This article compares RabbitMQ, RocketMQ, and Kafka on throughput, latency, scalability, and reliability, outlining each system's core features and recommending suitable scenarios such as reliable messaging, high‑performance streaming, and large‑scale real‑time data processing.
This article compares Node.js and Python for backend development in 2026, examining their architectures, performance benchmarks, ecosystem strengths, and suitable use-cases, and provides a decision framework to help developers choose the most appropriate technology based on project requirements, team skills, and scalability needs.
In a landscape crowded with OLTP, OLAP, HTAP, NewSQL and cloud‑native options, this article explains why enterprises must look beyond performance and assess a database’s five‑dimensional long‑term service capability to ensure sustainable growth and low migration risk.
The article lists several front‑end and back‑end frameworks that are no longer worth learning, explains why they have faded, and offers three concrete criteria—job demand, ecosystem activity, and problem‑solving ability—to help developers decide which technologies to invest in.
This article outlines practical guidelines for startups to choose a simple, reliable, and forward‑looking tech stack—covering backend frameworks, databases, cloud services, containerization, architecture evolution stages, team processes, and cost‑optimization—to avoid common pitfalls and maximize long‑term growth.
This article reveals the hidden pitfalls of popular frameworks, explains why over‑hyped promises often lead to massive redesign costs, and provides a practical evaluation matrix and best‑practice checklist to help teams choose stable, maintainable technologies for long‑term project success.
An in‑depth comparison reveals how state‑owned enterprise architects work on multi‑year, documentation‑heavy projects with conservative tech stacks, while internet company architects operate under rapid, agile cycles, embracing cutting‑edge tools, flat collaboration, and high‑pressure environments, highlighting distinct values, career paths, and skill demands.
This article showcases a prize‑driven Q&A session where senior architects answer real‑world questions on AI deployment, backend language choices, large‑model integration, and career advancement, offering practical guidance and a chance to win exclusive Tencent Cloud merchandise.
This article compares seven mainstream programming languages—Python, JavaScript, Java, C++, C#, Go, and Rust—detailing their features, pros, cons, typical use cases, and ideal learners to help beginners select the language that best fits their goals and interests.
This article defines cloud native, outlines its core technology layers, examines the tangible benefits and hidden costs for enterprises, discusses the new challenges it introduces, offers guidance on technology selection, and predicts how operations roles will evolve in a cloud‑native world.
Choosing the right technology involves evaluating functional fit, non‑functional quality attributes, and team considerations, and this article presents a hierarchical decision framework that helps structure the selection process, adapt dimensions to specific scenarios, and foster consensus within development teams.
After initially adopting Tailwind CSS for rapid UI development in a React real‑time chat app, our team reverted to SASS combined with CSS Modules because the growing utility‑class markup hurt readability, increased build times, and bloated the CSS bundle, ultimately delivering a more maintainable codebase and noticeably better performance.
The article reviews cross‑platform architecture concepts, examines the trade‑offs between code reuse and user experience, discusses screen‑size differentiation, outlines criteria for selecting a technology stack, and proposes progressive development and systematic standards to ensure sustainable, high‑quality multi‑device applications.
The article examines whether Docker incurs performance penalties compared to native services, arguing that the decision to adopt containers and micro‑services must weigh business complexity, company stage, team size, infrastructure readiness, and operational costs rather than relying on generic hype.
This article comprehensively discusses the essential aspects of constructing a system engineering architecture, emphasizing value‑first decision making, layered and DDD architectural patterns, technology selection criteria, exception handling, logging, monitoring, and the importance of establishing shared consensus among teams.
This article explores engineering architecture design, emphasizing value‑first decision making, layered and DDD architectures, technology selection criteria, and best practices for consensus, exception, logging, and monitoring to build scalable, maintainable, and secure software systems.
This article explores the principles of engineering architecture design, emphasizing value‑first decision making, discusses common pitfalls, outlines layered and domain‑driven design patterns, compares MVC and hexagonal architectures, and provides practical guidance on technology selection, risk assessment, and operational best practices for building maintainable, scalable backend systems.
This comprehensive guide examines the key factors for selecting between React and Vue—including team suitability, compatibility, usage patterns, ecosystem, cross‑platform support, performance benchmarks, mental models, community size, and licensing—to help developers make an informed technology‑stack decision.
