Authored by Mikhail Filimonov, Director of IT mac OS and reviewed by the Metapress editorial team, this article was published following a careful evaluation process to ensure quality, relevance, and editorial standards.
***
In real-time applications, even the smallest delays can dramatically shape user experiences. Latency isn’t just a technical goal – it’s a fundamental aspect of how users perceive and engage with your system. Whether it’s instant messaging on a social platform or lightning-fast responses in a competitive game, the threshold for what feels “instant” can make or break your product.
In this article, I’ll share some of the key lessons from my experience to help you build responsive systems.
How latency affects real-time applications
The basic definition of latency is the delay between a user action and the system’s response. However, in reality it’s much more. There are quite a few forms latency can take: network round-trip time, server processing delays, database query times, and the often-overlooked user-perceived latency.
The impact latency has on user engagement is actually dramatic. Studies show that even a 100-millisecond delay in web page loading times can reduce conversion rates by 7%. In gaming, latency above 150ms makes competitive play nearly impossible, while social platforms see engagement drop off sharply when message delivery exceeds 200ms.
Different kinds of applications need different latency targets. Social platforms are usually built with sub-100ms response times for action like posting or messaging. Gaming systems demand ultra-low latency, typically around 10–50 ms for real-time multiplayer play. It gets even more extreme in the world of finance and trading, where even microseconds matter because every tiny delay can cost (or make) millions.
Design challenges
Building low-latency systems at scale presents a unique set of challenges that traditional application architectures simply weren’t designed to handle. First, there’s the sheer volume problem: modern social platforms serve hundreds of millions of concurrent users, while popular games might host millions of simultaneous players across thousands of servers.
Traffic patterns in these systems are notoriously unpredictable. A viral post can trigger a cascade of activity that increases load by orders of magnitude within minutes. Similarly, special in-game events or product launches can create traffic spikes that would crush unprepared infrastructure.
The consistency versus responsiveness dilemma adds another layer of complexity. Users expect their actions to be reflected immediately, but ensuring data consistency across distributed systems traditionally requires coordination that introduces latency. Finding the right balance between these competing needs often defines the success or failure of a real-time system.
Finally, the heterogeneous nature of modern networks compounds these challenges. Your carefully optimized system might perform beautifully on fiber connections but struggle on mobile networks with variable bandwidth and intermittent connectivity.
Lessons from social platforms
Social platforms have pioneered several techniques that have become standard practices in low-latency system design. The most fundamental is strategic data replication and caching. Rather than serving all requests from centralized databases, successful platforms distribute data across geographically dispersed edge caches and content delivery networks (CDNs). This ensures that when a user in São Paulo requests their timeline, the data comes from a nearby server rather than traveling across continents.
Asynchronous processing has proven invaluable for hiding latency from users. When you post a photo, the system immediately confirms receipt while the actual processing — resizing, filtering, virus scanning — happens in the background. Message queues and event-driven architectures enable this sleight of hand, allowing systems to appear instantaneous even when complex operations are still in progress.
Smart platforms avoid recalculating everything from scratch. Instead of rebuilding an entire news feed when one post changes, they use incremental updates to modify only what’s necessary. This approach dramatically reduces computational overhead and response times.
Quality of Service (QoS) mechanisms ensure that high-priority traffic gets preferential treatment. Live video streams and breaking news notifications might jump ahead of routine background synchronization tasks. This prioritization prevents important user interactions from being delayed by less critical system operations.
Perhaps most importantly, social platforms have mastered the art of managing user perception. Skeleton screens give the impression of loading while content loads in the background. Optimistic updates show users their actions immediately, even before server confirmation. Prefetching anticipates what users might want next, loading content before it’s requested.
Lessons from gaming
Gaming systems have some of the toughest latency requirements, and over time they’ve developed clever ways to meet them. Client-side prediction is one of the key tricks. It lets games respond instantly to a player’s input by simulating actions locally — even before the server confirms them. This creates the illusion of zero latency for common actions like movement or firing a weapon.
Of course, local predictions don’t always match up with the server’s version of reality. When they diverge, lag compensation and rollback systems step in. The server might “rewind” the game state to when a player fired their shot, check if it would have hit, and then fast-forward to the current state. Players never see this behind-the-scenes complexity — they just enjoy smooth, responsive gameplay.
The choice of network protocol also makes a big difference. Web apps usually rely on TCP for reliable delivery, but games often use UDP to cut down on overhead. If a single position update goes missing, it’s not the end of the world — the next update will fix it. But skipping TCP’s confirmation process can slash latency in ways that are critical for fast-paced games.
To keep data lean, games use delta compression, sending only the changes in the game world rather than full state updates. Instead of transmitting a character’s entire state, a well-tuned server might send just a few bytes to update a player’s position.
Finally, load balancing and matchmaking help connect players to the nearest available server. It’s not just about cutting latency for a smoother game — it’s about fairness, too. In competitive play, a player with 20ms latency has a huge edge over someone with 200ms.
Common architectural strategies
Different industries working with latency-sensitive applications have developed some key architectural patterns. Partitioning and sharding are big ones — they keep data physically close to where it’s needed. For example, a European user’s social data is stored on European servers, while their American friends’ data stays in the U.S. The system only has to deal with long network hops when there’s a cross-region interaction.
The choice between stateless and stateful services is another big factor. Stateless services are easier to scale and typically offer lower latency for simple tasks. But when you need to keep complex session data or maintain consistency, stateful services are the way to go. The trick is to use each one where it makes the most sense.
Proactive monitoring is also key for keeping latency low. Latency histograms don’t just show the average performance — they reveal how responses are distributed, which helps pinpoint issues. Service Level Objectives (SLOs) set clear targets for what’s considered acceptable performance, guiding your optimization efforts. Without good observability, teams can waste time tweaking things that aren’t the real bottleneck.
Actionable recommendations for system designers
Successful low-latency system design starts with understanding your specific domain requirements. Social platforms can often tolerate higher latency than games but must handle larger scale. Gaming systems need ultra-low latency but typically serve smaller, more predictable user bases. Choose your optimization strategies accordingly.
Measurement must precede optimization. Profile your system under realistic load conditions to identify actual bottlenecks rather than assumed ones. The database query you thought was the problem might be dwarfed by network round-trip times or serialization overhead.
Incorporate low-latency patterns from the architectural design phase rather than retrofitting them later. Designing for horizontal scaling, implementing caching strategies, and planning for geographic distribution are much easier when considered upfront rather than bolted on afterward.
Remember that user perception often matters more than absolute performance metrics. A system that responds in 80ms but feels instant through clever UI techniques might provide a better user experience than one that responds in 60ms but feels sluggish due to poor interaction design.
Building low-latency systems is both an art and a science, requiring technical expertise, careful measurement, and deep understanding of user expectations. The lessons learned from social platforms and gaming provide a solid foundation, but every system has unique requirements that need tailored solutions. The key is understanding the principles, measuring relentlessly, and optimizing thoughtfully rather than blindly chasing ever-lower numbers on a dashboard.