라인 / flutter

4 posts

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앱 성공을 위한 필수 요소: 장애 모니터링 (opens in new tab)

Effective mobile app management requires proactive outage monitoring to prevent user churn caused by failures in critical flows like registration or payment. Relying on user reports is often too late, so developers must implement systematic event collection and real-time dashboards to identify issues the moment they arise. By integrating tools like Sentry or Firebase, teams can maintain high quality through immediate response and detailed performance analysis. ### Implementing Sentry in Flutter * **Dependency and Initialization**: Integration begins by adding `sentry_flutter` and `sentry_dio` to the project. The initialization process involves setting the Data Source Name (DSN), environment tags (e.g., production vs. staging), and release versions to ensure logs are correctly categorized. * **Performance and Privacy**: Developers should configure `tracesSampleRate` and `profilesSampleRate` to balance monitoring depth with costs. Additionally, the `beforeSend` callback allows for masking sensitive user data like authorization headers or IP addresses before they are transmitted. * **Contextual Tracking**: To aid debugging, the system captures user IDs via `Sentry.configureScope` and tracks user movement using `SentryNavigatorObserver`. Utilizing `SentryInterceptor` with the Dio library allows for automatic tracking of HTTP request performance and API bottlenecks. ### Strategic Log Level Design * **Debug and Info**: Debug logs remain local to the terminal to save resources. Info logs are reserved for significant user actions that change data, such as successful sign-ups or purchases, while high-frequency read actions like "viewing a product list" are excluded to reduce noise and costs. * **Warning**: This level tracks external system failures, such as failed API calls or push notification losses. To prevent "alert fatigue," client-side network issues (e.g., timeouts or offline status) are ignored, and alerts are triggered only when specific thresholds are met, such as 100 failures within 10 minutes. * **Error**: Error logs represent internal logic failures that bypass defensive coding, such as null object errors, parsing failures, or unreachable code branches. These require immediate notification to the development team to facilitate rapid hotfixes. * **Fatal**: This level is dedicated to application crashes and unhandled exceptions. When configured at the app's entry point, the system automatically captures these critical failures to provide a comprehensive "crash-free users" metric. ### Creating Effective Dashboards * **Naming Conventions**: Logs should follow a strict structure, using tags for modules and event names (e.g., `[API] [postLogin] success`). This consistency allows for granular querying and clearer visualization on monitoring dashboards. * **Data Enrichment**: Using the `extra` field in log events provides vital context for troubleshooting, such as including the specific endpoint, request body, and response status code for a failed transaction. * **Actionable Metrics**: Effective monitoring focuses on key performance indicators like API error rates and the failure percentage of core business events (login, registration, payment) rather than just raw crash counts. A robust monitoring strategy shifts the focus from simple crash reporting to comprehensive service health. By standardizing log levels and automating event collection, development teams can distinguish between transient network blips and critical logic errors, ensuring they spend their time fixing high-impact issues.

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한 달짜리 과제, 바이브 코딩으로 5일 만에!(ChatGPT·Cursor) (opens in new tab)

This blog post explores how LY Corporation reduced a month-long development task to just five days by leveraging "vibe coding" with Generative AI tools like ChatGPT and Cursor. By shifting from traditional, rigid documentation to an iterative, demo-first approach, developers can rapidly validate multiple UI/UX solutions for complex problems like restaurant menu registration. The author concludes that AI's ability to handle frequent re-work makes it more efficient to "build fast and iterate" than to aim for perfection through long-form specifications. ### Strategic Shift to Rapid Prototyping * Traditional development cycles (spec → design → dev → fix) are often too slow to keep up with market trends due to heavy documentation and impact analysis. * The "vibe coding" approach prioritizes creating "working demos" over perfect specifications to find "good enough" answers through rapid feedback loops. * AI reduces the psychological and logistical burden of "starting over," allowing developers to refine the context and quality of outputs through repeated interaction without the friction of manual re-documentation. ### Defining Requirements and Solution Ideation * Initial requirements are kept minimal, focusing only on the core mission, top priorities, and essential data structures (e.g., product name, image, description) to avoid limiting AI creativity. * ChatGPT is used to generate a wide range of solution candidates, which are then filtered into five distinct approaches: Stepper Wizards, Live Previews with Quick Add, Template/Cloning, Chat Input, and OCR-based photo scanning. * This stage emphasizes volume and variety, using AI-generated pros and cons to establish selection criteria and identify potential UX bottlenecks early in the process. ### Detailed Design and Multi-Solution Wireframing * Each of the five chosen solutions is expanded into detailed screen flows and UI elements, such as progress bars, bottom sheets, and validation logic. * Prompt engineering is used iteratively; if an AI-generated result lacks a specific feature like "temporary storage" or "mandatory field validation," the prompt is adjusted to regenerate the design instantly. * The focus remains on defining the "what" (UI elements) and "how" (user flow) through textual descriptions before moving to actual coding. ### Implementation with Cursor and Flutter * Cursor is utilized to generate functional code based on the refined wireframes, using Flutter as the framework to ensure rapid cross-platform development for both iOS and Android. * The development follows a "skeleton-first" approach: first creating a main navigation hub with five entry points, then populating each individual solution module one by one. * Technical architecture decisions, such as using Riverpod for state management or SQLite for data storage, are layered onto the demo post-hoc, reversing the traditional "stack-first" development order to prioritize functional validation. ### Recommendation To maximize efficiency, developers should treat AI as a partner for high-speed iteration rather than a one-shot tool. By focusing on creating functional demos quickly and refining them through direct feedback, teams can bypass the bottlenecks of traditional software requirements and deliver user-centric products in a fraction of the time.

