Explore >> Select a destination
|
You are here 
|
paulkernfeld.com | ||
| | | | |
blog.thislongrun.com
|
|
| | | | | Introduces the CAP theorem series, going into the definition of consistency, availability and partitions, and the meaning of AP/CP/CA categories of the CAP theorem. | |
| | | | |
scorpil.com
|
|
| | | | | How the CAP theorem explains trade-offs in software engineering organizations between quality, velocity, and communication. | |
| | | | |
tomaugspurger.net
|
|
| | | | | Last week, I was fortunate to attend Dave Beazley's Rafting Trip course. The pretext of the course is to implement the Raft Consensus Algorithm. I'll post more about Raft, and the journey of implementing, it later. But in brief, Raft is an algorithm that lets a cluster of machines work together to reliably do something. If you had a service that needed to stay up (and stay consistent), even if some of the machines in the cluster went down, then you might want to use Raft. | |
| | | | |
preethikasireddy.com
|
|
| | | Distributed systems can be difficult to understand, mainly because the knowledge surrounding them is distributed. But don't worry, I'm well aware of the irony. While teaching myself distributed computing, I fell flat on my face many times. Now, after many trials and tribulations... | ||
