#Api Protocols

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#Api Protocols Reel by @cloudwithsingh - 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
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@cloudwithsingh
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 #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]
#Api Protocols Reel by @codingwithmee_18 - Which API Style Should You Choose? 🤔🚀
Har project ke liye same API architecture work nahi karta ❌
👉 REST / GraphQL - Modern apps ke liye best
👉 gR
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@codingwithmee_18
Which API Style Should You Choose? 🤔🚀 Har project ke liye same API architecture work nahi karta ❌ 👉 REST / GraphQL – Modern apps ke liye best 👉 gRPC – High-performance microservices 👉 WebSocket – Real-time apps (chat, trading, gaming) 👉 Webhook – Event-driven updates Sahi API choose karna = Better performance + Scalability + Clean architecture 💻🔥 Save this post 📌 Share with your dev friends 👨‍💻 #API #BackendDevelopment #SystemDesign #GraphQL #RESTAPI gRPC WebSocket Webhook CodingLife FullStackDeveloper TechContent DeveloperIndia CodingWithmee 🚀
#Api Protocols Reel by @iamrajpadval - 1 Million RPS isn't about code, it's about architecture.

Here are the 8 key layers to scale your API architecture.

comment "1MR" to get the complete
10.0K
IA
@iamrajpadval
1 Million RPS isn't about code, it's about architecture. Here are the 8 key layers to scale your API architecture. comment "1MR" to get the complete document in your DM! 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 #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]
#Api Protocols Reel by @sanskriti_malik11 - How do you design an API that survives MILLIONS of requests per second? 🚀

Handling 1M+ RPS isn't about writing faster code.
It's about designing sma
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@sanskriti_malik11
How do you design an API that survives MILLIONS of requests per second? 🚀 Handling 1M+ RPS isn’t about writing faster code. It’s about designing smarter architecture. Here’s what actually keeps systems alive at scale 👇 1️⃣ Traffic Distribution (Load Balancers) Don’t let one server take the hit. Spread traffic across hundreds of instances. 1,000,000 requests ÷ 200 servers = ~5,000 per server. That’s manageable. 2️⃣ Scale Out, Not Up (Horizontal Scaling) Instead of upgrading one giant machine, add more machines. Flash sale spike? Launch 50 more API pods instantly. 3️⃣ Cache Everything You Can Use Redis / Memcached to avoid hitting the database every time. Hot data in memory = microsecond reads. Millions of DB queries saved daily. 4️⃣ CDN at the Edge Static files shouldn’t touch your core servers. Users in Delhi get content from a nearby edge node — not a US data center. 5️⃣ Async Processing (Queues) APIs should respond fast. Heavy work runs in background. Payment confirmed now. Email sent later. Queues = smoother traffic under pressure. 6️⃣ Database Sharding One database will choke. Split data across multiple shards. A–M on one shard, N–Z on another. Parallel writes. Parallel reads. 7️⃣ Rate Limiting Protect your system from abuse. Limit clients to X requests/sec. Block bots before they block you. 8️⃣ Lightweight Payloads Smaller JSON = faster network = lower CPU usage. Send only what’s needed. At massive scale, survival isn’t about code. It’s about architecture decisions. Follow for more real-world system design breakdowns 🔥 #systemdesign #softwaredevelopers #programming #tech #interview [API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availabilityl
#Api Protocols Reel by @code_with_nishan - 🌍 If you think API = only REST… you're thinking too small.
Top developers understand the difference between REST, GraphQL, SOAP, gRPC, and WebSockets
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@code_with_nishan
🌍 If you think API = only REST… you’re thinking too small. Top developers understand the difference between REST, GraphQL, SOAP, gRPC, and WebSockets — and they choose the right one based on performance, scalability, and system design. Knowing API types isn’t optional anymore. It’s what separates junior coders from real engineers. #WebDevelopment #BackendDeveloper #APIDesign #SoftwareEngineering #CodingLife
#Api Protocols Reel by @cloud_x_berry (verified account) - Follow @cloud_x_berry for more info

#APIDesign #RESTfulAPI #BackendEngineering #CleanArchitecture #DeveloperExperience

API design principles, RESTfu
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@cloud_x_berry
Follow @cloud_x_berry for more info #APIDesign #RESTfulAPI #BackendEngineering #CleanArchitecture #DeveloperExperience API design principles, RESTful design, resource naming, HTTP methods, status codes, stateless APIs, request response consistency, versioning strategies, pagination, filtering, sorting, error handling, authentication, authorization, rate limiting, idempotency, backward compatibility, API documentation, OpenAPI specification, developer friendly APIs
#Api Protocols Reel by @mission_compile - 1 Million RPS isn't about code, it's about architecture.
Here are the 8 key layers to scale your API architecture.

Unlock 200+ practical problem-solu
2.2M
MI
@mission_compile
1 Million RPS isn't about code, it's about architecture. Here are the 8 key layers to scale your API architecture. Unlock 200+ practical problem-solutions just like this one in the Ebook. Link in bio 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 #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]
#Api Protocols Reel by @muniker.codes - How do you design a backwards compatible API?🤔

It means making changes in a way that existing clients keep working without any changes on their side
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@muniker.codes
How do you design a backwards compatible API?🤔 It means making changes in a way that existing clients keep working without any changes on their side. ➡️ Treat the API as a contract. Avoid removing or renaming fields ➡️ Make additive changes. Add fields/endpoints instead of changing behavior ➡️ New params should be optional with safe defaults ➡️ Use versioning for breaking changes (v1 → v2) ➡️ Deprecate gradually and monitor usage before removal ➡️ Be tolerant. Clients ignore unknown fields, servers handle missing ones The goal is to evolve the API safely while keeping integrations reliable. #cs #developer #softwareengineer #tech
#Api Protocols Reel by @conceptsofcs - REST is not just GET & POST.

Follow these standards to build scalable, production-ready APIs 🚀
Save this before writing your next backend service.
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@conceptsofcs
REST is not just GET & POST. Follow these standards to build scalable, production-ready APIs 🚀 Save this before writing your next backend service. Follow @conceptsofcs to see more content like this. #java #javadeveloper #javainterview #JavaBackend #springboot
#Api Protocols Reel by @coding_with_pal - 90% of system design beginners call multiple microservices directly.

That's the mistake.

An API Gateway exists so your frontend talks to one door, n
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@coding_with_pal
90% of system design beginners call multiple microservices directly. That’s the mistake. An API Gateway exists so your frontend talks to one door, not 12 services. It handles: • authentication • rate limiting • routing • aggregation Without it → tight coupling, security risk, and chaos. Now you know why every real production system starts with an API Gateway. #systemdesign #microservices #backend #java #softwarearchitecture TechInterview CodingTips faang maang distributed systems lld hld leetcode
#Api Protocols Reel by @_nugget_dev - System Design day 3 🚀🚀

Spinning off with API security 

#technology #development #fyp #coding #software
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@_nugget_dev
System Design day 3 🚀🚀 Spinning off with API security #technology #development #fyp #coding #software
#Api Protocols 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.

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