jthan24

@ghumare64 Linux!

How does Linux work from the basics? I know, we've done various revisions previously on this in my tweets, but this page is a collection of everything. Comment with "Linux" and get this resource. Also, RETWEET for my DM to get early access.

Top 5 Comics for DevOps Engineers! I bet you don't know them. 1. Github PR - bit.ly/hare-comic 2. comic agile - comicagile.net/comic/the-devo… 3. Sebiwi - sebiwi.github.io/comics/we-devo… 4. turnoff - turnoff.us/geek/before-de… 5. CNCF - cncf.io/phippy/the-chi… Bookmark this for later 🔖

Top 5 DevOps Learning Websites: 1️⃣ MIT OpenCourseWare - Offers free DevOps-related materials, like system administration and cloud computing lectures. Link: ocw.mit.edu 2️⃣ edX - Free DevOps courses (audit mode) from universities like Linux Foundation, covering CI/CD, Kubernetes, and more. Link: edx.org/learn/devops 3️⃣ Coursera - Free-to-audit DevOps courses, like "DevOps Culture and Mindset" from UC Davis, focusing on CI/CD and collaboration. Link: coursera.org/learn/devops-c… 4️⃣ KodeKloud - Free courses on Docker, Terraform, and Kubernetes basics, with hands-on labs for practical learning. Link: kodekloud.com/courses/free-c… 5️⃣ FreeCodeCamp - Free DevOps tutorials and projects, including Linux, Docker, and AWS, via YouTube and articles. Link: freecodecamp.org/news/tag/devops

Su información, su responsabilidad.

How do we Perform Pagination in API Design?

7 must-know runtime complexities for coding interviews: 1. 𝐎(1) - 𝐂𝐨𝐧𝐬𝐭𝐚𝐧𝐭 𝐭𝐢𝐦𝐞 - The runtime doesn't change regardless of the input size. - Example: Accessing an element in an array by its index. 2. 𝐎(𝐥𝐨𝐠 𝐧) - 𝐋𝐨𝐠𝐚𝐫𝐢𝐭𝐡𝐦𝐢𝐜 𝐭𝐢𝐦𝐞 - The runtime grows slowly as the input size increases. Typically seen in algorithms that divide the problem in half with each step. - Example: Binary search in a sorted array. 3. 𝐎(𝐧) - 𝐋𝐢𝐧𝐞𝐚𝐫 𝐭𝐢𝐦𝐞 - The runtime grows linearly with the input size. - Example: Finding an element in an array by iterating through each element. 4. 𝐎(𝐧 𝐥𝐨𝐠 𝐧) - 𝐋𝐢𝐧𝐞𝐚𝐫𝐢𝐭𝐡𝐦𝐢𝐜 𝐭𝐢𝐦𝐞 - The runtime grows slightly faster than linear time. It involves a logarithmic number of operations for each element in the input. - Example: Sorting an array using quick sort or merge sort. 5. 𝐎(𝐧^2) - 𝐐𝐮𝐚𝐝𝐫𝐚𝐭𝐢𝐜 𝐭𝐢𝐦𝐞 - The runtime grows proportionally to the square of the input size. - Example: Bubble sort algorithm which compares and potentially swaps every pair of elements. 6. 𝐎(2^𝐧) - 𝐄𝐱𝐩𝐨𝐧𝐞𝐧𝐭𝐢𝐚𝐥 𝐭𝐢𝐦𝐞 - The runtime doubles with each addition to the input. These algorithms become impractical for larger input sizes. - Example: Generating all subsets of a set. 7. 𝐎(𝐧!) - 𝐅𝐚𝐜𝐭𝐨𝐫𝐢𝐚𝐥 𝐭𝐢𝐦𝐞 - Runtime is proportional to the factorial of the input size. - Example: Generating all permutations of a set. ♻️ Repost to help others in your network.

You’ve never seen a Git Workflow explained like this ------------------------- 🔥My @SketechWorld

@tecmint @Linux_Mint debian!

Which #Linux distro is best for everyday use? What do you use? I use @Linux_Mint because it’s lightweight, stable, and just works out of the box! Drop your choice below!

FREE Programming Books from O'Reilly - Python - SQL - Java - JavaScript - C# - Rust Links inside:

Quickly add empty lines above and below with Unimpaired 👉 bit.ly/3aC7uDq [ + space - Add line above ] + space - Below According to our stats, this is the most hated VimTrick we've published. 🤷‍♂️ 📨 Subscribe for (better) #vim tips: bit.ly/vimtrickspace

Bash scripting functions crash course

ChatGPT Prompt Frameworks 🔥

6 proven techniques to increase productivity, And reclaim your time:

TCP vs UDP

VGHF abre el acceso gratuito en línea a 1.500 revistas de juegos clásicos y 30.000 archivos históricos La Fundación para la Historia de los Videojuegos ha abierto hoy oficialmente el acceso digital a una gran parte de sus enormes archivos library.gamehistory.org

This is my favorite video on the internet!!

Defensive Linux Security

How to use AI to learn anything faster;

Cuídate de aquellos que parece que te están ayudando pero en realidad es todo lo contrario: x.com/visualfeastwan…

Cheat Sheet (Linux Commands)