Want to level up from simple CRUD projects? Build a secure RESTful To-Do List API that lets users create, update, and track their tasks with authentication.
How to Build a Secure RESTful To-Do List API
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New Feature Drop: GraphQL Mock Server For months, the need for a "GraphQL Mock Server" was the single most requested feature from our clients. The core issue: generic mocks can't keep pace with complex GraphQL schema and scenarios, leading to fragile client tests and slowing development. Our team took that feedback and engineered a solution for true parallel development - GraphQL Mock Servers, now one of the core features of our platform. What's inside: • Intelligent, Reliable Data: No more static JSON. AI-powered mocking analyzes your schema to generate realistic, contextual data that strictly honors Non-Null and List constraints. • Instant Contract-First Development: Simply upload your SDL or use live introspection to immediately provision a hosted, working endpoint. • Full Testing Coverage: Test every scenario, from complex data fetching (Queries), state changes (Mutations), real-time streams (Subscriptions), and efficient network loading (Batch Queries). • Resilience Testing, on Demand: Use the powerful Rules Engine to proactively inject chaos. Force specific GraphQL errors, or HTTP status codes (403/500), or inject latencies to ensure that your client is robust. If you or your teams are currently blocked by an unfinished GraphQL backend, this feature is specifically engineered to solve that bottleneck.
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➡️Dependency Injection (DI) Lifetimes in .NET Core When you register services in Program.cs using builder.Services.Add..., you specify how long each instance should live — this is called service lifetime. 1. Transient ✅ New instance created every time it’s requested. 👉 Best for lightweight, stateless services. Example use: Helper classes, formatters, or short operations. 2. Scoped ✅ One instance per HTTP request. 👉 Most common for Web API — keeps request data consistent. Example use: Business logic services, repositories. 3. Singleton Single instance for the entire application lifetime. 👉 Ideal for shared resources (e.g., cache, configuration). Example use: Logging, caching, configuration providers. ✅app.Use(), app.Run(), and app.Map() — Middleware Flow In .NET Core, middleware defines the HTTP request pipeline. ✅ Executes logic before and after next middleware. 👉 Great for logging, authentication, or request handling. ✅app.Run() Defines the end of the pipeline. Once it runs, no other middleware executes. ✅ Usually the last middleware — acts as a terminal handler. ✅app.Map() Used to branch the pipeline based on URL path. ✅ Great for defining specific route-based pipelines (like /api, /admin, etc.). 1.Use Use() for middleware, 2.Map() for routing branches, 3.and Run() to end the pipeline. ✅What is the Request Pipeline in .NET Core? The request pipeline is the sequence of middleware components that handle an HTTP request before it reaches your endpoint (controller or Razor page). Each middleware: • Can perform work before and after the next middleware. • Either passes the request to the next middleware or short-circuits the pipeline (ends response early). ✅Example pipeline flow: Request → ExceptionHandler → Routing → Authentication → Authorization → Endpoint → Response
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You’ve already built a few APIs, connected MongoDB and handled authentication. But now it’s time to take your backend skills a step further. Here are 7 core concepts that’ll help you move from beginner-friendly to production-ready. ⬇⬇⬇ 1. Middleware — Centralize logic for authentication, logging, and request validation instead of repeating it in every route. 2. Error Handling — Use centralized error middleware and consistent HTTP responses to make debugging painless. 3. Security Basics — Protect your app with input sanitization, password hashing, Helmet, and rate limiting. 4. Database Optimization — Use indexes, lean queries, and pagination to make your API faster and more efficient. 5. Caching — Store frequent responses or queries in memory using Redis or Node cache to cut down database load. 6. Testing — Write unit and integration tests so you can deploy confidently without breaking production. 7. Deployment & Environment Configs — Learn CI/CD, reverse proxies, and environment setups that make your app reliable in production. 💡 Once you start thinking in terms of these concepts, you stop “just building APIs” and start engineering systems.
