 Demilade Agboola: Yeah, maybe that’s it. Actually, it’s 1 local functionality.

148 00:14:10.620 00:14:19.709 Ryan Luke Daque: Oh, yeah, actually, let let me maybe share my screen. So you can see.

149 00:14:20.350 00:14:20.680 Ryan Luke Daque: Thanks.

150 00:14:20.680 00:14:24.689 Ryan Luke Daque: I mean in the in the Dvt, it’s also just the jobs.

151 00:14:26.120 00:14:27.840 Ryan Luke Daque: But in

152 00:14:30.880 00:14:32.089 Ryan Luke Daque: can you see my screen.

153 00:14:33.580 00:14:34.100 Annie Yu: Yep.

154 00:14:34.620 00:14:40.190 Ryan Luke Daque: So yeah, in Dbt, it’s only the jobs that’s also being monitored here.

155 00:14:40.500 00:14:42.529 Ryan Luke Daque: So just the duration

156 00:14:43.510 00:14:50.129 Ryan Luke Daque: but here in the data warehouse in this case, in bigquery this is where we see all the models.

157 00:14:50.940 00:14:53.520 Ryan Luke Daque: and this is where we can set up

158 00:14:54.150 00:15:01.750 Ryan Luke Daque: like row count monitors, whether there’s like an increase or sudden decrease in row, counts

159 00:15:02.721 00:15:09.910 Ryan Luke Daque: or bear within the standard deviation, or something like that like source freshness

160 00:15:10.410 00:15:15.239 Ryan Luke Daque: where we can add them. No, miss, tests which are like similar to

161 00:15:16.140 00:15:21.500 Ryan Luke Daque: what we have in DVD, we’re on this. But like this would be in like

162 00:15:22.230 00:15:27.890 Ryan Luke Daque: in terms of like anomaly detection as well. So it’s gonna be checking the number of nulls

163 00:15:29.090 00:15:31.510 Ryan Luke Daque: for a model or or for a table.

164 00:15:31.700 00:15:37.500 Ryan Luke Daque: And then if there’s a spike, I guess that’s gonna cause a warning or an error.

165 00:15:38.840 00:15:44.620 Ryan Luke Daque: So yeah, we can also have custom sequel tests as well.

166 00:15:47.080 00:15:51.690 Ryan Luke Daque: And it would be shown us a

167 00:15:54.020 00:15:58.370 Ryan Luke Daque: a normally detection type as well test.

168 00:15:58.920 00:16:00.510 Ryan Luke Daque: So yeah, it seemed to be like.

169 00:16:01.320 00:16:03.509 Ryan Luke Daque: if there’s a spike, then it’s whatever else.

170 00:16:06.400 00:16:12.980 Ryan Luke Daque: And yeah in tableau, you can see here, they’re using tableau. There’s like monitors for

171 00:16:14.720 00:16:18.640 Ryan Luke Daque: like data source extract, last update. So maybe this is like

172 00:16:18.800 00:16:26.790 Ryan Luke Daque: this is like a source specialist. That’s basically when the data sources last updating.

173 00:16:30.670 00:16:34.539 Ryan Luke Daque: yeah, and in the Cicd, this should be where.

174 00:16:35.090 00:16:38.339 Ryan Luke Daque: like once, maybe in urban stems, once that gets

175 00:16:38.870 00:16:42.679 Ryan Luke Daque: installed to Github, we should see all the Prs here.

176 00:16:42.920 00:16:46.350 Ryan Luke Daque: And like, yeah, this one. For example.

177 00:16:47.410 00:16:52.439 Ryan Luke Daque: you can see that the Pr ran through through tests

178 00:16:53.160 00:16:56.800 Ryan Luke Daque: which is like the impact preview and the test preview.

179 00:16:58.480 00:17:03.020 Ryan Luke Daque: Yeah, I guess impact preview would just

180 00:17:04.700 00:17:11.620 Ryan Luke Daque: show if there are impacting, it’s impacting like downstream models or like any dashboards

181 00:17:12.920 00:17:15.500 Ryan Luke Daque: stuff like that like this preview.

