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Spring Cloud Gateway vs. Netflix Zuul 2: Which API Gateway Should You Use in 2025?

Spring Cloud Gateway (SCG) and Netflix Zuul 2 are key API gateways in Java for microservices architecture, offering different strengths.
Performance-wise, SCG boasts lower latency, higher throughput, and lower CPU usage compared to Zuul 2.
Feature-wise, SCG supports HTTP/2, WebSockets, and offers more modern protocol support, while Zuul 2 excels in fine-grained filters and dynamic server-side load balancing.
SCG is cleaner for declarative routing, integrates better with Spring Boot Actuator, and is future-proof with WebFlux and HTTP/2 support.
In 2025, it's recommended to use SCG if on Spring Boot/Cloud for high throughput and low latency, while Zuul 2 is ideal for Netflix OSS-heavy environments with complex request manipulation needs.
Migration tips from Zuul to SCG include replacing Groovy filters with WebFlux GatewayFilter and utilizing Spring Cloud LoadBalancer.
Detailed benchmark setups between SCG and Zuul 2 show SCG's superiority in performance, especially in throughput, latency, and resource usage.
For most use cases in 2025, Spring Cloud Gateway emerges as the preferred choice, offering speed, modernization, and strong integration with Spring ecosystems over Zuul 2.
Conclusion: Spring Cloud Gateway is recommended in 2025 for its performance and modern features, while Zuul 2 remains suitable mainly for legacy Netflix OSS setups.

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Hackernoon

420

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The HackerNoon Newsletter: What to Do While I Wait for ChatGPT (6/13/2025)

The HackerNoon Newsletter for June 13, 2025 brings tech highlights and top quality stories.
Notable events on this day include significant milestones in history.
Highlighted stories in the newsletter cover topics such as observational writing, API versioning, Keras model training customization, AI operations, and self-hosting language models at scale.
The newsletter emphasizes the importance of writing for consolidating technical knowledge and contributing to community standards.
Readers are encouraged to explore the content and answer the greatest interview questions of all time.
The HackerNoon Team wishes readers an enjoyable experience and invites them to share the newsletter with others.
The topics covered in the newsletter range from writing compelling stories without an extraordinary life to self-hosting large language models.
The newsletter offers insights into API versioning for preventing disruptions to existing clients.
Keras model training customization is explored, focusing on overriding train_step() while retaining fit() benefits.
One article delves into the frustrations of waiting for ChatGPT to load and its impact on teams.
Another article discusses the intricacies of self-hosting a language model at a larger scale.
Writing is touted as a tool for establishing credibility and sharing technical expertise within the community.
The newsletter provides free reading material and encourages sharing with like-minded individuals.
The HackerNoon Team signs off with warm regards, looking forward to connecting with readers on Planet Internet.

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Scand

221

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The Pros and Cons of Flutter App Development and When to Choose It in 2025

Flutter continues to be a popular cross-platform mobile app development platform backed by Google and a strong community, with notable advantages like Dart programming language, null safety, and WebAssembly support.
Flutter's adoption rate remains high with key updates in 2024-2025 including the transition to the Impeller graphics engine for improved performance, better Flutter Web support, and enhanced native API integration.
It offers efficient cross-platform development, high performance with Impeller, fast development using Hot Reload, a growing ecosystem, and consistent UI across platforms, making it suitable for various projects in 2025.
However, potential drawbacks in 2025 include larger app sizes, limitations in platform-specific features, Dart's niche status, and web/desktop support still lagging behind native solutions.
Decision factors for using Flutter in 2025 include needing unified UI and business logic, quick MVP launches, rapid UI updates, existing Flutter expertise in the team, and minimal deep native integrations.
When considering Flutter, it excels in projects with time-to-market constraints, stringent budget requirements, existing Flutter knowledge, minimal native integrations, UI-centric applications, long-term scalability needs, and reducing technical debt.
Flutter may not be suitable for apps with strict size constraints, demanding native features, requiring peak performance, facing ecosystem limitations, or lacking team Dart/Flutter experience.
Key considerations for hiring a Flutter development team include experience with Flutter-specific projects, a diverse team composition, focus on code quality and maintenance, and expertise to avoid inefficient implementations.
Flutter remains relevant in 2025 for enterprise development, web app creation, and its cost efficiency, but native development still holds sway for certain project requirements.
While Flutter is competitive, it may not entirely replace native development and alternatives like React Native, Kotlin Multiplatform, and .NET MAUI offer different strengths based on project needs in 2025.
Dart remains essential for Flutter development, even in 2025, as a key language that unlocks Flutter's potential for creating cross-platform applications.

