Understanding API Development

Revisiting My Viral API Terminology Guide: Still Essential Knowledge 2 Years Later! Two years ago, I created an API Terminology Guide that unexpectedly went viral. Today, I'm resharing this resource because its relevance has only grown stronger with time. Why it matters now more than ever: 1. API literacy is no longer just for tech roles. It's crucial for:    - Project Managers    - Business Analysts    - C-level Executives    - And anyone involved in modern business operations 2. APIs are the backbone of:    - Business integrations    - Data exchanges    - Service compositions The language of APIs is the language of modern business. My API Terminology Guide offers a comprehensive overview of key terms and concepts. Whether you're a seasoned pro or new to the tech sector, it's designed to enhance your understanding and improve communication. If this guide helped you before or you're discovering it for the first time, please share it with your network. Let's continue to bridge the knowledge gap in our evolving tech landscape! P.S. I'm curious: How have you seen the importance of API knowledge change in your field over the last two years? Share your thoughts in the comments!

“Should OpenAPI be treated as supplementary documentation, evolve alongside requirements, or serve as the primary source of truth?” That was the sharp question one of my API PM students asked yesterday. So what’s the answer? API Descriptions—including OpenAPI Initiative, AsyncAPI Initiative, GraphQL Foundation schemas, and Protobufs—can sit at the center of every stage of the API lifecycle. Here’s how: 1. IDEATION & PROTOTYPING Use your API Description Document as a design artifact for Mock APIs. Share these prototypes with customers for discovery and validation. 2. DESIGN & DEVELOPMENT Treat the API Description Document as a Contract—validated against organizational standards—to ensure the final delivery aligns with the initial market-validated design. Enforce this with contract testing in your CI/CD pipeline to keep the contract and implementation in sync. 3. SECURITY Take that same API Description Document (which exactly matches the implementation because you’re testing it!) and run it through specialized vulnerability scanners to ensure you meet security and privacy standards. 4. DOCUMENTATION Your API Description Document doubles as the blueprint for interactive documentation in your Developer Portal. Involve your tech writers directly in that doc, then use it to render and continuously test your published docs so they never diverge from what’s actually delivered. 5. RUNTIME CONFIGURATION Gateways, Monitoring, and Analytics tools can ingest the API Description Document for consistent configuration across environments. Many top-tier tools already support this workflow. 6. CLIENTS Providing a public API Description Document lets your consumers easily generate SDKs and scaffold clients. So, check your API Descriptions into version control alongside your code and use them throughout the lifecycle as a living contract. And spoiler alert—AI is already enhancing every stage of the API lifecycle. We’ll dig into that in a separate post. Are you using API Description Documents as contracts today? My students and I would love to hear your real-world scenarios—drop them in the comments!

"🌟 Best Practices for Designing REST APIs 🌟 Designing REST APIs that are efficient, scalable, and easy to use is crucial for building robust web services. By following best practices, you can ensure your APIs are well-structured and maintainable. Here are some key best practices to consider: 1. Use Meaningful Resource Names: - Use nouns to represent resources, such as `/users`, `/orders`, and `/products`. - Avoid using verbs in endpoint paths, keeping URLs clean and intuitive. 2. Consistent Naming Conventions: - Stick to a consistent naming convention, such as using lowercase letters and hyphens (`-`) to separate words. - Ensure uniformity across all endpoints to make the API predictable. 3. Versioning Your API: - Implement versioning in your API URLs, such as `/v1/users`. - This allows you to introduce breaking changes without disrupting existing clients. 4. Use HTTP Status Codes: - Return appropriate HTTP status codes for different outcomes (e.g., `200 OK`, `201 Created`, `400 Bad Request`, `404 Not Found`, `500 Internal Server Error`). - This helps clients understand the result of their requests clearly. 5. Implement Pagination: - For endpoints that return large datasets, implement pagination to improve performance and manageability. - Use query parameters like `?page=1&limit=10` to control data retrieval. 6. Provide Error Messages: - Return meaningful error messages in the response body to help clients debug issues. - Include error codes, descriptions, and possible solutions. 7. Secure Your API: - Implement authentication and authorization mechanisms, such as OAuth, JWT, or API keys. - Use HTTPS to encrypt data transmission and protect sensitive information. 8. Documentation: - Provide comprehensive and up-to-date documentation using tools like Swagger or OpenAPI. - Include examples, endpoint descriptions, request/response formats, and authentication methods. 9. Statelessness: - Ensure that each request from the client contains all the information needed for the server to fulfill it. - Avoid storing client context on the server between requests to maintain scalability and simplicity. 10. Caching: - Implement caching strategies to reduce server load and improve response times. - Use HTTP caching headers (`Cache-Control`, `ETag`, etc.) to control cache behavior. By adhering to these best practices, you can design REST APIs that are user-friendly, efficient, and maintainable, enhancing the overall developer experience. What best practices do you follow when designing REST APIs? How have these practices improved your API design? Share your thoughts and experiences in the comments below! Let's discuss and learn from each other. For more insights and tips on REST API design, be sure to follow my LinkedIn profile: [https://lnkd.in/gAiSRGut) #WebDevelopment #RESTAPI #APIDesign #BestPractices #SoftwareDevelopment #TechCommunity"