182 00:17:17.310 00:17:26.860 Ryan Luke Daque: Yeah, just I believe this is where it tests the before and after changes like that.

183 00:17:27.359 00:17:32.099 Ryan Luke Daque: There was no change in terms of their column count. But if a model

184 00:17:32.580 00:17:38.320 Ryan Luke Daque: that you if the Pr. Added a column to a model, and it should show the change here

185 00:17:39.120 00:17:41.880 Ryan Luke Daque: right compared to the main branch.

186 00:17:42.140 00:17:45.719 Ryan Luke Daque: So 8 main branch, there’s 8 columns, but in the

187 00:17:45.930 00:17:48.200 Ryan Luke Daque: in the branch for the Pr.

188 00:17:49.810 00:17:51.080 Ryan Luke Daque: It’ll be 9

189 00:17:51.300 00:17:57.768 Ryan Luke Daque: columns, and there would be a percent change here. Same with the row, count and stuff like that. So this would be great.

190 00:17:59.190 00:18:07.889 Ryan Luke Daque: especially when, like the the update is like joining some stuff or like changing some business logic. And suddenly, we have like duplicate

191 00:18:08.210 00:18:13.370 Ryan Luke Daque: columns or duplicate records. Then we’d be able to see it here

192 00:18:13.640 00:18:15.730 Ryan Luke Daque: that, like the numbers change or something.

193 00:18:17.510 00:18:18.330 Ryan Luke Daque: See ya.

194 00:18:19.080 00:18:20.220 Demilade Agboola: That’s pretty cool.

195 00:18:21.380 00:18:29.319 Ryan Luke Daque: And this also shows in the Pr app itself. So if we go to the Pr this specific branch.

196 00:18:29.980 00:18:32.019 Ryan Luke Daque: yeah, it would show up here.

197 00:18:32.400 00:18:34.770 Ryan Luke Daque: The impact be where that has been.

198 00:18:36.170 00:18:36.690 Demilade Agboola: Nice.

199 00:18:36.690 00:18:41.490 Ryan Luke Daque: That’d be great. Yeah, nice.

200 00:18:41.740 00:18:44.490 Demilade Agboola: Do you have any idea how much Meta plan costs or.

201 00:18:44.490 00:18:49.199 Ryan Luke Daque: That’s a good question. That’s I. Because, like in their pricing model

202 00:18:50.420 00:18:58.559 Ryan Luke Daque: it there we did. Didn’t really mention it, but I see pricing.

203 00:18:59.430 00:19:02.990 Ryan Luke Daque: But they said, It’s like per table or something

204 00:19:04.860 00:19:11.279 Ryan Luke Daque: usage base. Yeah. So it’s pay for what you use. So pay per table monitor. So

205 00:19:11.860 00:19:13.600 Ryan Luke Daque: I don’t know how much that is.

206 00:19:14.890 00:19:25.880 Ryan Luke Daque: So I actually asked, like, Yeah, I wish we can have another call with meta plane. So we can discuss this. Maybe I don’t know. Maybe that needs to be in that call as well to this, like

207 00:19:26.120 00:19:29.870 Ryan Luke Daque: maybe even ask for discounts or whatever.

208 00:19:30.650 00:19:33.379 Ryan Luke Daque: Yeah, they’re not seeing how much it costs

209 00:19:37.870 00:19:45.279 Ryan Luke Daque: the free tier can only go up to 10 tables, one very, very low. Yeah.

210 00:19:45.600 00:19:49.685 Demilade Agboola: 10 tables Is- is a side project, is not.

211 00:19:50.140 00:19:51.360 Ryan Luke Daque: Yeah. Exactly.

212 00:19:53.600 00:19:54.429 Ryan Luke Daque: See? Ya.

213 00:19:56.290 00:19:58.230 Demilade Agboola: Okay, interesting.

214 00:19:59.520 00:20:04.800 Ryan Luke Daque: It’s pretty cool, though, thank you. Especially this one. The Cicd test previews pretty great.

215 00:20:05.420 00:20:08.309 Demilade Agboola: Yeah, it is. That’s like, that’s really amazing.

216 00:20:08.960 00:20:09.550 Ryan Luke Daque: Yeah.