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Medium

151

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What’s The Role Of Elixir?

AI is dominating the software world with languages like Python and JavaScript being favored over Elixir.
Elixir is not considered dead yet but is facing challenges in gaining popularity against more mainstream languages.
It might be a good time to focus on Elixir for those who understand its potential.
Current AI models are predominantly trained on Python, JavaScript, and Java, making Elixir a niche language in comparison.
AI struggles with niche languages like Elixir due to lack of exposure in their training data.
Elixir's strength lies in handling specialized and unconventional scenarios where AI might not perform as well.

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Hackernoon

281

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Code Smell 303 - How to Prevent Breaking Existing Clients When You Make Changes

Breaking APIs without warning can lead to client application crashes, integration failures, and broken trust, among other problems.
Solutions include semantic versioning, backward compatibility, deprecation warnings, clear documentation, and thorough testing.
Proper versioning ensures smooth transitions and reliability for API consumers.
Detecting API changes without proper versioning can be semi-automatic and involve monitoring client failures after releases.
Maintaining a stable mapping between API contracts and client expectations is crucial to prevent system failures and lost trust.
AI generators can introduce this issue if not instructed to maintain backward compatibility and implement versioning strategies.
Always version APIs to prevent breaking changes, build trust with consumers, and enable smooth system evolution.
Breaking API contracts can lead to defects, downtime, and a poor user experience.
It is essential to deprecate features carefully and communicate changes proactively to avoid disruptions.
You should always version APIs to prevent client application impacts, building trust and enabling smooth system evolution.
API changes without versioning can result in cascading failures across dependent systems, causing frustration and costly fixes for users.

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Dev

173

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Project of the Week: MapLibre

MapLibre is a leading open-source JavaScript library for interactive vector maps on websites and apps, originating as a fork from Mapbox GL JS in December 2020.
MapLibre has gained popularity with over 7,700 GitHub stars, 843 forks, and contributions from 551 developers as a web-based vector mapping solution.
Research on collab.dev revealed efficient collaboration patterns in MapLibre, showcasing its development practices.
Key Highlights: MapLibre showcases incredibly fast merge times, with a median merge time of 12 minutes and 21 seconds for pull requests.
Contributors experience minimal wait times, with an average wait time of just 10 minutes and 14 seconds, supporting rapid development cycles.
82% of PRs in MapLibre are bot-generated, with bots accounting for 47.7% of repository events, indicating a high level of workflow automation.
Review processes are exceptional in MapLibre, with 85% of reviews completed within 1 hour and a median review turnaround time of just 16 seconds, offering immediate feedback to developers.
The project's focus on bot-driven development and fast review processes enhances the developer experience and ensures quality standards.

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Medium

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The SkillForge Journal #3: From Blueprint to Living Code

The article discusses the implementation of a Test-Driven Development (TDD) workflow in creating a SkillForge engine.
TDD involves writing tests prior to writing code, enforcing clarity and correctness.
The TDD process revealed a critical bug where a Skill object was passed instead of a skill_id string to a function, showcasing the importance of tests in catching errors.
A fundamental decision was made regarding treating a 'category' of skills as the same type of object as a 'skill' itself.
To maintain simplicity and power, categories were treated as skills by adding a boolean attribute to the Skill class.
An abstract skill functions as a parent node, while a concrete skill acts as a completable task, enabling future complexity.
The V1 implementation of the core Skill and SkillGraph classes has been completed through TDD-driven work.
The foundation is verified, and the next step involves implementing graph traversal algorithms for the SkillForge engine.
These algorithms will help answer critical user questions related to learning specific skills and potential progression paths.
The blueprint has transitioned into code, laying the foundation for the next phase of development.

