samuel Ramdas

[Keith D @inneroperator]

The third largest bank in the world just revealed that Chainlink’s CCIP is the future of finance. But what does that really mean?

[samuel Ramdas @samdasoxide]

@jamescoder12 Resume

[TheRealMvitaOne @FauzKhalid]

Ugandan Minister Balaam says the internet is off in Uganda because a ship vandalised the fibre optic cable in Mombasa

[samuel Ramdas @samdasoxide]

@beginnersblog1 Guide

[samuel Ramdas @samdasoxide]

@atikcoder0 Agent

[ℏεsam @Hesamation]

this is still the best guide on Claude Code I've seen that covers basically how you should (and shouldn't) use it. comprehensive, practical, and to-the-point.

https://t.co/1P847kkROo

[Boris Cherny @bcherny]

I'm Boris and I created Claude Code. Lots of people have asked how I use Claude Code, so I wanted to show off my setup a bit.

My setup might be surprisingly vanilla! Claude Code works great out of the box, so I personally don't customize it much. There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it, and hack it however you like. Each person on the Claude Code team uses it very differently.

So, here goes.

[Nelly; @nrqa__]

How to use AI to learn anything faster;

[Elon Musk @elonmusk]

https://t.co/XjTHCNw7B5

[Neo Kim @systemdesignone]

Here are some white papers you must read as a senior engineer:

[gaut @0xgaut]

The most productive setup is 9 here.

Change my mind.

[INTERIOR PORN @INTERIORPORN1]

loft apartment of my dreams

[INTERIOR PORN @INTERIORPORN1]

I could stare at this view all day

[ShyTay @shyxtaylax]

Simple Outfit

[Milan Jovanović @mjovanovictech]

Data structures are hard!

Using the right data structure makes a world of difference.

Take a trivial exercise like detecting if a collection contains duplicates.

I'm sure you can come up with a few ways to find the solution.

A brute force solution would be comparing each element to the remaining elements in the list. This takes O(N^2) time complexity.

But what's the most efficient data structure for a job like this?

The humble HashSet in C# stores only unique values.

You can go through the collection while adding elements to the HashSet.

You've found the solution as soon as you run into a duplicate.

This takes O(N) time complexity and costs a bit of memory.

P.S. If you liked this, consider joining The .NET Weekly - my newsletter with 41,000+ engineers that teaches you how to improve at .NET and software architecture.

Subscribe here → https://t.co/zVBFd2uo25

What's your favorite data structure?

[Massimo @Rainmaker1973]

How a book written in 1910 could teach you calculus better than several books of today

[Calculus Made Easy, by Silvanus P. Thompson, 1910: https://t.co/HJDxFqZNJf]

[Sahn Lam @sahnlam]

Key Concepts to Understand Database Sharding

Database sharding refers to splitting data across multiple database servers and is commonly used for scaling. However, sharding introduces major operational and infrastructure complexity that should be avoided unless absolutely necessary.

Approaches to postpone sharding

Vertical Scaling: Use more powerful single database servers - more CPUs, memory, storage and I/O bandwidth. Much simpler to manage than sharding while allowing sizable expansion.

SQL Optimization: Tune SQL queries and database schema to maximize performance on a single server. Requires proper indexes, efficient SQL, etc.

Caching: Use in-memory caches like Redis to reduce database load by avoiding hitting it for every common query.

Read Replicas + Load Balancer: Adds horizontal read scaleability without full complexity of sharding. Directs reads across replicas.

These optimization approaches should be exhausted before sharding given the complexity.

Horizontal vs Vertical Sharding

There are two high-level approaches:

Vertical Sharding: Split database into columnar tables or sections vs rows. For example, having one table for names and another table for emails.

Horizontal Sharding: Split database into row partitions distributed evenly across multiple servers.

Some horizontal sharding methods:

1. Range Based: Segment rows based on range values like age groups. Can cause uneven data distribution and hot spots.

2. Directory Based: Use a lookup directory to locate rows. Allows flexibility but single point of failure risk.

3. Hash Based: Apply hash functions to spread rows uniformly across shards. Harder to rebalance.

When sharding, use the simplest approach that meets requirements to minimize complexity. Seek to avoid until necessary.

–
Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://t.co/kNfv0DVDdf

[kamran Hassan @Rana_kamran43]

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Post viral videos on YouTube

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[Tushar Rajpoot @tush_tr604]

7 awesome Github repos for DevOps👇

1. binhnguyennus/awesome-scalability
2. joseadanof/awesome-cloudnative-trainings
3. bregman-arie/devops-exercises
4. omerbsezer/Fast-Kubernetes
5. dastergon/awesome-sre
6. devsecops/awesome-devsecops
7. HariSekhon/DevOps-Bash-tools