Taming daily data transfers at scale

Managing IT operations across a large retail network comes with unique challenges. When every store needs to send sales data to headquarters every morning, things can quickly become chaotic. We recently spoke with a CIO from a supermarket chain who shared how CTFreak transformed their daily data transfer operations.

Can you describe your role and the challenge you were facing?

I’m the CIO for a supermarket chain with several hundred stores across Europe. Every morning, each store needs to upload the previous day’s sales data to a central SFTP server. This data is then aggregated and used by both our accounting and business intelligence teams. It’s a critical process because delays or missing data directly impact financial reporting and decision making.

Before CTFreak, we had a homegrown solution where each store’s server was responsible for triggering its own data export. This meant configuring the transfer schedule individually on hundreds of servers. When something failed (and it did!), we had to either contact the store or connect remotely to restart the process and check the logs. With logs scattered across hundreds of servers, troubleshooting was a nightmare. We were constantly firefighting instead of improving our infrastructure.

The biggest issue was load spikes. When you have hundreds of stores potentially sending files at the same time, even if you stagger the schedules, file sizes vary significantly. This caused regular interruptions on our SFTP server, which then required manual intervention on multiple stores.

What made you choose CTFreak and how did you implement it?

I wanted two things: centralized triggering of the transfers instead of leaving it to each store, and centralized logging so my team wouldn’t have to connect to individual servers just to see what happened. That’s when I found CTFreak.

We configured a node in CTFreak for each store server and created a single Bash script task that runs every morning to export data to our SFTP server. The task executes across all nodes, but the key was using the workers feature. Instead of risking simultaneous exports from hundreds of stores, we limited execution to 80 workers. This means at any given moment, no more than 80 stores are actively transferring data. The SFTP server now handles a steady, predictable load instead of erratic spikes. We haven’t had a single interruption caused by overload since implementing this.

Network issues still happen, that’s unavoidable. But now when a transfer fails, I can see it immediately in CTFreak’s centralized interface and relaunch the task only on the stores that failed. No more connecting to individual servers, no more calling stores.

The migration took about three weeks to fully configure CTFreak and migrate all stores to the new system. Given the scope of several hundred nodes, that was faster than we expected.

What benefits have you seen since the migration?

The time savings alone justified the switch. We’re saving several hours per week, easily. The time we used to spend connecting to servers, checking logs, coordinating with stores, and manually restarting jobs is now almost zero. My team can focus on actual improvements instead of daily firefighting.

I travel frequently, and being able to monitor and manage everything from my phone has been invaluable. The interface is fully functional on mobile, so I can check status, review logs, or relaunch failed tasks from anywhere. That mobility aspect was not something I specifically looked for initially.

Given how reliable the tool has proven, we’re now progressively migrating all our batch processes across the company to CTFreak. We’ve also set up Slack notifications, so the relevant teams get alerted immediately when something needs attention. What started as a solution for one specific pain point is becoming our standard for all scheduled operations.

Any advice for other IT leaders facing similar challenges?

If you’re managing distributed infrastructure and spending too much time on manual coordination, centralization is the answer. CTFreak gave us visibility and control we simply didn’t have before. The workers feature alone was worth the switch for our use case.

This interview has been edited for clarity. The customer requested to remain anonymous due to company policy.