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@sunitaghimre2: #foryo #foryoupage #nepalitiktok #❤️🥰 @Puspa Dhamala Ojha @Radhika Acharya @{झापालि कान्छि}🌹❣️🥀🕉️ @💞कान्छा कि कान्छि❤️🥀☕️😘 @kunta tiwary @Bimala Kc

Sunita Phuyal Ghimire
Sunita Phuyal Ghimire
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Region: NP
Monday 22 June 2026 04:04:22 GMT
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Comments

puspadhamalaojha
Puspa Dhamala Ojha :
Enjoy♥️♥️
2026-06-22 05:20:45
0
timsina41
Timsina :
ramilo vetghat🙏🙏❤️
2026-06-22 04:15:40
0
savi7113
savi :
aaha kati ramailo full support done xa
2026-06-23 04:50:50
0
sajal_sakchyam
Sajal_Sakchyam Ghimire 🫶❤️🧿 :
❤️❤️
2026-07-05 23:29:38
0
apsharaphuyal3
apsharaphuyal :
❤️❤️❤️
2026-07-01 09:05:24
0
krishnabhandari595
krishnabhandari595 :
❤️❤️❤️
2026-06-29 01:22:34
0
chandabasnet05
Chanda Basnet :
❤️❤️❤️
2026-06-28 18:48:04
0
kapilkopila
kopila mainali :
❤️❤️❤️❤️
2026-06-26 12:59:17
0
kalpanaysubba1
kalpana :
🥰🤩😘
2026-06-26 02:27:58
0
chanda_siwakoti
Chanda kamal siwakoti :
❤️❤️👌👌🙏
2026-06-25 06:47:34
0
gangaojha66
Gangaojha :
🙏🙏🙏
2026-06-25 05:12:28
0
anu.phuyal6
Anu Phuyal :
💚💚💚💚💚
2026-06-24 07:44:25
0
gitaghimire237
Gitaaaaa💗💐 :
❤️❤️❤️❤️❤️
2026-06-23 16:55:22
0
bimalakc21
Bimala Kc :
👌👌👌👌❤️❤️❤️
2026-06-23 02:07:24
0
menukaupreti78
Menuka_Sangroula❤️✨ :
❤️❤️❤️
2026-06-22 15:40:08
0
mayathapaliya6
Maya Thapaliya :
💕💕💕💕
2026-06-22 10:38:35
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sushila.bista8
Sushila Bista :
🥰🥰🥰🥰
2026-06-22 10:15:59
0
kamalapoudel428
kamala poudel :
😘❤️❤️
2026-06-22 08:58:21
0
nirajpokharel88
Niraj Pokharel :
🙏🙏🙏🙏🙏🙏🙏
2026-06-22 08:39:11
0
lalitaphuyal123
💞कान्छा कि कान्छि❤️🥀☕️😘 :
❤️❤️❤️❤️
2026-06-22 08:19:18
0
gomaghimirepokhre
Goma Ghimirepokhrel :
❤️❤️❤️
2026-06-22 08:14:17
0
radhikaacharya_
Radhika Acharya :
❤️❤️❤️❤️❤️
2026-06-22 06:49:10
0
govinda_phuyal5
govinda_phuyal5 :
🥰🥰🥰🥰🥰
2026-06-22 06:41:17
0
lalitaphuyal8
{झापालि कान्छि}🌹❣️🥀🕉️ :
❤️❤️❤️
2026-06-22 04:47:38
0
kamalaghimiradhungana
kamaladhungana00 :
👌👌👌
2026-06-22 04:05:44
0
To see more videos from user @sunitaghimre2, please go to the Tikwm homepage.

Other Videos

When to Shard Database vs Replicate? Database Scaling Explained Most database scaling mistakes come from treating replication and sharding as interchangeable. They solve different problems. I've seen teams throw sharding at a simple read-heavy bottleneck and buy themselves months of operational pain, resharding, cross-shard queries, and hot partitions when two read replicas would have fixed it. And I've seen the opposite: teams stacking replicas onto a write-heavy system and wondering why the primary is still on fire. Every replica has to apply every write, so replication does nothing for write volume. The rule is simple. Don't shard until you've exhausted caching and replication. Replication, one primary pushing copies out to read replicas, is the answer for read-heavy workloads like social feeds, and it gives you a standby when the primary dies. Sharding is for when writes or raw data size physically outgrow one machine. You split the data across independent servers, each owning its own slice. And in mature production systems, it's not either or. You shard first, then replicate each shard. Writes scale across the shards, and every shard survives a machine failure. Match the fix to the actual bottleneck. Most of the time the bottleneck is reads, and most of the time replicas are enough. #SystemDesign #Databases #DevOps #BackendDevelopment #SoftwareArchitecture
When to Shard Database vs Replicate? Database Scaling Explained Most database scaling mistakes come from treating replication and sharding as interchangeable. They solve different problems. I've seen teams throw sharding at a simple read-heavy bottleneck and buy themselves months of operational pain, resharding, cross-shard queries, and hot partitions when two read replicas would have fixed it. And I've seen the opposite: teams stacking replicas onto a write-heavy system and wondering why the primary is still on fire. Every replica has to apply every write, so replication does nothing for write volume. The rule is simple. Don't shard until you've exhausted caching and replication. Replication, one primary pushing copies out to read replicas, is the answer for read-heavy workloads like social feeds, and it gives you a standby when the primary dies. Sharding is for when writes or raw data size physically outgrow one machine. You split the data across independent servers, each owning its own slice. And in mature production systems, it's not either or. You shard first, then replicate each shard. Writes scale across the shards, and every shard survives a machine failure. Match the fix to the actual bottleneck. Most of the time the bottleneck is reads, and most of the time replicas are enough. #SystemDesign #Databases #DevOps #BackendDevelopment #SoftwareArchitecture


Lưới che nắng xanh lá, màu sắc sáng sủa, thích hợp che mái hiên, sân vườn, có rất nhiều kích thước để lựa chọn #luoichesanvuon #luoichenang #luoichenangxanhla #luoichenangvuonlan
Lưới che nắng xanh lá, màu sắc sáng sủa, thích hợp che mái hiên, sân vườn, có rất nhiều kích thước để lựa chọn #luoichesanvuon #luoichenang #luoichenangxanhla #luoichenangvuonlan
نام سن کر اس کا ابھی بھی بے چجن ہوتے ہو .......................... . . . . . . . . . . . . . . #fyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyppppp#unfreezemyacount #sujjestionpromotion #jimingirl #btsarmyforever
نام سن کر اس کا ابھی بھی بے چجن ہوتے ہو .......................... . . . . . . . . . . . . . . #fyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyppppp#unfreezemyacount #sujjestionpromotion #jimingirl #btsarmyforever
#طالت_الغيبة_ماشفت_عينك 🙈💔
#طالت_الغيبة_ماشفت_عينك 🙈💔
#сериалпес #подпишись #recommendation #рекомендации #пёс
#сериалпес #подпишись #recommendation #рекомендации #пёс

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