ViewTube

My first build with Swamp Club. Nick Stinemates joins me on Rawkode Live to take me from zero to building something real.

Lecture 5 of Designing Data-Intensive Applications, Explained in Java · Part 1: Trade-Offs in Data Systems Architecture.

Become AI-native Senior Engineer - https://learn.theseniordev.com/free-training?utm_content=10_26_system_design_linkedIn ...

Picture a small bakery's website. It loads like any other page, but it arrives with a hidden label: a certificate that proves the page ...

Distributed Systems Explained: Consistency, CAP, Quorums, Raft and Two-Phase Commit · System Design ...

ACID guarantees stop at the single database boundary . When business workflows cross multiple microservices or databases, ...

For this episode, we rent four RTX 4090s on Vast.ai and pretrain a model about six times bigger than our laptop's, in GPT-2 small's ...

Discover how distributed key-value stores like DynamoDB and Cassandra scale to millions of requests per second. We break ...

Too long? Great overview/summarization: https://gist.github.com/lalyos/05fbb62dc9f0487727ab64e4fda7835f Originally ...

In this video, we explain the question: What is Distributed Computing? Explain its advantages, challenges, and real-world ...

How do vector databases make similarity search fast? We build from embeddings and nearest-neighbor search to HNSW, filters, ...

Master 45 advanced English terms for cloud computing, software architecture, backend engineering, distributed databases, ...

Distributed Computing: Why vertical scaling hits a physical limit and how horizontal sharding solves big data bottlenecks .

Learn how to design a distributed email platform capable of handling 1 billion users, 50 billion messages a day, and petabytes of ...

Understand publish-subscribe systems and one-to-many event delivery. Learn topic routing, subscriptions and filtering, push ...

John Furrier of theCUBE Research speaks with Jeff Wang, president of New Enterprise at Cognition, for theCUBE + NYSE Wired: ...

How much performance do you actually give up when you split an application into microservices? I built the same Go app as a ...

Lecture 68 of Designing Data-Intensive Applications, Explained in Java · Part 8: Transactions. In this lecture • Distributed ...

Learn how to design a distributed cache by mastering consistent hashing, eviction policies, and core replication tradeoffs.

How do you trace a request across multiple microservices and identify performance bottlenecks in a real-world DevOps ...