#Http Request Methods Get Post Put Delete Diagram

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#Http Request Methods Get Post Put Delete Diagram Reel by @heyshaill - A read-heavy API is an Application Programming Interface (API) for a system where data retrieval (read operations) happens far more frequently than da
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@heyshaill
A read-heavy API is an Application Programming Interface (API) for a system where data retrieval (read operations) happens far more frequently than data modification (write operations, such as create, update, or delete). The primary design goal for such APIs and the systems they interact with is to maximize read throughput and minimize latency for fetching data at scale. Architectural Strategies for Read-Heavy APIs 1️⃣ Pagination: Large datasets are returned in smaller chunks (pages) to reduce the memory and processing load on both the server and the client. 2️⃣ Caching: This is the most critical strategy. Frequently accessed data is stored in faster, in-memory caches (like Redis or Memcached) or even at the client, API gateway, or CDN level to avoid hitting the main database for every request. 3️⃣ Database Replication: Multiple read-only copies (replicas or slaves) of the primary database are maintained. The main database handles all write operations, while read requests are distributed across the replicas to balance the load. 4️⃣ Load Balancing: Traffic is distributed across multiple servers to prevent performance bottlenecks and ensure efficient handling of read requests.
#Http Request Methods Get Post Put Delete Diagram Reel by @codekarlo - REST APIs and GraphQL are two popular approaches for building and consuming web services. REST APIs expose data through multiple endpoints, relying on
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@codekarlo
REST APIs and GraphQL are two popular approaches for building and consuming web services. REST APIs expose data through multiple endpoints, relying on standard HTTP methods (GET, POST, PUT, DELETE), but often result in over-fetching or under-fetching due to fixed data structures. GraphQL, on the other hand, offers a single endpoint where clients can query for specific data, providing greater flexibility and efficiency for complex client needs. #programming #api #graphql #restapi #coding
#Http Request Methods Get Post Put Delete Diagram Reel by @contactformtoanyapi - APIs don't want stories.
They want structure.
CF7AA gives you complete control over what your API receives:
• Clean JSON
• Correct types
• No formatti
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@contactformtoanyapi
APIs don’t want stories. They want structure. CF7AA gives you complete control over what your API receives: • Clean JSON • Correct types • No formatting issues • No email parsing • No lost fields Devs love it because the payload is predictable. Teams love it because nothing breaks downstream. 🚀 See how it works → https://lnkd.in/dHYverQb Start building cleaner, more reliable integrations today. #APIs #APIIntegration #JSON #DeveloperTools #WordPressDevelopers #CF7 #ContactForm7 #Webhooks #BackendDevelopment #NoCodeTools #LowCode #DataIntegrity #CleanData #AutomationTools #SaaSTech #MarTech #DevLife #BuildInPublic
#Http Request Methods Get Post Put Delete Diagram Reel by @getyotta - GraphQL vs REST API - two ways to talk between client & server 💬
.
REST sends multiple requests for different data, while GraphQL fetches everything
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@getyotta
GraphQL vs REST API — two ways to talk between client & server 💬 . REST sends multiple requests for different data, while GraphQL fetches everything in one go . Result: faster, flexible, and perfect for modern apps 🚀 . . . #coding #programming #javascript #server #client data meta graphql restapi api webdevelopment backend frontend softwaredevelopment programming developer tech
#Http Request Methods Get Post Put Delete Diagram Reel by @neatroots - 1 Million RPS isn't about code, it's about architecture.
Here are the 8 key layers to scale your API architecture.

