What Are Concurrent Connections?
Multiple connections happening roughly within a 500-millisecond timespan can be considered concurrent connections. When evaluating new server hardware, you must consider whether your setup will hit a concurrent connection limit at some point. Exceeding these limits can lead to slow response times, dropped connections, or server crashes, affecting user experience and business operations.
How Are Concurrent Connections Measured?
Most web servers, databases, and cloud providers define concurrent connections differently. Some focus on HTTP requests, while others consider active sessions, WebSocket connections, or database queries. Understanding your specific use case is crucial when designing infrastructure.
Real-Life Example: Website Traffic from a Magazine Campaign
Imagine you run a campaign in a magazine promoting a special offer through a single-page website. To estimate potential concurrent connections, consider the magazine’s readership:
- If the magazine has 50,000 readers
- If 1% of them visit your site at the same time
- That results in 500 concurrent users hitting your website
While it’s unlikely that all readers will visit simultaneously, this estimate helps in planning server capacity. Traffic spikes, particularly during a product launch or limited-time offer, can strain a server significantly.
How to Prepare Your Server for Spikes?
- Load Testing – Tools like Apache JMeter and Loader.io can simulate traffic loads to see how your server responds.
- CDN Usage – Services like Cloudflare and AWS CloudFront help distribute traffic and reduce load on your origin server.
- Optimized Caching – Implementing caching mechanisms with Redis or Varnish can reduce the number of requests hitting your backend.
- Auto-Scaling Solutions – Platforms like AWS Auto Scaling and Google Cloud Autoscaler dynamically adjust server resources based on demand.
The Impact on Mobile Apps
Concurrent connections become more critical when building mobile apps. A popular app can easily hit concurrent user limits, making cloud solutions invaluable for handling sudden traffic spikes. Platforms like Parse, Firebase, and Supabase provide backend services that automatically scale.
Why Mobile Apps Face Greater Challenges
- Persistent Connections – Mobile apps often rely on WebSockets, which maintain open connections, consuming server resources.
- Global Usage – Unlike web campaigns with regional traffic patterns, mobile apps can experience simultaneous user activity worldwide.
- Push Notifications – Sending mass notifications can lead to sudden surges in active users, creating unexpected loads on servers.
RAM Limits: The Real Bottleneck
While concurrent connections are important, the real constraint often isn’t the connection limit—it’s the server’s RAM capacity. Ensuring your server has sufficient RAM is crucial to prevent performance degradation or crashes under high load.
How to Manage RAM Effectively?
- Monitor Memory Usage – Tools like Prometheus and Grafana help track server health.
- Optimize Database Queries – Poorly optimized queries can consume excessive memory. Use EXPLAIN ANALYZE in PostgreSQL to optimize queries.
- Use Memory-Efficient Frameworks – Lightweight frameworks like FastAPI for Python or Go Fiber can handle high loads with minimal memory usage.
Conclusion
When planning for high-traffic scenarios, always account for:
- Concurrent connections and their impact on your server
- Server RAM capacity and how it affects performance
- Cloud scalability options to handle unpredictable spikes
By understanding these factors, you can optimize your infrastructure to handle traffic spikes smoothly. Whether you’re running a campaign, developing a mobile app, or managing an online service, proper planning ensures a seamless user experience.
