CAP Theorem - Partition is a verb

People who’ve spent some time around databases usually have an intuitive sense of ACID, even if the acronym slips their mind. And if you work with distributed systems, you usually have a rough idea of the CAP Theorem, even if the details are fuzzy. The first thing you remember about CAP is probably, “Pick two out of three.” And maybe you can even remember the letters without a search engine …

Monique Mudama

The CAP theorem, proven by MIT's Gilbert and Lynch in 2002, states a distributed data store can guarantee only two of three properties: consistency, availability, and partition tolerance.

#CAPTheorem #DistributedSystems #CloudComputing

The CAP theorem, proven by Gilbert and Lynch of MIT in 2002, states that a distributed data store can simultaneously provide at most two of three guarantees: Consistency, Availability, and Partition Tolerance.

#CAPTheorem #DistributedSystems

LOL: "Eight Sleep adds ‘outage mode’ to smart beds after AWS problems left them frozen". They did not learn.

#fallaciesofdistributedcomputing
#offlinefirst
#captheorem

https://www.reddit.com/r/technology/comments/1oddh8v/eight_sleep_adds_outage_mode_to_smart_beds_after/

I'm surprised that NextCloud can run on something as small as a Raspberry Pi and also scale to enterprise-level distributed global servers, dealing with CAP theorem challenges at the same time.

An example of a global provider with lots of servers around the globe:
>> "Nextcloud Global Scale: local data and limitless scalability at commodity cost"

https://nextcloud.com/blog/nextcloud-global-scale-how-it-works/

#nextcloud #nextcloud25 #nextcloudglobalscale #officesuite #captheorem #enterprise

Nextcloud Global Scale: local data and limitless scalability at commodity cost - Nextcloud

Scaling file sync and share architectures from thousands to tens of thousands all the way to millions of users with Nextcloud Global Scale.

Nextcloud
Distributed Systems Design: Patterns and Practices

In today’s world of massive-scale applications and services, distributed systems have become the backbone of modern computing. They enable applications to handle vast amounts of data, remain resilient in the face of failures, and deliver high performance across the globe. However, designing these systems is not a trivial task. It involves understanding complex principles and implementing robust patterns to ensure they meet the desired specifications. In this blog post, we’ll dive deeper into the core principles and patterns of distributed system design, covering consistency models, the CAP theorem, fault tolerance, and essential patterns like Saga, Circuit Breaker, and Bulkhead.

Kubernetes is vulnerable to stale reads, violating critical pod safety guarantees · Issue #59848 · kubernetes/kubernetes

When we added resourceVersion=0 to reflectors, we didn't properly reason about its impact on nodes. Its current behavior can cause two nodes to run a pod with the same name at the same time when us...

GitHub
Heute für die Vorlesung morgen mit #etcd gespielt 🤓 #CAPTheorem hands on 😀
Keeping CALM: when distributed consistency is easy | the morning paper

@marcel
Gerade heute in der #Cloud-Vorlesung das Thema #captheorem kurz angeschnitten:
Studi: "Aber eine #Blockchain erfüllt ja #CAP auf einmal?"
Dieser Hype ist immer noch "da" und wird durch #web3, #smartcontracts, #nfts, etc. nur weiter gepusht: Es muss als Allheilmittel herhalten, eben weil sich konkrete Usecases als unpraktikabel herausgestellt haben.