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Dev

169

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2616. Minimize the Maximum Difference of Pairs

Given an integer array and a number p, the task is to find p pairs of indices such that the maximum difference among the pairs is minimized.
The approach involves sorting the array and using binary search to find the smallest possible maximum difference.
Pairs are formed by selecting adjacent elements with the smallest difference to minimize the overall maximum difference.
Binary search is used to efficiently determine the smallest value that allows for at least p valid pairs.
Greedy pair formation ensures that pairs are optimally selected to meet the maximum difference criteria.
The provided PHP code snippet showcases the implementation of the solution using binary search and greedy techniques.
Initial checks are performed, the array is sorted, and binary search is executed to find the optimal maximum difference.
The canFormPairs function validates if the given mid value allows forming at least p valid pairs.
The binary search loop adjusts the search space based on the feasibility of forming enough pairs for the current mid value.
This efficient approach combines binary search and greedy selection to minimize the maximum difference among pairs.

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Medium

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These new Windsurf updates are completely insane for developers

Windsurf released a new Wave 10 update with revolutionary features aimed at developers.
One of the major updates is the Planning Mode that enhances the AI's understanding of the codebase and project goals.
The agent now comprehends both current and future project aspects, which significantly improves task accuracy.
Cascade conversations now include a live Markdown plan for shared planning between developers and AI, allowing task prioritization and goal setting.
If changes are made to the plan, the AI will take action accordingly.
The update is expected to have a profound impact on coding efficiency and accuracy.

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Medium

216

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How to 10x your vibe coding with AI

Journalist explores using pseudocode as a bridge for human-computer communication, delving into its benefits and applications.
Pseudocode allows for clear, unambiguous communication with AI, enabling users to think like computers and systems.
The article highlights the importance of pseudocode in documenting, defining actions, making decisions, and managing processes.
It emphasizes pseudocode's role in AI understanding and translating processes into various programming languages.
Pseudocode simplifies complex tasks into structured processes, enhancing clarity, efficiency, and adaptability in programming.
The piece discusses how pseudocode can empower users in varied scenarios from daily habits to business operations.
It showcases the versatility and significance of pseudocode in fostering algorithmic thinking and AI interaction.
AI's proficiency in translating well-structured pseudocode across programming languages highlights its pivotal role in future programming approaches.
The article concludes with a call to embrace pseudocode as a foundational skill for effective algorithmic communication in an AI-driven world.
Pseudocode serves as a lingua franca for communicating algorithmic concepts, bridging the gap between human intent and AI execution.

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Medium

300

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The JavaScript Myths Every Developer Believes — Busted!

JavaScript is a widely-used programming language with common myths and misconceptions.
One myth is that JavaScript is only used for websites and web apps, but it has evolved beyond that.
With tools like Node.js, JavaScript is used for server-side applications, command-line tools, APIs, and IoT applications.
Platforms like React Native enable building mobile apps with JavaScript.
JavaScript is now a general-purpose programming language.
The article debunks common JavaScript myths and sheds light on its versatility.
Myth: JavaScript is limited to web development.
Reality: JavaScript is used for various applications beyond the web.
Busted: JavaScript is now a versatile language for diverse development needs.