REST vs GraphQL Explained: You can't build great APIs if you choose the wrong architecture. 📌 REST: ◾ Each request must contain all the information needed to process the request ◾ REST APIs expose resources (e.g., /users, /orders) as endpoints. Each resource is represented by a unique URL ◾ Uses standard HTTP methods and status codes to indicate the result of operations (e.g., 200 OK, 404 Not Found) This comes with: ↳ A clear decoupling between the client and server ↳ Easier caching integration ↳ Simplicity in the system. But it can be prone to overfetching: For example, a /users endpoint might return all user details when the client only needs a username and email. 📌 GraphQL: ◾ All requests are sent to a single endpoint, and the client specifies the data it needs in the query ◾ GraphQL APIs are defined by a schema that specifies the types of data available and their relationships ◾ Clients can request only the data they need and use nested queries, avoiding overfetching and underfetching. This has the benefit of flexibility and efficiency if you know exactly the data you're requesting, and is generally resilient to schema changes. It comes with the cost of complexity for the system: ↳ Understanding of schemas, resolvers, and query optimization/caching patterns. Recap: ◾ REST: Like ordering from a fixed menu, you get predefined portions, even if you don’t need everything on the plate. ◾ GraphQL: Like a buffet, you pick exactly what you want, but you need to know what’s available. What’s your preferred API design approach, and why? ~~~ 👉🏻 Join 50,001+ software engineers getting curated system design deep dives, trends, and tools (it's free): ➔ https://lnkd.in/dkJiiBnf ~~~ If you found this valuable: 👨🏼💻 Follow Alexandre Zajac 🔖 Bookmark this post for later ♻️ Repost to help someone in your network #softwareengineering #systemdesign #programming