This article outlines a practical technology stack and architectural choices—including load balancing, CDN, distributed RPC frameworks, message queues, caching, databases, and search—for building a scalable backend that can support tens of thousands of daily active users in a mid‑size internet company.
The author, a seasoned Java backend developer, shares personal experiences and insights on evaluating efficiency, ecosystem, and team dynamics when selecting technologies—from legacy frameworks and databases to modern big‑data tools like Spark and Flink—offering practical guidance for developers and teams navigating today’s rapidly evolving tech landscape.
The article reflects on a Java backend developer's seven‑year journey, examining how efficiency, community ecosystem, and team preferences influence technology choices across front‑end frameworks, big‑data platforms, databases, and open‑source tools.
This article reviews microservice architecture, outlining selection principles, comparing popular frameworks such as Dubbo and Spring Cloud for service governance, evaluating API gateway options like Zuul, Traefik, and Kong, and discussing configuration center solutions including Spring Cloud Config, Apollo, and Nacos.
The article explains OpenSSF's criticality scoring system for open‑source projects, lists the weighted parameters used, shows how Java backend projects rank, and compares popular Java frameworks and libraries to guide technology selection decisions.
This guide surveys over a hundred modern frameworks and tools across fourteen critical backend domains—message queues, caching, sharding, data sync, communication, micro‑services, distributed utilities, monitoring, scheduling, entry proxies, storage, CI/CD, debugging, and local utilities—offering concise recommendations and practical insights for architects and engineers.
The article shares a veteran engineer's reflections on choosing technologies, contrasting trendy versus familiar tools, weighing maintenance costs against productivity gains, and offering a pragmatic decision‑making framework illustrated with real‑world examples from Etsy, Mailchimp, and other projects.
This guide outlines key criteria for selecting a message queue—open source, ecosystem, reliability, clustering, and performance—and compares RabbitMQ, RocketMQ, and Kafka, highlighting each system's strengths, weaknesses, and ideal use‑cases.
The article shares practical insights on the role of a technical leader, outlines a streamlined R&D workflow and team responsibilities for fast‑moving startups, and discusses technology selection, architecture components, and management practices to help early‑stage companies build effective engineering teams.
The article explains what a software architect does, outlines their responsibilities such as architecture design, technology selection, managing non‑functional requirements, solving technical challenges, and guiding teams, describes different types of architects, and offers advice on the skills and experience needed to become one.
Becoming a software architect requires more than high‑concurrency knowledge; it demands comprehensive abilities such as requirement analysis, system decomposition, technology selection, design, communication, and leadership across all development phases, balancing business understanding with technical expertise to deliver effective architectural solutions.
This article shares a former Google engineer’s journey to CTO at a game studio, highlighting the challenges of leaving the programming comfort zone, mastering communication, choosing the right technologies, abandoning side projects, and navigating complex team‑management decisions.
The article explains the concept of the big front‑end, distinguishes its horizontal UI and vertical server dimensions, outlines why it reduces communication and development costs, and details practical technology selection, architecture design, and the measurable benefits of shared components and server‑side rendering.
This article explains what graph databases are, traces their evolution from early navigational models to modern distributed systems, highlights their core concepts and advantages over relational databases, showcases typical application scenarios, and provides a comparative overview of popular open‑source graph database engines to guide technology selection.
This article explores the blurry line between development and software architecture, outlines the responsibilities and evolution of a software architect, and provides practical guidance on defining architecture, managing non‑functional requirements, selecting technologies, evaluating designs, and leading teams toward successful releases.
The article shares a series of practical recommendations for improving system architecture design, emphasizing the need to avoid premature API planning, make decisive technology choices, eliminate triangular call relationships, clearly define program modules, adopt a star‑shaped hub architecture, separate business logic, ensure transaction safety, and isolate scheduling from business via databases.
Lan Langworth, a former Google engineer and co‑founder of Artillery, shares his candid journey from leaving Google to becoming a CTO, offering practical insights on direction, communication pitfalls, building a developer‑focused culture, choosing technologies, and trusting intuition in a fast‑moving startup environment.
The article discusses practical technology selection for mobile app development, weighing native versus H5 approaches, choosing between Objective‑C and Swift, and comparing MVC, MVP, and MVVM architectures, emphasizing decisions based on team resources, project timelines, and long‑term maintainability.
