A sharp jump in MTU in one day

We are on Scholarship Plan at 200k MTU.

Last several months we had a sharp jump in MTU in one day. It looks like this (green line):

When I asked support manager about the situation, she suggested us start by going through this article and look especially at any anonymous user jumps we might have.

I asked my developer to check and he didn’t find any problems.

Could you help me to investigate and fix the problem? It’s super important for me since I have already had 2 overruns of MTU because of this problem. Next time my account will be blocked.

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JennRu

Hi ivanb following back up here, our team investigated this further and identified both projects were backfilling events for prior months. However for a unique user in June that is backdated for previous months (say April), it is treated as an additional MTU that is counted in June, the month they are received in.

Please review the stacked bar charts below to identify data that was backfilled for previous months. We count MTUs based on the server upload time (i.e. when Amplitude ingests the data). The unique user counts from the blue bars add up to the total June MTU count, and the unique user counts from the green bars add up to the total July MTU count.

Production project: https://app.amplitude.com/analytics/bloodoxygenapp/chart/8smboxit

Dev project: https://app.amplitude.com/analytics/bloodoxygenapp/chart/8smboxit/edit/wa6saboc

Would your developer be able to share more details on how they’re sending these events to Amplitude with older timestamps? Typically when we see backfilled data, the library source utilizes our batch api but that doesn’t appear to be the case for this data.

Let us know if your engineer can share further information on that. In the meantime, I’ll update the article to include counting backfilled data.

All comments

JennRu

Hi ivanb thank you for reaching out here. Could you please share your Amplitude org id, or a hyperlink to your org settings page? I can help investigate this week.

ivanb

Hi JennRu. My Org ID 199285. Link. Thank you!

JennRu

Hi ivanb the Amplitude team is still investigating this. I surfaced this to a few additional team members to see if anyone can share more details. What I’ve found so far

I built this chart in the main Prod project to investigate any noticeable spikes in the data on a daily trend among users performing any event, segmented by
- anonymous users
- identified users
- all users
I modified the chart to monthly to get end-of-month counts [chart] and broke it up individually by
- June [chart]
- July [chart]
I also tried summing up the unique device ID’s from anonymous users with the identified users for each month
- June [chart] - this sum was the closest to the max MTU limit
- July [chart]
I conducted a similar comparison in the Dev project [chart]
I verified none of your projects had logged any drop filters
I verified the libraries in which data is being sent to amplitude [chart] to verify there were no undercounted identify calls from upstream CDPs, such as segment

I can’t conclude anything just yet, as there might be something I’m missing on how we received data vs how we can report on it in this chart type. I’ll respond back here as soon as we hear back from the team.

JennRu

Production project: https://app.amplitude.com/analytics/bloodoxygenapp/chart/8smboxit

Dev project: https://app.amplitude.com/analytics/bloodoxygenapp/chart/8smboxit/edit/wa6saboc

Let us know if your engineer can share further information on that. In the meantime, I’ll update the article to include counting backfilled data.

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