5 posts tagged with "distributed-systems"

Let’s restate the subset of rules that are relevant to this section:

1. Durability: Every decision is a distributed decision.
   1. A distributed decision must be made durable.
   2. A decision that has been made durable can be applied.

As we solve the problem of durability, we will realize that there is a simple set of governing rules that we will be applying repetitively. We will develop these as we progress in our design. However, we will share their entirety upfront.

If you followed these rules, you should actually be able to implement any kind of consensus system. Here are some definitions and rules:

In our previous post, we came up with an informal definition :

A consensus system must ensure that every request is saved elsewhere before it is completed and acknowledged. If there is a failure after the acknowledgment, the system must have the ability to find the saved requests, complete them, and resume operations from that point.

Let us stick to this definition and expand on some of these rules.

In this blog series, I have the following goals:

• Propose an alternate and more approachable definition of consensus.
• Expand the definition into concrete requirements.
• Break the problem down into goal-oriented rules.
• Provide algorithms and approaches to satisfy the rules with adequate explanations to prove correctness and safety.
• Show that existing algorithms are special cases of this generalization.

Today, we're releasing a series that presents a fresh perspective on consensus algorithms. Rather than treating consensus as a monolithic black box, we propose a conceptual framework that makes these systems more approachable, adaptable, and flexible.