👉 Distributes traffic across mult
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@neatroots
1 Million RPS isn't about code, it's about architecture. Here are the 8 key layers to scale your API architecture. 👉 Distributes traffic across multiple servers so no single machine melts. Example: 1M req/s split across 200 servers = only 5k req/s each. ⸻ 2️⃣ Horizontal Scaling 👉 Add more servers when traffic spikes instead of upgrading one big server. Example: Black Friday? Spin up 50 more API nodes in seconds. ⸻ 3️⃣ Caching Layer 👉 Serve frequent reads from Redis/Memcached to avoid DB overload. Example: User profile cached → avoids 10M database hits/day. ⸻ 4️⃣ CDN for Static Content 👉 Images and static assets load from edge servers near the user. Example: A user in Delhi gets images from a Delhi CDN node. ⸻ 5️⃣ Async Processing (Queues) 👉 Push heavy tasks to Kafka/SQS so API responds instantly. Example: Payment API returns fast → receipt email sent in background. ⸻ 6️⃣ Database Sharding 👉 Split huge datasets across multiple DB shards to scale reads/writes. Example: Users A–M on shard 1, N–Z on shard 2. ⸻ 7️⃣ Rate Limiting 👉 Block or throttle abusive clients to protect server capacity. Example: “100 requests/sec limit” prevents bots from killing the API. ⸻ 8️⃣ Lightweight Payloads 👉 Reduce JSON response size to cut latency and bandwidth. Example: Return only “id, name, price” instead of 20 unnecessary fields. #systemdesign #apidesign #scaling #1millionrps #distributedsystems #loadbalancing #caching #microservices #softwaredeveloper #programming #coding #devops #tech #backenddeveloper #backenddevelopment #api #interviews #database #learninganddevelopment #tech [API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]
#Http Request Methods Get Post Put Delete Diagram Reel by @mhrithikk - GraphQL: https://www.instagram.com/reel/DVTon8Ok2FD/

Every API is simply a different answer to one core question: How should the client talk to the s
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@mhrithikk
GraphQL: https://www.instagram.com/reel/DVTon8Ok2FD/ Every API is simply a different answer to one core question: How should the client talk to the server? Understanding the differences is essential for backend engineers, DevOps professionals, and system design learners. • REST – Simple, stateless, and widely adopted. Ideal for most web and mobile applications. • SOAP – Structured, contract-driven, and highly secure. Best for financial and enterprise systems. • gRPC – High-performance, low-latency communication using Protocol Buffers. Built for microservices. • GraphQL – Client-controlled queries. Fetch exactly what you need with a single endpoint. The right architecture decision depends on speed, control, scalability, and business requirements. Mastering these API types strengthens your system design foundation and makes you industry-ready. Save this for your backend fundamentals. Share it with someone learning system design. #api #tech #restapi #systemdesign #graphql
#Http Request Methods Get Post Put Delete Diagram Reel by @muhammad_awais_safdar - 𝐇𝐨𝐰 𝐝𝐨 𝐲𝐨𝐮 𝐝𝐞𝐬𝐢𝐠𝐧 𝐚𝐧 𝐀𝐏𝐈 𝐭𝐡𝐚𝐭 𝐬𝐮𝐫𝐯𝐢𝐯𝐞 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 𝐨𝐟 𝐫𝐞𝐪𝐮𝐞𝐬𝐭𝐬 𝐩𝐞𝐫 𝐬𝐞𝐜𝐨𝐧𝐝 ? 👉 Such a design of API
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@muhammad_awais_safdar
𝐇𝐨𝐰 𝐝𝐨 𝐲𝐨𝐮 𝐝𝐞𝐬𝐢𝐠𝐧 𝐚𝐧 𝐀𝐏𝐈 𝐭𝐡𝐚𝐭 𝐬𝐮𝐫𝐯𝐢𝐯𝐞 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 𝐨𝐟 𝐫𝐞𝐪𝐮𝐞𝐬𝐭𝐬 𝐩𝐞𝐫 𝐬𝐞𝐜𝐨𝐧𝐝 ? 👉 Such a design of API requires a layered and distributed architecture . Let’s see the strategies involved : 1️⃣ Use multi tier layered caching mechanism : ➡️Edge CDN for static or global data ➡️Redis clusters for dynamic user data ➡️It slashes DB load by 90 percent and above. 2️⃣ Use Horizontal auto scaling plus global load balancer : ➡️ Run stateless services in ECS across regions ➡️ Balance load using Nginx or AWS global accelarator. ➡️ This distribute load dynamically and prevent single point of failure. 3️⃣ Use Sharding and replicated nosql storage : ➡️ Use partition data using consistent hashing in Cassandra or dynamodb. ➡️ Apply multi master replication and read replicas ➡️ It scales writes in linear fashion to millions per second by parallelising across shards. 4️⃣ Use advanced rate limiting : ➡️ Apply distributed token bucket per API key or IP. ➡️ Use circuit brakers ➡️ They throttle abuser and isolate faulty downstreams #SystemDesign #BackendDevelopment #SoftwareEngineering #Scalability #CodingTips TechArchitecture API CloudComputing DevOps
#Http Request Methods Get Post Put Delete Diagram Reel by @solidcode.work - 👉 An 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 acts as a single entry point for clients, handling request routing, authentication, rate limiting, protocol translation an
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@solidcode.work
👉 An 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 acts as a single entry point for clients, handling request routing, authentication, rate limiting, protocol translation and microservice communication. 👉 A 𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗿 distributes incoming traffic across multiple servers, preventing bottlenecks, maximising throughput and ensuring high availability. Key differences: 🔸 API Gateways manage how requests are handled, Load Balancers manage where traffic goes. 🔸 API Gateways operate at Layer 7, Load Balancers operate at Layer 4 or Layer 7. 🔸 API Gateways offer auth, rate limiting, routing, circuit breakers, Load Balancers handle traffic distribution and failover. 🔸 API Gateways can transform requests (e.g. JSON to XML), Load Balancers don’t touch the payload, they just route it efficiently.
#Http Request Methods Get Post Put Delete Diagram Reel by @sujan.codes - Bad API responses make apps hard to use and scale.�Good API responses make everything simple.�

