@user1131556134938:

ام عسولة💋

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Tuesday 11 August 2026 20:40:45 GMT

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Engineer 🔥🇮🇶 :

كتابة

2026-08-12 01:57:44

1

فاطمه :

وانه ضاله بضيم

2026-08-12 01:27:32

1

نودي :

افف

2026-08-12 01:49:09

1

مرتضى الكربلائي :

🤣🤣🤣 والله انشهرنه🤣🤣🤣عمي عيب 🤣🤣🤣

2026-08-11 22:13:33

1

العسكري :

بل عافيه

2026-08-11 21:34:25

1

مصطفى العامري :

ضيم

2026-08-11 20:46:18

1

هبه قويه :

اشتهيت عل صوت

2026-08-11 21:41:39

12

⚔️كرار الكناني ⚔️ :

نعزي انفسنا بوفاة الغيرة والشرف والقيم والاخلاق والإنسانية كل الشكر والتقدير للذي يخاف الله في هذا الزمان

2026-08-11 22:01:53

2

نرجسـ🎀 :

ويلي اريد

2026-08-12 01:48:23

0

اميرالحب حسان العراقي🌹 :

موشي الشغل

2026-08-12 00:56:29

0

👑الملكي 👑 :

😂😂😂

2026-08-11 21:08:36

1

الملكي :

😁😁😁😁

2026-08-11 21:39:45

1

Mm😍 :

@لوجين م تردي يبنتي

2026-08-11 23:22:37

0

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عيوب و مميزات Cupra Leon ! #egyptcars #carsoftiktok #cupra

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What year was the best for Halloween?👻 #halloween #1990s #nostalgia #vintage #autumn

Message queues: how one append-only log moves a trillion messages a day without ever blocking the producer. A producer writes messages to a log. A consumer reads them at its own pace. That one design decision is why systems like Kafka survive traffic spikes that would crush a normal request/response API. Watch what happens when the consumer crashes: the producer keeps writing, completely unbothered. The messages don't vanish, they wait in the log, in order. When the consumer recovers, it rips through the backlog and catches up. Zero messages lost. And because it's an append-only log with offsets, the consumer can seek backward and re-read old messages from any point. A delete-on-ack queue (RabbitMQ, SQS) can't do that. once a message is acked, it's gone. This is the backbone of every event-driven system: producer never waits, consumer reads on its own clock, the log remembers everything. Save this for the next time someone asks

Message queues: how one append-only log moves a trillion messages a day without ever blocking the producer. A producer writes messages to a log. A consumer reads them at its own pace. That one design decision is why systems like Kafka survive traffic spikes that would crush a normal request/response API. Watch what happens when the consumer crashes: the producer keeps writing, completely unbothered. The messages don't vanish, they wait in the log, in order. When the consumer recovers, it rips through the backlog and catches up. Zero messages lost. And because it's an append-only log with offsets, the consumer can seek backward and re-read old messages from any point. A delete-on-ack queue (RabbitMQ, SQS) can't do that. once a message is acked, it's gone. This is the backbone of every event-driven system: producer never waits, consumer reads on its own clock, the log remembers everything. Save this for the next time someone asks "why not just call the API directly?" 👇 What are you using. Kafka, SQS, RabbitMQ? Follow @krishnachaytanyaa for backend systems explained visually. #trending #kafka #vibecoding #systemdesign #ai

califica este edit 1/10? #football #defensas #araujo🇺🇾 #saliba #vandijk

califica este edit 1/10? #football #defensas #araujo🇺🇾 #saliba #vandijk

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