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Bandwidth Control on a Satellite Link, and What the Data Showed Next

By Bikram Bhujel

Network operations case study · October 2026

Bandwidth Control on a Satellite Link, and What the Data Showed Next

A research station in Kenya on satellite internet was using data at roughly twice its monthly budget. I applied controls remotely, then analysed 24 days of firewall reports to check whether they worked. They did not fully work, and the data showed why.

PlatformFortiGate · traffic shaping · DNS filter
PeriodSeptember – October 2026
My roleRemote analysis, firewall changes, two written reports
EnvironmentCIMMYT field research station, Kenya
~2× budgetUsage pace before any change
24 daysOf daily firewall reports combined into one analysis
934 GBUsed in those 24 days, with the real drivers identified
01 · The problem

A data budget running out halfway through the month.

The station's satellite plan has a monthly data budget, and usage was on pace for roughly twice that amount. Firewall reports for three and a half days showed about 110 GB used, between 27 and 37 GB a day, dominated by video and social media.

This post describes work I did in my role at CIMMYT. The network and equipment belong to CIMMYT; addresses, configurations, device names and the names of colleagues are left out on purpose. All figures come from my own project reports.
02 · First response

Throttle, don't block.

Video and social mediaThrottled to 2 Mbps instead of blocked. Staff sometimes need video for work, and hard blocks push people towards workarounds.
Business appsTeams, Zoom, email and other business categories left outside the throttle.
One social media appBlocked through DNS filtering, because the firewall's application signatures did not identify it.
Expected outcomeUsage of about 200–250 GB a month, with a commitment to check real data after a week or more.
03 · Follow-up analysis

Checking the result with 24 days of data.

Three weeks later I combined 24 daily firewall reports into one analysis. One day's report was missing, and the analysis says so instead of filling the gap.

Expected

Monthly usage200–250 GB
Main driverVideo and social media

Measured

Usage in 24 days934 GB
Average per day38.9 GB
Working-day average53.8 GB
Projected per 30 daysabout 1,167 GB

The throttle worked on the traffic it targeted, but that traffic was not the main cause.

04 · What was really using the data

Cloud uploads and personal devices.

01
Two laptops bulk-uploading to cloud storage

134 GB of uploads to OneDrive and SharePoint, 126 GB of it in a single day.

Largest single driver
02
Many personal devices

About 271 devices on a working day, mostly personal phones on the Wi-Fi.

Volume
03
Video, app updates and social media

Still present, but reduced by the throttle.

Background
05 · Recommendations

Specific next steps instead of a general warning.

  • Contact the two heavy uploaders and agree a schedule or limit for cloud sync
  • Apply per-device limits on the network used by personal phones
  • Identify two unknown high-usage devices
  • Investigate two unidentified destinations
  • Keep the existing app and betting-site blocks
  • Confirm the satellite plan's limits with the provider
  • Fix the missing daily report so future analysis has complete data
These were recommendations at the time of writing; their outcome is not covered in this post.
06 · Lessons

Why I include a fix that did not fully work.

01
Measure after the change.

The first fix was reasonable, but only the follow-up data showed it targeted the wrong traffic.

02
Look at uploads, not just downloads.

Cloud backup and sync can use more data than all the video on the network.

03
Say what is missing.

Stating that one day of data was missing made the analysis more trustworthy, not less.

Comments

Questions and corrections are welcome. I read every comment before it appears, and remove spam and promotional links.