|
You are here |
eli.thegreenplace.net | ||
| | | | |
timilearning.com
|
|
| | | | | One common pattern in the previous systems we have discussed like MapReduce, GFS, and VMware FT is that they all rely on a single entity to make the key decisions. While this has the advantage of making it easier for the system to decide, the downside of this approach is that the entity is now a single point of failure. In this post, we'll learn how the Raft consensus algorithm solves this problem. | |
| | | | |
www.mattritter.me
|
|
| | | | | Background Lately I've been studying consensus algorithms to bolster my understanding of distributed systems. Consensus algorithms achieve agreement on data that is replicated across many nod... | |
| | | | |
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. | |
| | | | |
blog.donorschoose.org
|
|
| | | Tips, tools, and resources for educational leaders looking to lead classrooms and organizations. | ||