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Insider

138

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GitHub's CEO says startups can only get so far with vibe coding

GitHub's CEO, Thomas Dohmke, emphasized the importance of developers for startup success at VivaTech in Paris.
Dohmke stated that startups using AI tools for launching still need developers to build complex systems to attract investors.
While AI can lower the barrier to entry for startups, scaling requires technical expertise, according to GitHub's CEO.
Observing a shift in the market, Dohmke noted increasing interest in AI among companies.
AI coding assistants can help non-technical founders create startups with minimal teams, but investors might question their uniqueness.
Startups heavily reliant on coding assistants may struggle to demonstrate significant value to investors, emphasized Dohmke.
Non-technical founders may find it challenging to scale startups without developers to build complex systems.
Dohmke highlighted the importance of deeper understanding and quality development over quick, inexpensive measures for startup value.
GitHub, known for its Copilot tool providing coding suggestions, emphasizes the role of human developers despite AI integration.
Vibe coding tools raise questions regarding the demand for software developers and essential skills in the AI era.
Dohmke believes that every child should learn coding despite the AI-driven engineering boom, underscoring the importance of self-reliant coding.
Software engineers need to balance using AI prompts effectively while knowing when to rely on personal coding skills, per Dohmke.
Dohmke advised against wasteful prompting skills, emphasizing the importance of knowing when not to use AI prompts.
The article discusses GitHub's position under Microsoft and the implications of vibe coding on the software development landscape.
Thomas Dohmke's insights highlight the crucial role of developers and human expertise in creating valuable startups.

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Medium

247

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Performant ArkTS Programming: Best Practices for High-Efficiency Code

ArkTS offers developers a powerful, TypeScript-like syntax with optimizations for better runtime performance.
Writing performant applications with ArkTS requires awareness of low-level optimizations.
Real-world performant programming practices include avoiding mixing integer and floating-point types.
Arithmetic overflow should be avoided as it can degrade performance.
Extract constants outside loops to reduce attribute lookup costs.
Optional parameters in hot paths should be avoided to prevent extra undefined checks.
Sparse arrays are slower to access; initialize arrays with contiguous elements for better performance.
Union arrays with mixed types should be avoided to maintain performance.
Adopting these tips can lead to faster, leaner, and more efficient applications when using ArkTS or HarmonyOS.
Developers can achieve significant performance improvements by making small, focused changes.
Happy coding!

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14 Likes

Medium

186

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Firebase Studio: Your Perfect Full Stack Picky Companion

Firebase Studio serves as a valuable companion for developers, providing guidance and uncovering potential pitfalls in project development.
It acts as a sounding board, devil's advocate, and a source of inspiration to help developers validate their ideas.
The tool aids in unearthing hidden complexities, exploring alternative approaches, and creating remarkable solutions.
Firebase Studio assists in maintaining focus on the bigger picture during coding and brainstorming sessions.
It helps anticipate unexpected challenges in software development, avoiding critical bugs and issues post-launch.
The tool prompts developers to consider edge cases when generating schemas and backend logic, enhancing the robustness of the solutions.
It challenges developers' ideas, forces justifications of choices, and identifies potential weaknesses, leading to early validation and prevention of future debugging work.
Firebase Studio is not a replacement for developers' expertise but a tool that enhances their problem-solving abilities and strategic thinking.
It serves as a skeptical partner and idea generator, supporting developers in reaching their full potential.
Developers can rely on Firebase Studio for assistance with features like a magic link authentication system, prompting considerations of various scenarios and ensuring robust implementation.

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11 Likes

Medium

307

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I Made a Trading Bot. Now What?

The author shares their experience of creating a trading bot without prior knowledge and the challenges faced.
The trading bot resulted in confusion, trial-and-error, with instances of not trading or making poor trading decisions.
The author started with no knowledge and struggled with errors in the code when developing the bot.
Initially, the bot did not execute trades even when market conditions were met.
After multiple attempts at refining the bot, it started trading excessively, closing trades at slight losses.
Despite the challenges, the author found satisfaction in the process of building the bot themselves.
There is a dilemma between continuing to refine the bot or giving up on the project entirely.
The author plans to monitor the bot's performance, make adjustments, and continue running it.
The experience of debugging and improving the bot has been rewarding for the author.
A lesson learned is to test the bot extensively using demo accounts before trading with real money.
The author emphasizes enjoying the learning process despite the challenges faced.

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