CAP Theorem CAP Theorem talks about tradoffs of disturbed systems Here C - Consistency (Every read request to the distributed system should return same result irrespective of whichever node we are reading from) A - Availability (The system should respond to any request made to it irrespective of any node is failed or not) P - Partition Tolerance (The system continues to respond/operate even though there is a network breakdown/partition between the nodes) Before Diving into CAP theorem here is some background knowledge you should know Distributed System : Data Stored in multiple servers instead of one(like we do when we apply horizontal scaling) Why distributed systems? > Spread Workload among multiple servers > Can handle more number of requesss > Improves overall performance In distributed system we replicate same data across multiple systems to get the above benifits. Server/s are called a node here. Now let's talk about the CAP Let's say there are there nodes X, Y and Z Consistency says that whenever you read data from X, Y or Z they should return the same data and when you write then it should be propogated to other nodes to maintain consistency Availability says that if B fails due to some hardware issue and go offline then A and C should still be working and should serve the requests Partition Tolerance says if network partition happens on B and it can't communicate with A and C, then node B will still be serving requests even though it is not up to date with the data with other nodes(A and C) since it got a network partition. CAP Theorem: CAP Theorem states that in a distributed system, you can only guarantee two out of these three properties simultaneously. It's impossible to achieve all three You can refer to the image below for clear understand about the statement once Only the combination of CA(Consistency-Availability), AP(Availability-Partition tolerance), CP(Consistency-Partition tolerance) is possible In distributed system there are very high chances of network partition so we should must handle P(partition tolerance). So most of distributed systems choose either AP or CP because they can't afford network partition What to choose between CP and AP CP - if you can't afford inconsistent data then go for CP like banking, payment services where numbers are the most important thing AP - if you can afford in consistent data but can't afford unavailability like social media can have slightly different likes, comments or views for different users but it can't have their apps down.

Launching Billy. Creating an invoice shouldn’t feel like filling out paperwork. Most tools made it slower and more complicated than it needed to be. So I built Billy, an in-browser invoice generator where you edit directly on the template, like editing a doc. No forms. No extra steps. Built for everyone. But if you're a freelancer, indie hacker, or running a small business, this could genuinely change how fast you create and manage invoices. Working on things like: - Local-first workflows - Templates - Cloud sync - Exports - And more Currently in waitlist mode, building otw.

kitna bura jaa rha hai yaar mera 2026 🙁🙁

how tf am I supposed to consolidate someone apart from saying it happens lmao

atp it's about minimizing things I don't know that I don't know ig

Tf is this ui of prajaakeeya

lost.

Mera khel khatam hai 🥀🥀

Seeing so many people's last btech last exam on my tl is kinda making me sad that I'll be posting the same by a year.

Claude khatam, Codex khatam aur ab open code ki baari 😈😈😈

Anyone going for scaler hack at blr tomo(technically today)?

Any place to find go devops projects/project ideas?

OMFG how tf am I able to procrastinate this much

Fuck it, I ain't sleeping tonight

🎬 Gully Boy (2018)

Thumbnail: use claude code for free Video: download gemini cli

next 9pm ke baad

Locking in till 7pm

coding solve ho gayi AI se ab sab app banayenge, abey coding toh pehle bhi solved thi gavar podcastiye

wrote up the blog after so many procrastination spent 2 days like a zombie to write up this which no one’s gonna read prolly but we ball anyways 😭 writing up gave me more pain than building it lmao😭 anyways here’s the link -> akanshatwt.me/blogs/kafka-pa… and with this im gonna take a good nap ;)

again fumbled in a hackathon presentation 🤓☝️