@moussahassansimon1: #اهلابشهرالمولد #الحمدالله_علی_کل_حال❤ #اللهم_صل_وسلم_على_نبينا_محمد #الحمدلله_دائماً_وابداً❤️

MOUSSA HASSAN SIMON موسى حسن
MOUSSA HASSAN SIMON موسى حسن
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Wednesday 02 September 2026 16:47:56 GMT
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bakit ahmat🇷🇴🇷🇴🇷🇴🇷🇴 :
@ماشااللة
2026-09-25 14:03:44
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user3450209090659
المادح سيف الدين ابراهيم :
ماشاءالله صلي الله عليه وسلم
2026-09-03 13:23:17
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user202095059401
إدريس اسحاق :
صلى الله عليه وسلم
2026-10-18 10:40:10
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user9658457361132
ابراهيم :
ماشاء
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user6195977253696
عيس محمد515 :
الله الله الله الله الله
2026-09-05 09:55:04
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abdl.212_
Abdl :
صلي الله عليه وسلم
2026-09-02 19:34:17
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user80028155941224
عبدالرازق أدم محمد. بری :
ما
2026-09-10 22:09:14
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user1416299357394
عـــلي محمد :
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2026-10-01 18:49:21
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moussa arabi :
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قننل 🖤وادي :
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atteib_hadaf333 :
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السيد كرا الصحراو :
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ادم عبدالله ابراهيم :
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ءادم السليك بحر مصطفى 🌺 :
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2026-09-06 17:58:12
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Mahamat zen Adammahamat :
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ماكن حسن :
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SAFIYOU NOUFFOU :
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محمد علي أبكر يحي :
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Mohammed Ali :
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2026-09-02 16:52:58
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Other Videos

🚨 Full Database Sharding Course on Udemy: https://kode.wiki/4B9vHwD Database sharding explained from scratch, using one growing app to show exactly when a single database stops scaling and what replaces it. Chirp starts on one server and one database. Then it hits millions of users, the biggest machine the cloud will rent isn’t enough, and writes start failing during busy moments. Replicas rescue the slow reads but can’t touch the write problem. This course follows Chirp through every fix, so shard keys, hashing, hotspots and consistent hashing each show up right when the app needs them. 🧪 Try it yourself in the free lab: https://kode.wiki/4eARqUp 📚 What you’ll learn: 1️⃣ Why read replicas speed up reads but can’t help once writes start failing 2️⃣ The five checks a shard key has to pass, and why user ID beats country, signup year and username 3️⃣ How hashing turns an email into a shard number, and why Python’s built-in hash() breaks sharding 4️⃣ How to stop a celebrity hotspot with a dedicated shard, a cache and salted keys 5️⃣ Why adding one shard can move 80% of your data, and how consistent hashing with virtual nodes prevents it 🧪 Free hands-on lab: https://kode.wiki/4eARqUp ⏰ Timestamps: 00:00 - Intro 00:40 - Chirp: one app, one database 02:30 - Reads, writes and scaling up 04:00 - Read replicas 06:00 - Why writes can’t go to replicas 08:00 - What sharding actually is 09:30 - Splitting users across four shards 11:00 - Lab 1: Shard a 10,000-row users table 11:30 - What a shard key is 13:00 - Five properties of a good shard key 19:30 - Hashing non-numeric shard keys 22:00 - Why Python’s hash() fails for sharding 25:00 - Range, directory and geographic sharding 29:30 - Lab 2: Test different shard keys 30:00 - The routing layer: app, proxy or database 34:00 - Hotspots and the celebrity problem 37:30 - Salting hot keys 41:00 - Why adding one shard moves most of your data 43:30 - Consistent hashing and the hash ring 46:30 - Virtual nodes 🗄️ System Design Playlist: https://www.youtube.com/playlist?list=PLPOrzEadD7Ew 🔔 Subscribe for more database and system design lessons built around real apps #DatabaseSharding #SystemDesign #KodeKloud #ConsistentHashing #Sharding #DatabaseScaling #HorizontalScaling #ShardKey #DistributedSystems #DatabaseReplication #Hashing #MongoDB #BackendEngineering #SystemDesignInterview #Scalability #DevOps
🚨 Full Database Sharding Course on Udemy: https://kode.wiki/4B9vHwD Database sharding explained from scratch, using one growing app to show exactly when a single database stops scaling and what replaces it. Chirp starts on one server and one database. Then it hits millions of users, the biggest machine the cloud will rent isn’t enough, and writes start failing during busy moments. Replicas rescue the slow reads but can’t touch the write problem. This course follows Chirp through every fix, so shard keys, hashing, hotspots and consistent hashing each show up right when the app needs them. 🧪 Try it yourself in the free lab: https://kode.wiki/4eARqUp 📚 What you’ll learn: 1️⃣ Why read replicas speed up reads but can’t help once writes start failing 2️⃣ The five checks a shard key has to pass, and why user ID beats country, signup year and username 3️⃣ How hashing turns an email into a shard number, and why Python’s built-in hash() breaks sharding 4️⃣ How to stop a celebrity hotspot with a dedicated shard, a cache and salted keys 5️⃣ Why adding one shard can move 80% of your data, and how consistent hashing with virtual nodes prevents it 🧪 Free hands-on lab: https://kode.wiki/4eARqUp ⏰ Timestamps: 00:00 - Intro 00:40 - Chirp: one app, one database 02:30 - Reads, writes and scaling up 04:00 - Read replicas 06:00 - Why writes can’t go to replicas 08:00 - What sharding actually is 09:30 - Splitting users across four shards 11:00 - Lab 1: Shard a 10,000-row users table 11:30 - What a shard key is 13:00 - Five properties of a good shard key 19:30 - Hashing non-numeric shard keys 22:00 - Why Python’s hash() fails for sharding 25:00 - Range, directory and geographic sharding 29:30 - Lab 2: Test different shard keys 30:00 - The routing layer: app, proxy or database 34:00 - Hotspots and the celebrity problem 37:30 - Salting hot keys 41:00 - Why adding one shard moves most of your data 43:30 - Consistent hashing and the hash ring 46:30 - Virtual nodes 🗄️ System Design Playlist: https://www.youtube.com/playlist?list=PLPOrzEadD7Ew 🔔 Subscribe for more database and system design lessons built around real apps #DatabaseSharding #SystemDesign #KodeKloud #ConsistentHashing #Sharding #DatabaseScaling #HorizontalScaling #ShardKey #DistributedSystems #DatabaseReplication #Hashing #MongoDB #BackendEngineering #SystemDesignInterview #Scalability #DevOps

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