217 00:20:11.700 00:20:14.620 Ryan Luke Daque: Remind me again, yeah. Yeah, go ahead.

218 00:20:15.186 00:20:22.120 Annie Yu: The was that manually set up, or that was also like, and the default.

219 00:20:23.850 00:20:28.180 Ryan Luke Daque: Yeah, we set this up. So we connected Github right?

220 00:20:28.959 00:20:33.899 Ryan Luke Daque: And in the Dbt part where is it?

221 00:20:35.160 00:20:36.490 Ryan Luke Daque: Message here?

222 00:20:38.800 00:20:42.970 Ryan Luke Daque: Oh, yeah, it’s just yeah. It’s just

223 00:20:44.070 00:20:47.190 Ryan Luke Daque: set up here. Well, actually, we did some

224 00:20:49.160 00:20:57.949 Ryan Luke Daque: updates the workflow so that we, the Pr can send the metadata to Meta plane. So if you look at the

225 00:20:59.900 00:21:08.960 Ryan Luke Daque: the workflow for Eden, yeah, in today.

226 00:21:09.240 00:21:11.789 Ryan Luke Daque: So we added this portion here.

227 00:21:18.700 00:21:28.969 Ryan Luke Daque: yeah, this one, so that it can report report the Dbt run that had happened prior.

228 00:21:29.350 00:21:30.870 Ryan Luke Daque: So this one.

229 00:21:32.040 00:21:40.969 Ryan Luke Daque: the Dvt test DVD sources the run Dvt part so it can report the output of that to Meta plane, basically.

230 00:21:41.330 00:21:46.909 Ryan Luke Daque: And I just basically copy and pasted whatever the documentation said.

231 00:21:48.570 00:21:55.199 Ryan Luke Daque: So yeah, just added this to the secret Github secrets as well.

232 00:21:55.730 00:22:00.969 Ryan Luke Daque: The token and the connection. Id, so this is basically the

233 00:22:01.390 00:22:05.960 Ryan Luke Daque: manual part, so that we can send

234 00:22:06.830 00:22:09.099 Ryan Luke Daque: data to report it to Meta plane.

235 00:22:09.990 00:22:14.280 Ryan Luke Daque: And this is the part where it triggers, comments through. It.

236 00:22:14.630 00:22:16.969 Ryan Luke Daque: shows up in the Pr itself.

237 00:22:21.630 00:22:22.395 Annie Yu: God.

238 00:22:29.290 00:22:29.870 Ryan Luke Daque: You know.

239 00:22:30.700 00:22:32.410 Ryan Luke Daque: But yeah, that’s about it.

240 00:22:34.320 00:22:38.040 Ryan Luke Daque: So maybe I don’t know. Maybe we can try to

241 00:22:39.230 00:22:43.670 Ryan Luke Daque: like once we get the access for the Cic D 4

242 00:22:44.560 00:22:47.779 Ryan Luke Daque: organ stems we can set by setting that up

243 00:22:50.770 00:22:53.479 Ryan Luke Daque: and also once we get access to redshift.

244 00:22:53.730 00:22:58.110 Ryan Luke Daque: then we can add, like monitors like like here.

245 00:22:59.110 00:23:02.049 Demilade Agboola: Okay, I’ll try. I’ll try and do the redshift

246 00:23:02.320 00:23:11.199 Demilade Agboola: like cli, like at least an Api stuff today or actually not today. It’s like 1030 my time, but like tomorrow.

247 00:23:11.858 00:23:15.690 Demilade Agboola: and just see what progress we’re able to make on that.

248 00:23:17.400 00:23:18.254 Ryan Luke Daque: Nice, sounds good.

249 00:23:18.750 00:23:19.470 Demilade Agboola: Okay.

250 00:23:20.750 00:23:22.210 Annie Yu: Thank you so much.

251 00:23:22.460 00:23:23.260 Demilade Agboola: And you guys.

252 00:23:23.260 00:23:26.010 Ryan Luke Daque: Yes, bye-bye.

253 00:23:26.110 00:23:27.740 Demilade Agboola: Alright, bye.