API Design Principles Great APIs aren’t just functional, they’re usable, scalable, and easy to evolve. Here are 10 principles that guide better API development, especially in complex, fast-moving teams: 1. Single Source of Truth ➟ Your API design should live in one place, not scattered across docs, mocks, and test scripts. ➟ Fragmentation leads to version drift and painful debugging. 2. Contract First ➟ Start with a clear spec that defines how your API behaves before writing code. ➟ Whether it's OpenAPI or AsyncAPI, this keeps teams aligned and integration smooth. 3. Strong Typing Saves Time ➟ Define data types, formats, and constraints. ➟ This isn't just for code, it helps consumers avoid misfires and understand expectations fast. 4. Self-Descriptive Responses ➟ Your API should explain itself. Use consistent status codes, error messages, and response formats. 5. Documentation as a Feature ➟ Good docs reduce support tickets. Great docs build trust. ➟ Automate them from your spec and keep them in sync, manually updated docs are a trap. 6. Fail Fast, Validate Early ➟ Catch mistakes before production. ➟ Validation, linting, and autocomplete are must-have, not luxuries. 7. Minimal Surprise ➟ Keep your endpoints consistent in naming, structure, and behavior. ➟ Predictability = Usability. 8. Versioning is Not a Dirty Word ➟ APIs evolve. Be explicit. ➟ Support versions and never surprise your consumers. 9. Security Without Sacrificing Flow ➟ Security shouldn’t slow you down. ➟ Encryption, access controls, and compliance should be built-in, not bolted on. 10. Tooling Matters ➟ The best teams reduce friction between design, test, and docs. ➟ Tools should fit your workflow, not force you into theirs. That’s why this month’s release from Postman caught my eye. They introduced Spec Hub and types in collections: • Design, test, and document in one place • Sync specs, docs, and tests with one click • Schema validation, even for collection-first workflows • BYOK encryption control without losing flexibility. No API-building tool has stuck with me longer than Postman. Check their latest update here http://fnf.dev/4ltYvYS If you’re tired of managing chaos instead of building great APIs, this update is for you. Big thanks to the Postman team for collaborating on this.

Top 9 HTTP Request Methods Every Developer Should Know! Whether you're building APIs, designing web services, or debugging applications, understanding HTTP request methods is a must-have skill for modern developers. This infographic breaks down the 9 most commonly used HTTP methods, their purposes, and practical examples of how they work. 🔑 Here's What You Should Know: 1️⃣ GET Used to retrieve data from a server. 👉 Example: GET /v1/products/iphone The server responds with the requested data, such as details about an iPhone product. Ideal for fetching single items or lists of resources. 2️⃣ POST Used to create new resources. 👉 Example: POST /v1/users Send a JSON payload (e.g., user details) to the server, and it creates a new resource. 3️⃣ PUT Used to completely replace an existing resource. 👉 Example: PUT /v1/users/123 Send the full updated data for a user, and the server replaces the old resource with the new one. 4️⃣ PATCH Used to partially update an existing resource. 👉 Example: PATCH /v1/users/123 Send only the fields you want to update (e.g., updating just an email). 5️⃣ DELETE Used to remove a resource. 👉 Example: DELETE /v1/users/123 The server deletes the specified user. 6️⃣ HEAD Fetches headers for a resource without downloading the full body. 👉 Example: HEAD /v1/products/iphone Great for checking metadata or verifying resource availability. 7️⃣ OPTIONS Used to discover the HTTP methods supported by an endpoint. 👉 Example: OPTIONS /v1/users The server responds with the allowed methods (e.g., GET, POST, DELETE, etc.). 8️⃣ CONNECT Establishes a two-way connection (like for tunneling through a proxy). 👉 Example: CONNECT example.com:80 9️⃣ TRACE Used for debugging; it performs a loop-back test to verify communication. 👉 Example: TRACE /index.html Why This Matters: Efficiency: Choose the right method for the right task to optimize your APIs. Performance: Avoid over-fetching or unnecessary operations by using methods purposefully. Security: Understand which methods expose vulnerabilities (e.g., over-permissive TRACE) and implement safeguards. Pro Tip: Pair these methods with proper status codes (like 200 OK, 404 Not Found, etc.) and authentication for a robust API design.