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Understanding HTTP Methods: Idempotency and the Forgotten OPTIONS I've been reviewing API design lately, and it struck me how often we overlook the fundamental concepts behind HTTP methods. Let me break down something that changed how I think about building APIs. What is Idempotency? An idempotent operation produces the same result no matter how many times you execute it. Think of it like a light switch set to "on." Flipping it to "on" once or ten times gives you the same result: the light is on. The Idempotent Methods: GET - Reading data never changes it. Request the same resource 100 times, you get the same response. PUT - Designed to replace a resource completely. Update a user's profile with the same data repeatedly, and the end state remains identical. DELETE - Remove a resource once or multiple times, the result is the same: it's gone. Subsequent DELETE requests typically return 404. PATCH - While technically it can be idempotent, it depends on implementation. A well-designed PATCH that sets absolute values is idempotent. HEAD and OPTIONS - These are also idempotent by nature. The Non-Idempotent Method: POST - Each request can create a new resource or trigger a new action. Submit a payment form twice? You might get charged twice. This is why we implement safeguards like idempotency keys in payment systems. The Underutilized OPTIONS Method Here's something most developers don't use enough: OPTIONS tells clients what methods are available for a resource and what the API supports. When a client sends an OPTIONS request, the server responds with allowed methods in the Allow header. This is crucial for: - CORS preflight requests that browsers send automatically - API discovery and documentation - Determining supported operations before attempting them Example response headers: Allow: GET, POST, PUT, DELETE, OPTIONS Access-Control-Allow-Methods: GET, POST, PUT Why This Matters: Understanding idempotency helps you: - Design more reliable APIs - Handle retries gracefully in distributed systems - Prevent duplicate operations in unreliable networks - Make informed decisions about which HTTP method to use Next time you're building an API, ask yourself: should this operation be idempotent? Your answer will guide you toward the right HTTP method
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𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚 𝐑𝐞𝐝𝐢𝐬 𝐂𝐥𝐢𝐞𝐧𝐭 𝐟𝐫𝐨𝐦 𝐒𝐜𝐫𝐚𝐭𝐜𝐡 𝐢𝐧 𝐆𝐨 About one and half year ago, I built redis-cli-lite as a simple learning project but it evolved into a week of deep dive journey to network protocols, concurrency, and system design. No GPTs. No “vibe coding.” Just pure Go and a lot of coffee. After being inactive for a while, I thought I’d finally share it with the community! Although it looks production-ready, I’ll admit there are more minimal alternatives out there. Still, this one was all about learning by doing. Technical Highlights Custom RESP Protocol Implementation • Built a complete Redis Serialization Protocol (RESP) parser/tokenizer from scratch • Implemented all RESP data types: Simple Strings, Errors, Integers, Bulk Strings, and Arrays • Leveraged Go 1.18+ generics for type-safe operations Advanced Concurrency & Performance • Channel-based connection pooling for concurrent operations • Automatic retry with graceful failure handling • Context-based monitoring for real-time pool health Security-First Design • Full TLS/SSL support with certificate validation • SAN (Subject Alternative Name) certificate implementation • Secure TCP connections for production-grade deployments Dual-Mode Architecture • CLI tool for quick ops: redis-cli-lite localhost 6379 • Embeddable Go library with a clean API • Layered design: cmd / client / api / serializer Production-Ready Features • TLS/SSL support • Comprehensive unit test coverage • Type-safe API (no string-based ops) • Pretty-print output & structured error handling Why It Matters This project wasn’t just about learning Go — it was about building real systems: implementing protocols, managing concurrency, and designing secure, maintainable architecture. If you’re looking for a lightweight, dependency-minimal Redis client in Go or just curious on how good/bad of a job this strange dude did, it might be worth checking out. 🔗 GitHub: https://lnkd.in/dyv3JH3b As library: ``` api, err := api.Initialize("localhost", 6379, 10, nil) if err != nil { panic(err) } resp, err := api.Ping() ``` As cli tool:
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What is API Gateway An API Gateway is a server that acts as the single entry point for all clients. It provides a unified interface to a set of microservices, simplifies the client-side code, and hides the internal structure of the application. Here is a detailed breakdown of its functions: 1. Client Request Handling: The API Gateway receives HTTP requests from various client devices and applications. 2. Request Validation: It checks that the incoming requests are well-formed and have correct format and necessary parameters. 3. Access Control Lists: It implements allow-lists and deny-lists to control access to various services, preventing unauthorized requests from proceeding. 4. Authentication and Authorization: It interacts with authentication services to verify the identity of the requester and checks permissions to ensure they are authorized to access the requested resources. 5. Rate Limiting: It applies predefined rules to limit the number of requests a client can make within a certain time frame to prevent abuse and manage load. 6. Service Discovery: It identifies the appropriate services required to fulfill the request based on the request path, parameters, or headers. 7. Dynamic Routing: It directs the validated and authorized requests to the correct backend services. 8. Protocol Translation: It converts the request from the web-friendly protocols like HTTP/HTTPS to the specific protocols used by the backend services, if necessary. 9. Error Handling: It catches and handles any errors that may arise during the processing of requests, ensuring graceful degradation of service. 10. Circuit Breaking: It implements patterns to detect failures and prevent overloading the system, avoiding cascading failures in interconnected services. 11. Monitoring and Logging: It utilizes tools like the ELK stack for logging requests and responses, which is crucial for monitoring, tracing, and debugging. 12. Caching: It optionally stores responses to common requests, reducing the number of calls to the backend services.
