This content originally appeared on DEV Community and was authored by Sathish
When Your Tracking System Becomes a Battery Vampire
Picture this: Your food delivery app just hit 100,000 active drivers. Success, right? Wrong. Your servers are screaming, driver phones are dying faster than ice cream in summer, and your AWS bill looks like a mortgage payment.
The culprit? Every driver's phone firing GPS coordinates at your servers every 4 seconds like an overeager intern sending status updates.
Here's how to fix this mess without losing your sanity.
Smart Updates Beat Frequent Updates
The nuclear option is obvious: reduce update frequency. But you can do better than that.
Adaptive intervals are your friend:
- Stationary drivers: Update every 30 seconds
- Moving slowly: Every 10 seconds
- Highway speeds: Every 5 seconds
function getUpdateInterval(speed, isOnDelivery) {
if (speed < 2) return 30000; // Parked/waiting
if (speed < 15) return 10000; // City driving
if (isOnDelivery) return 5000; // Active delivery
return 15000; // Just cruising
}
This alone cuts your update volume by 60-70%. Your servers will thank you.
Batch Everything Like Your Life Depends On It
Stop treating each GPS ping like a precious snowflake. Bundle them up and ship them in batches.
Client-side batching works wonders:
class LocationBatcher {
constructor() {
this.batch = [];
this.timer = null;
}
addLocation(lat, lng, timestamp) {
this.batch.push({ lat, lng, timestamp });
if (this.batch.length >= 5 || !this.timer) {
this.scheduleSend();
}
}
scheduleSend() {
clearTimeout(this.timer);
this.timer = setTimeout(() => this.sendBatch(), 10000);
}
}
Now you're sending 5 locations at once instead of 5 separate requests. Network overhead drops like a rock.
Your Backend Needs Smarter Filtering
Not every location update matters. If a driver moved 2 meters, nobody cares.
Server-side deduplication saves the day:
def should_update_location(driver_id, new_lat, new_lng):
last_location = get_last_location(driver_id)
# Skip if moved less than 20 meters
distance = calculate_distance(
last_location.lat, last_location.lng,
new_lat, new_lng
)
return distance > 20 # meters
This filters out 40% of meaningless updates where drivers are basically standing still.
WebSockets Won't Save You (But They Help)
Everyone jumps to WebSockets thinking they're the magic bullet. They're not, but they do help with the constant connection overhead.
The real win: Use WebSockets for outbound updates to customer apps, keep HTTP for driver location uploads. Best of both worlds.
The Database That Actually Scales
Your regular PostgreSQL setup will cry with 100k concurrent updates. Time for some write-optimized architecture:
- Time-series database (InfluxDB, TimescaleDB) for location history
- Redis for current driver positions
- Message queues to handle traffic spikes
This setup handles millions of updates without breaking a sweat.
Bottom line: Real-time doesn't mean "spam the server every few seconds." Smart updates, efficient batching, and proper architecture turn chaos into smooth sailing.
Your drivers' phones (and your bank account) will love you for it.
This content originally appeared on DEV Community and was authored by Sathish
Sathish | Sciencx (2025-08-23T03:31:00+00:00) Real-Time Tracking Without the Drama. Retrieved from https://www.scien.cx/2025/08/23/real-time-tracking-without-the-drama/
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