REST API Cheat sheet If I had to learn REST API from 0, this is what I would focus on 🏛️ Architectural Principles of REST 𝟭. 𝗖𝗹𝗶𝗲𝗻𝘁-𝗦𝗲𝗿𝘃𝗲𝗿 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 • 𝗦𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗖𝗼𝗻𝗰𝗲𝗿𝗻𝘀:    • Clients handle user interface and interactions.    • Servers manage business logic and data storage. • 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:    • Enables independent evolution, updates of client and server components.    • Allows flexibility to use different platforms and programming languages. 𝟮. 𝗦𝘁𝗮𝘁𝗲𝗹𝗲𝘀𝘀𝗻𝗲𝘀𝘀 - Each request from the client to the server must contain all the information needed to process it.    • No session state is stored server-side. • 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:    • Improves scalability since server doesn't need to remember client sessions.    • Enables load balancers to distribute requests efficiently. • 𝗘𝘅𝗮𝗺𝗽𝗹𝗲:     • Include an authorization token in each request rather than relying on a server-side session. 𝟯. 𝗖𝗮𝗰𝗵𝗲𝗮𝗯𝗶𝗹𝗶𝘁𝘆 • 𝗞𝗲𝘆 𝗣𝗼𝗶𝗻𝘁𝘀:    • Responses must explicitly state their cacheability via headers (`Cache-Control`, `ETag`).    • Improves speed by avoiding repetitive server processing for identical requests. • 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:    • Reduces latency for users.    • Lightens server load and enhances performance. 𝟰. 𝗟𝗮𝘆𝗲𝗿𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺 • 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲:    • REST APIs allow intermediaries (e.g., load balancers, caches) to enhance functionality.    • Requests might pass through multiple layers before reaching server. • 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:    • Enhances scalability and resilience by isolating each layers responsibility.    • Prevents clients from interacting directly with backend systems. 𝟱. 𝗨𝗻𝗶𝗳𝗼𝗿𝗺 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲 • 𝗖𝗼𝗿𝗲 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀:    • Resource identification through URIs (e.g., `/users/123`).    • Representation-based resource manipulation (e.g., JSON, XML).    • Self-descriptive messages with clear metadata.    • Stateless interactions that use standard HTTP methods. • 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:    • Simplifies integration with diverse systems by adhering to a consistent standard. 🌐 𝗛𝗧𝗧𝗣 𝗠𝗲𝘁𝗵𝗼𝗱𝘀: 𝟭. 𝗚𝗘𝗧 • 𝗣𝘂𝗿𝗽𝗼𝘀𝗲: Retrieve data from server. • 𝗧𝗿𝗮𝗶𝘁𝘀:    • Safe: Doesn’t change server data.    • Idempotent: Multiple identical requests produce the same result.    • Headers: `Cache-Control`, `If-Modified-Since`, `ETag`. • 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: /users/123 - Get details for user ID 123. 𝟮. 𝗣𝗢𝗦𝗧 • 𝗣𝘂𝗿𝗽𝗼𝘀𝗲: Create new resources on server. • 𝗧𝗿𝗮𝗶𝘁𝘀:    • Not idempotent: Sending the same request multiple times may create duplicate resources.    • Typically used to send data in the request body.    • Headers: `Content-Type`, `Location` (for the new resource). • 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: /users - Add a new user to the database. Continued here: https://lnkd.in/g6q-VZBn

𝟗 𝐊𝐞𝐲 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬 𝐭𝐨 𝐁𝐨𝐨𝐬𝐭 𝐀𝐏𝐈 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 ◾ Use Caching Store frequently accessed data in memory so you don’t have to fetch it from the database or other slow sources repeatedly. This drastically cuts down on response time. ◾ Minimize Payload Size Send only the necessary data in responses. Avoid sending large, unneeded chunks of data by filtering fields or compressing the payload, which reduces bandwidth usage and speeds up responses. ◾ Use Asynchronous Processing For tasks that don’t need an immediate response (like sending emails or processing large data sets), use asynchronous methods. This keeps the API responsive while the heavy work happens in the background. ◾ Load Balancing Distribute incoming API requests across multiple servers to prevent any single server from becoming overloaded. This improves availability and handles more traffic efficiently. ◾ Optimize Data Formats Use lightweight data formats like JSON or Protocol Buffers instead of XML. Smaller data formats reduce the time spent parsing and transmitting data. ◾ Connection Pooling Reuse existing connections to the database or other services rather than opening a new one for each request. Connection pooling significantly reduces the overhead of establishing connections. ◾ Use Content Delivery Networks (CDNs) For APIs serving static content (such as images or scripts), use CDNs to deliver content more quickly by caching it closer to the user’s location, thereby reducing latency. ◾ Implement API Gateway An API Gateway can help in routing requests, handling authentication, rate limiting, and caching. By offloading these tasks from your API, you can improve its overall performance. ◾ Avoid Overfetching and Underfetching Design your API endpoints to return the exact amount of data required. GraphQL, for example, allows clients to request exactly what they need, thereby avoiding the issues of overfetching and underfetching common in REST APIs. 📌 Liked this post? Join my free newsletter: https://lnkd.in/gpHAFd9t 📌Reference: Grokking the System Design Interview - https://lnkd.in/giwyzfkT #api #systemdesign #rest #grpc