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The source defines the structure of the video and explicitly lists the key concepts and evidence that must be included, all drawn from the project log: 1. The Debugging Focus: The most important part of the video is defined as the real-world debugging process. 2. The Initial Symptom: The script must mention that the application deployed, but the browser showed a generic error: "Error interacting with the database". 3. The Method: The script must explain that the real error was hidden and was found by going into AWS CloudWatch Logs. 4. The Root Cause: The central finding required for the video is the specific error: Error: Object of type Decimal is not JSON serializable. 5. The Fix: The script must show the one-line code fix: visit_count = int(visit_count). 6. The Final Proof: The script must conclude by showing the visit count going from 8 to 9 upon refreshing the page. Log Verification (Sources,,) All of these mandated points correspond precisely to Bug 3: Runtime Error (The "Decimal" Bug) and the subsequent successful resolution detailed in the project log: • The log confirms the problem: "The app deployed, but visiting the URL returned... 'Error interacting with the database.'". • The log confirms the debug method: "I went to the AWS Console and opened the CloudWatch Logs for my Lambda function.". • The log confirms the root cause: "The logs showed the real error: Error: Object of type Decimal is not JSON serializable.". • The log confirms the fix: "I edited my app.py file and added one line of code (visit_count = int(visit_count))". • The log confirms the success: "The browser returned... your 8 visit... I refreshed the page, and it returned: your 9 visit.".
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I'm happy to share another 𝗦𝘆𝗻𝘁𝗮𝘅𝗶𝗹𝗶𝘁𝗬 𝗡𝗲𝘅𝘁 𝗔𝗽𝗽 𝗖𝗟𝗜 — 𝗧𝗵𝗲 𝗨𝗹𝘁𝗶𝗺𝗮𝘁𝗲 𝗡𝗲𝘅𝘁.𝗷𝘀 𝗦𝘁𝗮𝗿𝘁𝗲𝗿 𝗳𝗼𝗿 𝗠𝗼𝗱𝗲𝗿𝗻 𝗦𝗮𝗮𝗦 & 𝗔𝗜 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 project I recently worked for the developers. The 𝗦𝘆𝗻𝘁𝗮𝘅𝗶𝗹𝗶𝘁𝗬 𝗡𝗲𝘅𝘁 𝗔𝗽𝗽 𝗖𝗟𝗜 empowers developers to bootstrap scalable, production-ready Next.js 14+ applications in seconds using: 𝙣𝙥𝙭 𝙘𝙧𝙚𝙖𝙩𝙚-𝙨𝙮𝙣𝙩𝙖𝙭𝙞𝙡𝙞𝙩𝙮-𝙣𝙚𝙭𝙩-𝙖𝙥𝙥@𝙡𝙖𝙩𝙚𝙨𝙩 This CLI generates a feature rich, enterprise-grade architecture with authentication, theming, database ORM, API utilities, and state management all preconfigured and ready for immediate development. It’s designed to eliminate repetitive boilerplate setup so teams can focus on innovation, not initialization. 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: • Authentication: Built-in Clerk integration with OAuth, email, and social logins. • Theming System: Dark/light theme persistence powered by Skiper UI and HeroUI. • State Management: Lightweight global state management using Zustand with TypeScript support. • Database Ready: Integrated Prisma ORM setup for PostgreSQL, easily customizable for other databases. • API Framework: Unified API response handlers and data provider abstractions for UI integration. • Middleware + Proxy: Route protection, server proxy handling, and secure server-side communication. • Folder Architecture: Clean, modular structure designed for scalability and maintainability. • Environment System: .env preconfiguration for backend services, API keys, and AI integrations. 𝗢𝘃𝗲𝗿𝗰𝗼𝗺𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝗶𝗲𝘀: • Authentication and user management • UI theming and component libraries • ORM and database schema setup • State management wiring • Secure middleware and API routing 𝗚𝗶𝘁𝗛𝘂𝗯: https://lnkd.in/d9Fchc-T 𝗻𝗽𝗺: https://lnkd.in/dBxHPdde 𝗻𝗽𝘅: npx create-syntaxility-next-app@latest my-app
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Interesting pattern for tool overload. The agent writes its own code to interact with MCP servers and over time it builds a library of skills that it can reuse. I like that self-improvement pattern. It also makes me think that if agents are great at writing their own MCP clients, they could also write their own API clients (provided proper Open API spec is available), which leads to the thought: maybe we don’t need MCP then? MCP was born as a standard protocol to plug and play stuff without having to write a custom integration. The key point was that the model could figure out the interfaces at run time. It worked beautifully. But it is proving to be token intensive (slow and expensive). Anthropic themselves are suggesting writing clients on the fly instead for efficiency. Of course this brings more security questions as you’d need to allow the agent to execute its own code. Code that is connected and authenticated against your sensitive data. What do you think? https://lnkd.in/gERFfYDe
