#Status Codes In Api Testing

HTTP status Codes.

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Follow @cloud_x_berry for more info #HTTPMethods #RESTAPI #BackendDevelopment #WebDevelopment #APIDesign HTTP methods, RESTful APIs, GET request, POST request, PUT request, PATCH request, DELETE request, client server architecture, API endpoints, CRUD operations, status codes 200 201 204, resource creation, data retrieval, resource update, partial update, resource deletion, request response cycle, stateless protocol, web services, backend fundamentals

common API error codes 1️⃣ 400 Bad Request 2️⃣ 401 Unauthorized 3️⃣ 403 Forbidden 4️⃣ 404 Not Found 5️⃣ 405 Method Not Allowed 6️⃣ 429 Too Many Requests 7️⃣ 500 Internal Server Error 8️⃣ 501 Not Implemented 9️⃣ 502 Bad Gateway 🔟 503 Service Unavailable 1️⃣1️⃣ 504 Gateway Timeout These error codes are commonly encountered in web development. Handling them appropriately in your application ensures a smoother user experience and better error resolution.

Follow @mrk_talkstech for more info #HTTPStatusCodes #HTTPErrors #WebDevelopment #APIDebugging #RESTAPI HTTP status codes, 404 not found, 500 internal server error, 400 bad request, 401 unauthorized, 403 forbidden, 502 bad gateway, 503 service unavailable, 504 gateway timeout, 200 OK, 201 created, 204 no content, client errors, server errors, REST API errors, debugging, response codes, HTTP protocol, web errors, API troubleshooting

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1 Million RPS isn't about code, it's about architecture. Here are the 8 key layers to scale your API architecture. 1️⃣ Load Balancer 👉 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 #developer #backenddeveloper #distributedsystems [API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]

“Seeing 404 or 500 errors and getting confused? 😵‍💫 Understand HTTP status codes like a pro 👇 ✅ 2xx → Success 🔁 3xx → Redirection ⚠️ 4xx → Client Errors 💥 5xx → Server Errors Every developer should know this 💻🔥 👇 Which status code do you see the most? 💾 Save this for quick reference 🔁 Share with your developer friends #salamhusain.dev #HTTP #WebDevelopment #Programming #Developers Coding BackendDeveloper TechTips LearnCoding SoftwareEngineer Debugging TechIndia

Your biggest customer just went viral. 10,000 requests hit your API in 3 seconds. Servers slow down. Clients timeout. They retry. More retries. More load. More timeouts. One success story just became everyone's outage. 💀 This is the cascade failure loop — and a basic rate limiter won't save you. Stripe moves billions of dollars. They can't afford "tourist-level" architecture. So they built 4 layers of protection — each independent, each designed to survive even if the others fail. Here's what actually works at scale 👇 Layer 1 — Token bucket. Kills the runaway script before it spreads. Layer 2 — Concurrent limiter. No hoarding resources, even if the rate looks fine. Layer 3 — Fleet shedder. 20% capacity locked for critical ops. Always. Non-critical? Clean 503. Layer 4 — Machine-level triage. Drops test traffic first. Payments survive the fire. The first 3 layers prevent the problem. The 4th limits the damage when it's already happening. That's not rate limiting. That's a promise to every customer that one bad day won't take everyone down. 🔒 Save this if you're building anything at scale. 🔖 . . . . #SystemDesign #BackendEngineering #RateLimiting #SoftwareArchitecture #APIDesign #DistributedSystems #Stripe #TechTwitter #EngineeringLeadership #ScalableArchitecture #SoftwareDevelopment #CodeNewbie #ProgrammingTips #DevCommunity #CloudArchitecture

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In this video, I compare normal async/await, Promise.all, and Promise.allSettled using real API calls. You’ll see how sequential requests increase total time and how Promise.all can drastically speed things up by running tasks in parallel. Also learn when Promise.all fails and why Promise.allSettled is safer. Perfect for JavaScript beginners and intermediate devs! 🚀 #javascript #js #coding #promises #asyncawait #promiseall #promiseallsettled #webdev #nodejs #frontend #backend #codingtips #learnjavascript #programming #codewithme

🚀 API Gateway = Brain of Microservices Without it ❌ Chaos & security risks With it ✅ Control, security & scalability 🔐 Why it matters? • Auth & security • Rate limiting 🚫 • Smart routing • Monitoring & logs ⚡ Example: Like a security guard + traffic controller 🎯 💡 Use it in: Microservices, Banking, E-commerce 🔥 Save for System Design prep. Do Follow @codewith_sushant for more tech tips. #SystemDesign #APIGateway #Microservices #JavaDeveloper #BackendDevelopment SpringBoot ScalableSystems InterviewPrep