C++ is the choice for low-latency systems, but are you making the right optimizations?

In this edition of Calculated Conversations, we dive into the mind of Herik Lima, a Senior C++ Software Engineer with over 13 years of experience building high-performance systems for industries like trading, gaming, and network optimization. Herik’s expertise in low-latency development is unmatched, particularly when it comes to optimizing C++ for speed and performance.

In our conversation, Herik shares insights on how C++ stands out for its fine-grained control over memory and hardware, how he made advanced C++ education more accessible with C++ MasterClass, and the surprising impact of simple changes, like replacing memory allocators, on server performance. We also explore the challenges of building a web framework in C++ and the best practices for writing clean, maintainable code.

Here is what he had to say:

1. You’ve built high-performance systems for trading, gaming, and network optimization. In your view, what makes C++ the language of choice for low-latency development, and where do most developers misstep when trying to optimize for speed?

C++ is unmatched when it comes to fine-grained performance control. It allows you to operate close to the hardware—managing memory, instructions, and even data alignment. Most developers go wrong by jumping into micro-optimizations without understanding the real cost of abstractions. They often overlook memory allocation, cache misses, or misuse data structures that don’t fit the workload.

2. With C++ MasterClass, you’re making advanced C++ education more accessible. What are some common myths or misconceptions you see about learning and mastering modern C++?

A common myth is that you need to master everything in C++ to be productive. That pushes beginners away. Another is the belief that modern C++ is harder than the old C++—when in fact, features like auto, range-based loops, smart pointers, and RAII make code safer and cleaner. The key is focused, practical learning—not trying to memorize the entire language.

3. You improved server performance at NoPing by 26% just by changing memory allocators. Could you walk us through what happened there, and what every C++ developer should know about memory allocation and performance?

At NoPing, we improved server performance by 26% just by replacing the default allocator with a custom memory pool. The standard allocation pattern caused fragmentation and lock contention under heavy load. The custom allocator used pre-allocated pools, tailored to the actual behavior of our traffic. Every C++ developer should understand that memory allocation is often an invisible hotspot—and the right choice here can be a game-changer.

4. You built a full web framework in C++, which is not something many developers attempt. What were some of the biggest challenges in making C++ work for the web, and how did you design it to be both fast and beginner-friendly?

I built CWF, inspired by Java Servlets, JSTL, and the Spring Framework. That influence gave us a clean component-based architecture with concepts like controllers, dependency injection, and middleware—all in modern C++. The biggest challenge was bridging C++’s raw power with web-level ergonomics. To make it beginner-friendly yet fast, we layered abstractions carefully, used meta-programming where necessary, and provided a familiar, declarative style for routes and services.

5. C++ offers power, but writing clean, maintainable code can be tricky. What practices or patterns do you rely on to keep your codebase efficient, testable, and readable?

I always lean on RAII and modern STL tools like std::unique_ptr, std::span, and std::optional. I avoid deep inheritance trees and prefer composition. My rule of thumb: if an abstraction adds overhead or reduces clarity, I drop it. I also write code with testability in mind—isolating logic from infrastructure, relying on clear interfaces, and using expected for predictable error handling.

6. For someone who knows the basics of C++ but wants to write production-grade, high-performance applications, how would you recommend they level up? What should they focus on first?

Understand value semantics and memory first. Then dive into move semantics, perfect forwarding, and lightweight template metaprogramming. Study what the compiler and CPU are doing under the hood: stack vs. heap, cache lines, alignment, and inlining. Read real-world open-source code. And most importantly—write code not just to work, but to scale and last.

7. You’ve worked across very different industries, from gaming at Riot to high-frequency trading. What’s one lesson about building robust C++ systems in the real world that you think every developer should learn early?

Before writing a single line of code, deeply understanding the problem domain is essential—and that doesn’t come from technical skills alone. It comes from solid requirements gathering, meaningful conversations with stakeholders, and modeling the system with tools like UML. Once the domain is clear and well-structured, I build a proof of concept (POC) to validate core ideas and alignment with the specifications. Only after that initial validation do I refine the solution, optimizing for performance and robustness. This iterative mindset ensures that the system is not only efficient but also purpose-driven and resilient in production.

To build fast, scalable systems, understanding both the problem and your tools is key. Herik Lima’s insights on optimizing C++, mastering memory allocation, and navigating challenges across industries show that performance isn’t just about code. It’s about strategy. By focusing on practical learning and avoiding common missteps, you can write not just code that works, but code that thrives in high-pressure environments.

If you found this conversation insightful, feel free to check out his LinkedIn full of tips here

Feel free to check out this conversation with Piyush Itankar about Embedded Systems