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๐Ÿ—„๏ธ Database Sharding

Horizontal Scaling, Partition Strategies, Distributed Databases

What sort of success?
seths.blogยท3h
๐Ÿ‘๏ธObservability
The end of easy PPC attribution โ€“ and what to do next
searchengineland.comยท1d
๐Ÿค–Machine Learning
Biwin has announced a teeny-tiny new type of SSD with shock and water resistance built-in, but it might be a while before you see one in your next mobile device
pcgamer.comยท1d
โšกZero-Copy
OpenAI's o3 model outperforms the newer GPT-5 model on complex, multi-app office tasks
the-decoder.comยท1d
๐ŸŒWebAssembly
Mawari Partners With Caldera To Launch Mawari Network For The Streaming Of AI-Powered Experiences
hackernoon.comยท1d
๐ŸŒEdge Computing
Taming the Beast: Comparing Jsonnet, Dhall, Cue
pv.wtfยท3dยท
Discuss: Lobsters, Hacker News
๐ŸŒWebAssembly
When cloud growth outpaces control, waste follows
techradar.comยท2d
๐Ÿ”—Distributed Systems
Family Alignment Problems
lesswrong.comยท3h
โ™ŸChess Programming
This might be the most important AI paper of the year.
threadreaderapp.comยท1d
๐Ÿค–Machine Learning
CoreWeave Crashes 46% After Lockup--Is This the AI Bargain of the Year or a Falling Knife?
finance.yahoo.comยท15h
๐ŸŒWebAssembly
๐Ÿง  Building Intelligent Kafka Health Probes in Go
dev.toยท1dยท
Discuss: DEV
๐Ÿ”—Distributed Systems
Need help managing my database on bubble io
reddit.comยท2dยท
Discuss: r/webdev
๐Ÿ”„Tokio
BaseDMS - An open-source, intelligent, AI-powered data management system based on browser
dev.toยท2dยท
Discuss: DEV
๐Ÿ“กgRPC
Stop Playing Feature Catch-Up: A Smarter Way to Beat Competitors
dev.toยท1hยท
Discuss: DEV
๐Ÿ”„Tokio
My First Encounter with Zabbix (Or should I sayโ€ฆ โ€œJepixโ€?)
dev.toยท9hยท
Discuss: DEV
๐ŸŒWebAssembly
Web Developer Travis McCracken on Using Go for Cloud Functions
dev.toยท40mยท
Discuss: DEV
๐Ÿ”„Tokio
5+ Best AI Content Marketing Tools, Autonomous and Less Autonomous
dev.toยท4hยท
Discuss: DEV
๐ŸŒWebAssembly
Dynamic Ride-Pooling Optimization via Adaptive Bayesian Network for Urban On-Demand Transit
dev.toยท13hยท
Discuss: DEV
๐Ÿค–Machine Learning
GraphQL Crash Course: The New Legacy System.
dev.toยท3dยท
Discuss: DEV
๐Ÿ“กgRPC
Long-Term Client Selection for Federated Learning with Non-IID Data: A Truthful Auction Approach
arxiv.orgยท3d
๐Ÿค–Machine Learning
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