You can do some mindblowing automation of Power BI development tasks by calling AI models via Power Query/M and C# scripts. However, always keep your API keys securely protected. Here's how... 🔸 WHAT ARE API KEYS? An API (Application Programming Interface) is a software "bridge" that allows applications to talk with each other. An API key is a combination ID and password that identifies you and tells the API that you are authorized to access the app. 🔸 GENERATING API KEYS Let's assume you're using Open AI models, but others operate in a very similar way. 🔹 Go to https://lnkd.in/ekJmYYeN and log in 🔹 I strongly recommend creating separate keys for each project to track usage, so choose or create a project via the dropdown at the top left 🔹 Select "Create a New Secret Key" 🔹 Give your key a name, set the permissions level, and click "Create Secret Key" 🔹 You will now see your full key and be allowed you to copy it. THIS IS THE ONLY CHANCE YOU WILL GET TO SEE THE FULL KEY. At this point, I copy the key into a separate encrypted password keeper so I can access the full string in the future. 🔸 WHY IS IT SO IMPORTANT TO PROTECT MY KEYS? Open AI subscribers and non-subscribers both have access to the API service, which operates on a per-request, pay-as-you-go framework. Costs are a function of the model you're using, and the amount of info you're sending and receiving - typically a fraction of a cent per API call. However, if you inadvertently release your API key, others can use it and the costs will accrue to you - just as if you'd given them your credit card info. To protect yourself, you can set warnings when your credits drop below a certain level, set limits on charges, and closely monitor usage. But best to protect your API keys from the start. 🔸 SECURING YOUR API KEYS 1) Environment Variables This is my preferred approach, where you set an alias for the key within the operating system. In Windows, just click on the Start Menu, and search for "Edit environment variables for your account". Create a new variable, give it a name, and copy your API key value into it. You can now safely call your API key by its variable name in scripts w/o revealing its value to anyone viewing your script. 2) Keyring Library Both Python and R have a package called "keyring" which allows you to enter your API key once. The package encrypts your key and enables you to assign a name to it. This works very similarly to an environment variable, but is only accessible from within Python or R. 3) Local Text File This method is recommended only if you can't use either of the above methods. You can store your API key in a local text file, and access it via M Code: apiKey = Text.FromBinary(File.Contents("C:\\temp\\PQ_API_KEY.txt")), Just be sure not to post the text file along with your script. #APIs to #AI models open a whole world of incredibly powerful capabilities, which we'll explore in future posts.

💡 New Tutorial: Building Flexible GraphQL APIs with Spring Boot Want to simplify your GraphQL API development? In my latest video, I show you how to build a dynamic book search API using Spring Boot's Query by Example (QBE) feature. Key highlights: • Create flexible search endpoints without writing tons of custom methods • Use @GraphQLRepository to automatically wire up your data fetchers • Implement dynamic querying with minimal boilerplate code • Set up a complete working example with PostgreSQL What I love about this approach is how it lets you focus on your domain logic instead of writing repetitive query methods. Perfect for when you need flexible search capabilities but don't want to maintain complex query builders. The best part? You get all this functionality with just a few annotations and interfaces - no need to write manual data fetchers or complex controllers. 🔗 Check out the full tutorial and grab the source code from the repository. What's your experience with GraphQL in Spring Boot? Have you tried Query by Example before? Share your thoughts in the comments! #SpringBoot #GraphQL #Java #Programming #SoftwareEngineering https://lnkd.in/ehK_mRVf