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Flutter Riverpod 200% 활용하기 (opens in new tab)

Riverpod is a powerful state management library for Flutter designed to overcome the limitations of its predecessor, Provider, by offering a more flexible and robust framework. By decoupling state from the widget tree and providing built-in support for asynchronous data, it significantly reduces boilerplate code and improves application reliability. Ultimately, it allows developers to focus on logic rather than the complexities of manual state synchronization and resource management. ### Modern State Management Architecture Riverpod introduces a streamlined approach to state by separating the logic into Models, Providers, and Views. Unlike the standard `setState` approach, Riverpod manages the lifecycle of state automatically, ensuring resources are allocated and disposed of efficiently. * **Providers as Logic Hubs:** Providers define how state is built and updated, supporting synchronous data, Futures, and Streams. * **Consumer Widgets:** Views use `ref.watch` to subscribe to data and `ref.read` to trigger actions, creating a clear reactive loop. * **Global Access:** Because providers are not tied to the widget hierarchy, they can be accessed from anywhere in the app without passing context through multiple layers. ### Optimization for Server Data and Asynchronous Logic One of Riverpod's strongest advantages is its native handling of server-side data, which typically requires manual logic in other libraries. It simplifies the user experience during network requests by providing built-in states for loading and error handling. * **Resource Cleanup:** Using `ref.onDispose`, developers can automatically cancel active API calls when a provider is no longer needed, preventing memory leaks and unnecessary network usage. * **State Management Utilities:** It natively supports "pull-to-refresh" functionality through `ref.refresh` and allows for custom data expiration settings. * **AsyncValue Integration:** Riverpod wraps asynchronous data in an `AsyncValue` object, making it easy to check if a provider `hasValue`, `hasError`, or `isLoading` directly within the UI. ### Advanced State Interactions and Caching Beyond basic data fetching, Riverpod allows providers to interact with each other to create complex, reactive workflows. This is particularly useful for features like search filters or multi-layered data displays. * **Cross-Provider Subscriptions:** A provider can "watch" another provider; for example, a `PostList` provider can automatically rebuild itself whenever a `Filter` provider's state changes. * **Strategic Caching:** Developers can implement "instant" page transitions by yielding cached data from a list provider to a detail provider immediately, then updating the UI once the full network request completes. * **Offline-First Capabilities:** By combining local database streams with server-side Futures, Riverpod can display local data first to ensure a seamless user experience regardless of network connectivity. ### Seamless Data Synchronization Maintaining consistency across different screens is simplified through Riverpod's centralized state. When a user interacts with a data point on one screen—such as "starring" a post on a detail page—the change can be propagated globally so that the main list view is updated instantly without additional manual refreshes. This synchronization ensures the UI remains a "single source of truth" across the entire application. For developers building data-intensive Flutter applications, Riverpod is a highly recommended choice. Its ability to handle complex asynchronous states and inter-provider dependencies with minimal code makes it an essential tool for creating scalable, maintainable, and high-performance mobile apps.

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테크 컨퍼런스 Tech-Verse 2025를 개최합니다 (opens in new tab)

LY Corporation is hosting its global technology conference, Tech-Verse 2025, on June 30 and July 1 to showcase the engineering expertise of its international teams. The event features 127 sessions centered on core themes of AI and security, offering a deep dive into how the group's developers, designers, and product managers solve large-scale technical challenges. Interested participants can register for free on the official website to access the online live-streamed sessions, which include real-time interpretation in English, Korean, and Japanese. ### Conference Overview and Access * The event runs for two days, from 10:00 AM to 6:00 PM (KST), and is primarily delivered via online streaming. * Registration is open to the public at no cost through the Tech-Verse 2025 official website. * The conference brings together technical talent from across the LY Corporation Group, including LINE Plus, LINE Taiwan, and LINE Vietnam. ### Multi-Disciplinary Technical Tracks * The agenda is divided into 12 distinct categories to cover the full spectrum of software development and product lifecycle. * Day 1 focuses on foundational technologies: AI, Security, Server-side development, Private Cloud, Infrastructure, and Data Platforms. * Day 2 explores application and management layers: AI Use Cases, Frontend, Mobile Applications, Design, Product Management, and Engineering Management. ### Key Engineering Case Studies and Sessions * **AI and Data Automation:** Sessions explore the evolution of development processes using AI, the shift from "Vibe Coding" to professional AI-assisted engineering, and the use of Generative AI to automate data pipelines. * **Infrastructure and Scaling:** Presentations include how the "Central Dogma Control Plane" connects thousands of services within LY Corporation and methods for improving video playback quality for LINE Call. * **Framework Migration:** A featured case study details the strategic transition of the "Demae-can" service from React Native to Flutter. * **Product Insights:** Deep dives into user experience design and data-driven insights gathered from LINE Talk's global user base. Tech-Verse 2025 provides a valuable opportunity for developers to learn from real-world deployments of AI and large-scale infrastructure. Given the breadth of the 127 sessions and the availability of real-time translation, tech professionals should review the timetable in advance to prioritize tracks relevant to their specific engineering interests.