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𝖲𝗂𝖽𝖾𝖾🦢
𝖲𝗂𝖽𝖾𝖾🦢
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Monday 02 November 2026 15:05:44 GMT
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sarkrda47m4d2
? :
Zhna zamana💔
2026-11-02 18:40:19
37
dno_b2
✰𝗗𝗻𝗼𝟳𝟳✰ :
كاته بينم🙂
2026-11-02 16:05:12
25
judy_spindare24
𝗝 𝗨̂ 𝗗 𝗬̈ 𝟮𝟰 :
Shkle we : 🙂
2026-11-02 18:01:00
8
m3archh_077
٧٧𖦹حـــــــه مـــــــــو𖦹 :
wayyy
2026-11-03 06:25:21
3
ali_zakhoiy
𝒯𝓎𝓅𝒾𝓃ℊ🩸 :
Ava am 😂
2026-11-02 18:07:52
6
nojeeen.01
♯̶̶1̶̶7̶🌊~ :
sidoyea mn
2026-11-02 15:18:33
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mz1ri.4
` :
As lawm🤙🏾
2026-11-02 18:24:49
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redoo260
REDØØ :
😂❤️‍🔥
2026-11-02 18:06:57
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spindary67
Alan barwari💫👑 :
2026-11-03 10:17:48
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ezge079
یــــزگێـــے.770🧛🏾‍♀️ :
2026-11-02 16:08:48
5
rojoo096
z4re💛 :
Hiç
2026-11-02 18:44:25
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barwari.372
꧁༒YOUSKO³³༒꧂ :
پاش من گوت جورجينايه
2026-11-02 19:32:05
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ar_zebari
ib4_m :
🔥
2026-11-02 15:10:23
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niko_diamond90
Niko😜 :
😍
2026-11-02 15:33:58
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System design has many terms that sound similar… …but they solve very different problems. Here’s the simplest breakdown worth saving: LATENCY How long does one request take? THROUGHPUT How many requests can the system process over time? BANDWIDTH How much data can move through the network at once? — REPLICATION Copies the same data across multiple machines. SHARDING Splits different parts of the data across multiple machines. — POLLING Keeps asking: “Has anything changed?” WEBHOOK Automatically sends a notification when something happens. — PROCESS An independent program with its own memory. THREAD A smaller execution unit that shares memory within a process. — LOAD BALANCER Distributes traffic across multiple servers. API GATEWAY Controls how clients access APIs. — CONCURRENCY Handles multiple tasks during the same period. PARALLELISM Executes multiple tasks at exactly the same time. — MONOLITH Built and deployed as one complete application. MICROSERVICES Split into smaller services that can be developed and deployed independently. Small differences. Big impact when designing production systems. Save this for your system design and AI engineering interviews. . . . [AI Engineering, AI Engineer, System Design, Backend Engineering, Software Engineering, Machine Learning Engineering, MLOps, LLMOps, Production AI, Latency, Throughput, Bandwidth, Replication, Sharding, Polling, Webhook, Process, Thread, Load Balancer, API Gateway, Concurrency, Parallelism, Monolith, Microservices, Distributed Systems, Scalability, High Availability, API Design, Cloud Engineering, DevOps, Technical Interviews] #softwaredeveloper #llm #ai #machinelearning #datascience
System design has many terms that sound similar… …but they solve very different problems. Here’s the simplest breakdown worth saving: LATENCY How long does one request take? THROUGHPUT How many requests can the system process over time? BANDWIDTH How much data can move through the network at once? — REPLICATION Copies the same data across multiple machines. SHARDING Splits different parts of the data across multiple machines. — POLLING Keeps asking: “Has anything changed?” WEBHOOK Automatically sends a notification when something happens. — PROCESS An independent program with its own memory. THREAD A smaller execution unit that shares memory within a process. — LOAD BALANCER Distributes traffic across multiple servers. API GATEWAY Controls how clients access APIs. — CONCURRENCY Handles multiple tasks during the same period. PARALLELISM Executes multiple tasks at exactly the same time. — MONOLITH Built and deployed as one complete application. MICROSERVICES Split into smaller services that can be developed and deployed independently. Small differences. Big impact when designing production systems. Save this for your system design and AI engineering interviews. . . . [AI Engineering, AI Engineer, System Design, Backend Engineering, Software Engineering, Machine Learning Engineering, MLOps, LLMOps, Production AI, Latency, Throughput, Bandwidth, Replication, Sharding, Polling, Webhook, Process, Thread, Load Balancer, API Gateway, Concurrency, Parallelism, Monolith, Microservices, Distributed Systems, Scalability, High Availability, API Design, Cloud Engineering, DevOps, Technical Interviews] #softwaredeveloper #llm #ai #machinelearning #datascience

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