Best popular backend frameworks by performance of throughput benchmark comparison and ranking in 2025 DEV Community

When things slow down, it helps you focus your efforts on the things that will matter the most. Real User monitoring tools like Request Metrics help you understand your performance, and how it changes over time. Does this mean you should drop your backend performance work and refocus? Using these metrics, and a few other tricks, we can measure the performance impact of the frontend and backend code separately. However, not all browsers support modern metrics like TTFB, FCP, and LCP, so it is still valuable for comparison. The Largest Contentful Paint, or LCP, measures the time it takes the browser to render the largest element on the page, by pixel area.

How can I identify and address bottlenecks in my back-end code? Avoid premature optimization and ensure changes are beneficial. Be aware of common pitfalls that can hinder your optimization efforts. 70% of recursive functions can be optimized. 70% of queries can be optimized by limiting results.

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• Avoid costly operations like JOINs on large tables and consider denormalizing data or creating optimized views.
• It is impossible to overestimate the importance of performance optimization in backend development as it directly affects the performance of online applications, therefore affecting operational expenses and user happiness as well.
• It occurs when you make 1 query to fetch a list of N items, then N additional queries to fetch a related piece of data for each item, totaling N+1 database round-trips.
• By offering a more scalable and effective approach to apply and control performance of web applications, containerizing and orchestration technologies have transformed backend development.

Backend Development Projects

The “traditional” backend is a mix of the server, databases, APIs, and operating systems that power an app’s front end. Each stage builds upon the previous, creating more sophisticated, efficient, and scalable backend systems. Also, Backend optimization has undergone a significant evolution over the years, adapting to the changing landscape of web development, increasing user demands, and advancements in technology.

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Development and server setup

• During testing, performance testers hope to gain insight into website functionality (APIs), performance (server response times, and so on), and system stability while a server is under increased load.
• The most accurate way to measure performance is through Real-User Monitoring, or RUM.
• This helps maintain consistent performance even when traffic spikes.
• These low-hanging optimizations often provide the biggest gains.
• ThreadsPerChild for mpm_worker_module had to be increased to 50 from the default 25 in httpd-mpm.conf.
• You can dramatically reduce the transfer time for these resources by using modern compression techniques like Brotli instead of gzip (or worse, no compression at all).

What matters far more than the implementation is that you record the whole distribution, not an average, because an average hides exactly the tail you care about. Because averages absorb variation, they are nearly http://cheapraybanolshop.com/Parks_and_recreation.html useless for performance analysis. The three fundamental metrics are latency (how long one request takes), throughput (how many requests per unit time), and utilization (what percentage of capacity is in use). This chapter builds intuition layer by layer, from the raw definition of “fast” through latency measurement, database tuning, caching strategy, and the two fundamental modes of scaling.

• The backend handles everything that happens before the browser receives its first byte of data.
• Teams that proactively focus on discovering backend bottlenecks avoid these traps.
• At low throughput, the server is mostly idle and each request gets served instantly.
• Caching, compression, parallelism, load balancing, and indexing are some of the techniques used.
• Adding proper indexes often reduces query time dramatically.

Microservices architecture is a design approach to building a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP-based API. Please note- Each of these strategies is a deep and complex field that requires specialized knowledge and experience to implement effectively. It includes practices like automation (CI/CD pipelines), collaboration and communication enhancements, and infrastructure as code. This refers to the practices and measures taken to protect applications and systems from threats and vulnerabilities. Strategies include optimizing data payloads (e.g., reducing size), implementing efficient API caching, managing rate limits, and optimizing database interactions behind the API. Common caching methods include in memory caches, distributed caches, and HTTP caching for web applications.