Why Your MongoDB Connection Is Eating Your SOCKS Proxy Bandwidth (And How to Fix It)

You opened your proxy dashboard expecting to see a quiet graph. Instead, you're looking at hundreds of megabytes of bandwidth consumed by what should be a lightly-used database connection. Nothing in your application logs explains it. Your HTTP traffic looks normal. What's going on?

This is a pattern we see regularly with MongoDB replica set connections routed through SOCKS proxies. The culprit isn't your application code. It's the MongoDB driver itself, doing exactly what it's designed to do.

How MongoDB Replica Set Heartbeats Work

The MongoDB driver maintains awareness of your replica set topology. To do this, it sends a lightweight heartbeat to each member of the replica set at regular intervals. By default, that interval is 10 seconds, though many configurations run at 30 seconds.

Each heartbeat is a small exchange. A few kilobytes at most. But when you multiply it across three replica set members, running continuously, 24 hours a day, it starts to add up.

At 30-second intervals across 3 replicas, you're looking at roughly 6 heartbeat roundtrips per minute. With wire protocol and TLS overhead, each exchange lands around 1.3 KB. That works out to approximately 200 KB per hour, per tunnel.

Over a month, that's roughly 140 MB of baseline traffic that has nothing to do with actual queries.

Why This Shows Up as Surprising in SOCKS Proxy Logs

If you're routing your MongoDB connections through a SOCKS proxy (common when your database sits behind a firewall allowlist), you'll see this traffic in your proxy logs.

QuotaGuard's log viewer emits a SOCKS BANDWIDTH entry every time another 1 MiB of real traffic passes through the proxy on a long-lived connection. To be clear, QuotaGuard does not enforce a 1 MiB minimum charge per connection; the 1 MiB increment is purely how our system batches and displays long-lived traffic data for the log viewer.

So, if you're routing 3 replica set tunnels through the proxy, you'll see these 1 MiB entries fire roughly every 5 hours per tunnel, even with zero application-level queries happening.

This trips up engineers because the bandwidth events look periodic and unexplained. The connection stays open. The entries keep firing. Nothing in the application is obviously responsible.

The key thing to understand: any bytes that pass through the proxy count toward bandwidth. That includes keepalives, TLS framing, and driver-level housekeeping traffic. The proxy has no way to distinguish "meaningful" query bytes from background protocol bytes. It just counts what passes through.

A Real Example

A customer recently came to us with exactly this pattern. They were seeing consistent ~1,024 KiB SOCKS BANDWIDTH events on long-lived MongoDB connections and couldn't explain the source. Their HTTP and router traffic showed nothing.

After working through the logging behavior with our support team, they traced it back to MongoDB driver heartbeats across their 3-node replica set. Each tunnel carrying a ~1.3 KB exchange every 30 seconds, with wire and TLS overhead, was accumulating to roughly 200 KB/hour per tunnel. That lined up precisely with the 1 MiB events they were seeing fire every ~5 hours.

Once they understood the source, they made three changes:

1. Increased the MongoDB heartbeat interval from 30s to 60s.
This is the most direct lever. You can configure this in the MongoDB driver using heartbeatFrequencyMS. Doubling the interval roughly halves the background bandwidth from this source. For most applications, 60 seconds is still plenty frequent for topology awareness.

// Node.js example
const client = new MongoClient(uri, {
  heartbeatFrequencyMS: 60000
});

# Python (pymongo) example
client = MongoClient(uri, heartbeatFrequencyMS=60000)

2. Moved session storage and public data caching to Redis.
Not all database traffic needs to go through the SOCKS tunnel. If you're caching data that doesn't require database-level access controls, routing it through a separate path keeps the proxy connection cleaner and reduces both bandwidth and latency for those operations.

3. Deployed WAF rules and rate limiting.
Bot traffic was generating additional MongoDB queries downstream. Reducing inbound noise at the edge reduced queries, which reduced proxy traffic as a byproduct.

The result: The customer's projected bandwidth dropped from ~450 MB/month down to ~225 MB/month, fitting comfortably within their plan limits.

How to Investigate This Yourself

If you're seeing unexpected SOCKS bandwidth with a MongoDB connection, here's how to approach it:

• Start with the log viewer. Look for REQUEST, BANDWIDTH, and RESPONSE entries for each destination host and port. The BANDWIDTH entries will tell you how frequently each MiB milestone is being crossed on each tunnel.
• Calculate the expected heartbeat traffic. Take your heartbeat interval, multiply by the number of replica set members, estimate ~1.5 KB per exchange with overhead, and project it over 24 hours. If that math lines up with what you're seeing, heartbeats are your culprit.
• Check your driver configuration. Most drivers default to 10 seconds. If you haven't set heartbeatFrequencyMS explicitly, you may be running tighter than necessary.
• Look at connection pool settings. If your application is opening more connections than it needs, each one carries its own background traffic. Review maxPoolSize and minPoolSize settings to ensure they reflect your actual load. For example, if your minPoolSize is set to 10, the driver maintains 10 active background connections at all times, effectively multiplying your baseline heartbeat traffic by 10!

The Broader Point

Long-lived database connections through a proxy will always carry some background traffic. That's expected. The MongoDB driver is doing the right thing by monitoring replica set health. The SOCKS proxy is doing the right thing by counting all bytes.

The interesting part is how quickly it adds up when you're not looking for it, and how much headroom you can recover with a few targeted configuration changes.

If you're running MongoDB through a SOCKS proxy and want to audit your bandwidth footprint, the driver configuration is the best place to start.

QuotaGuard provides static IP SOCKS and HTTP proxies for cloud applications, AI agents, and automation workflows. If your database or API requires IP allowlisting, start here.