When a client calls an API,�the server sends back a re
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@sujan.codes
Bad API responses make apps hard to use and scale.�Good API responses make everything simple.� When a client calls an API,�the server sends back a response. A good API response should be clear, consistent, and structured. Professional APIs usually return responses like this: They include three main parts. First — the data�This contains the actual information requested. Second — the status or success indicator�This tells whether the request succeeded or failed. Third — the metadata, like pagination info or timestamps. For example, pagination APIs include:�total count�current page�next cursor Good APIs also use proper HTTP status codes: �200 for success�404 for not found�500 for server error Consistency is very important. All responses should follow the same format�so frontend developers can handle them easily. In simple words:�good API responses are structured, predictable, and easy to understand.
#Http Request Methods Get Post Put Delete Diagram Reel by @tech_tonic_s - ▶️ GraphQL is not universally overhyped; rather, it is a powerful tool designed to solve specific, complex problems that standard REST APIs handle les
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@tech_tonic_s
▶️ GraphQL is not universally overhyped; rather, it is a powerful tool designed to solve specific, complex problems that standard REST APIs handle less efficiently. The decision between REST and GraphQL depends entirely on the project's specific needs. ▶️ GraphQL was introduced as a modern alternative to REST, promising flexibility and efficiency. Instead of multiple endpoints returning fixed data structures (like REST), GraphQL uses a single endpoint where the client requests exactly the data it needs. ➡️ With REST: • Multiple endpoints • Fixed response format • Simple caching • Easier debugging • Mature ecosystem ➡️ With GraphQL: • Single endpoint • Client-controlled queries • Reduces over-fetching & under-fetching • Strong for complex frontends • Great for large-scale UI applications But here’s where the debate begins. GraphQL introduces additional backend complexity. Caching is harder. Query optimization requires careful design. Poorly written queries can create performance issues. Monitoring and debugging are also more involved compared to REST. The real answer? GraphQL is not overhyped — but it is often overused. #restapi #graphql #restvsgraphql #api #graphqlapi
#Http Request Methods Get Post Put Delete Diagram Reel by @sujan.codes - What if 1 million users request the same API at the same time?�Without caching, your database would crash.
�This is why APIs use caching."

"Let's sta
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@sujan.codes
What if 1 million users request the same API at the same time?�Without caching, your database would crash. �This is why APIs use caching.” “Let’s start from the basics. When a client requests data, �the server usually fetches it from the database. But database calls are slow and expensive. If thousands of users request the same data,�the server would repeatedly hit the database. To solve this, APIs use caching. Here’s how it works. Step 1: Client sends a request. Step 2: Server first checks the cache. If data exists in cache → return it immediately. If not → fetch data from database, �store it in cache, and return it. Now future requests are served from cache,�not the database. This makes APIs:�faster�reduces database load�improves scalability Cache is usually stored in systems like Redis. In simple words:�API caching stores frequently requested data�so the server doesn’t query the database every time.
#Http Request Methods Get Post Put Delete Diagram Reel by @askdbaspprt24bar7 - When developers talk about a Graph API, they are usually referring to one of two things: a specific tool (like the Facebook Graph API) or a general ar
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@askdbaspprt24bar7
When developers talk about a Graph API, they are usually referring to one of two things: a specific tool (like the Facebook Graph API) or a general architectural style for querying data. At its core, a Graph API treats data not as a series of isolated tables, but as a network of interconnected nodes and edges.

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