Aashish Biradar

Coding from India.
RT != Endorsement

[Louis Gleeson @aigleeson]

Coding games are the best way to learn coding.

From CSS, Python, JavaScript to Blockchain.

Here are 10 of the BEST online games to learn coding:

[sysxplore @sysxplore]

Docker components explained

[Code Geek @codek_tv]

Docker Clearly Explained

[Sahn Lam @sahnlam]

A Visual Guide to CI/CD

𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 (𝗖𝗜) is a foundational practice in DevOps where developers frequently merge code changes into the main branch, often multiple times a day. This process is complemented by automated testing to ensure new changes integrate seamlessly with existing code. The primary goal of CI is to find and address bugs quicker, improve software quality, and reduce the time required to validate and release updates

𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 (𝗖𝗗) automates deploying code changes to a production without human intervention. It ensures every change passing all automated tests gets deployed. It accelerates customer feedback by releasing updates more frequently. CD also reduces pressure on developers by eliminating manual release processes.

Some companies rely on 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 instead. Continuous Delivery extends CI by automatically preparing code changes for release to production. However, unlike Continuous Deployment, it requires manual approval prior to production deployment. This practice ensures that all changes are automatically built, tested, and ready for release. It allows teams to deploy new changes anytime at the push of a button.

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

[javinpaul @javinpaul]

📗I created a GitHub repository to help you learn System Design and Software architecture
It gives you:
- system design problems
- tutorials
- system design resources
Feel free to add and contribute, this is just start, let's make it best
repo - https://t.co/40koHrJwUw

[Ezekiel @ezekiel_aleke]

35 SQL Interview Questions & Answers You Should Know.

Repost for others

[Manish Kumar Shah @manishkumar_dev]

Google, IBM and Harvard University are sponsoring Free courses for Python

𝟭. 𝗖𝗦𝟱𝟬𝗣 𝗳𝗿𝗼𝗺 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆
https://t.co/lI20d9WJiu

𝟮. 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗯𝘆 𝗜𝗕𝗠
https://t.co/HmlPncu0hz

𝟯. 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗣𝘆𝘁𝗵𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗯𝘆 𝗨𝗱𝗮𝗰𝗶𝘁𝘆 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘
https://t.co/4278dCS2ql

𝟰. 𝗟𝗲𝗮𝗿𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 𝗯𝗮𝘀𝗶𝗰𝘀
https://t.co/o5sqOGJkQD

𝟱. 𝗟𝗲𝗮𝗿𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 - 𝗙𝘂𝗹𝗹 𝗖𝗼𝘂𝗿𝘀𝗲 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀 𝗯𝘆 𝗙𝗿𝗲𝗲𝗖𝗼𝗱𝗲𝗖𝗮𝗺𝗽
https://t.co/JYXyKkCmlz

6. Machine Learning with Python
https://t.co/C6agbun5Qq

7. Python for Beginners (2023)
https://t.co/G5DW6VMLJO

8. Learn Python for Total Beginners
https://t.co/C4cfUmbp3t

9. Python for Data Science, AI & Development
https://t.co/gTbLYAFUY9

10. Python for Everybody Specialization
https://t.co/H7AIMAVssV

11. Crash Course on Python
https://t.co/pZYQ3d4Xfc

12. Google IT Automation with Python Professional Certificate
https://t.co/x4Hh93EDrx

13. Python 3 Programming Specialization
https://t.co/KITQXqIYCA

14. Get Started with Python by Google
https://t.co/rfboj4anYp

15. Programming in Python by Meta
https://t.co/reYWjwTgNH

16. Data Analysis with Python by IBM
https://t.co/3N3nlj9Mk7

Become a Python Backend Developer in 4 Months! 💼🔥

🚀 𝗬𝗼𝘂𝗿 𝟰-𝗠𝗼𝗻𝘁𝗵𝘀 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗹𝗮𝗻 🚀

1️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟭: 𝗚𝗲𝘁 𝘆𝗼𝘂𝗿 𝗯𝗮𝘀𝗶𝗰𝘀 𝗿𝗶𝗴𝗵𝘁

1. Learn Python:https://t.co/Z8TDfySsYq
2. Python Projects: https://t.co/pw0cz1Nepv
3. DSA with Python: https://t.co/nG52NVLv53

2️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟮: 𝗗𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝗙𝗹𝗮𝘀𝗸 𝗮𝗻𝗱 𝗔𝗣𝗜

Learn Flask: https://t.co/J2Z8aQF2NI
Flask Projects: https://t.co/C6isapYKUs
Learn REST API with Flask: https://t.co/9Oog6HY9vs

3️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟯: 𝗠𝗮𝘀𝘁𝗲𝗿 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗮𝗻𝗱 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀

1. Learn Multithreading, Multiprocessing, Asyncio: https://t.co/AunQ4Oo7yN
2. Gunicorn & Nginx with Flask: https://t.co/zF2lmOuL5p
3. TDD with Python & Flask: https://t.co/frw4zRv0dp
4. Basic RDBMS: https://t.co/ZW6cxPeT7c
5. Learn SQL: https://t.co/HhRIlpk26z & https://t.co/Dw2NsYQ73n
6. PostgreSQL with Python: https://t.co/9kNBk3hVmg
7. Flask App with PostgreSQL: https://t.co/L3FLBwvIjm

4️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟰: 𝗣𝗼𝗹𝗶𝘀𝗵 𝘆𝗼𝘂𝗿 𝘀𝗸𝗶𝗹𝗹𝘀 𝗮𝗻𝗱 𝗽𝗿𝗲𝗽𝗮𝗿𝗲 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗷𝗼𝗯 𝗺𝗮𝗿𝗸𝗲𝘁

1. Basics of Bash: https://t.co/xLUpDh9Qix
2. Basics of Docker: https://t.co/nAz86BWUQB
3. Deploy Flask App with Docker: https://t.co/fYrFI2XJIe
4. GIT & GitHub: https://t.co/egDZe2FjcJ
5. Python Portfolio on Github: https://t.co/Q6J2vir3EI
6. Python Resume Ideas: https://t.co/rr2TvTVpPN

Follow @manishkumar_dev for more such content.

[Alex Xu @alexxubyte]

What does a typical microservice architecture look like?

[System Design Codex @ProgressiveCod2]

The Kubernetes Intro You Deserve!

✅ What is Kubernetes?

It’s a piece of software that lets you orchestrate multiple containers.

How does it appear for the developers?

[1] The developer creates manifest files for their apps and submits them to Kubernetes

[2] Kubernetes checks those files and deploys the necessary apps to a cluster of nodes

[3] Kubernetes manages the complete life cycle of these apps based on the manifest file

✅ Kubernetes Architecture

Kubernetes is deployed as a cluster with two main parts:
- Master Node
- Worker Nodes

👉 The Master Node hosts the Control Plane. Think of it as the manager in an organization.

It consists of several important parts:

[1] The Kube-apiserver acts as an entry point to the cluster

[2] A scheduler that assigns pods to worker nodes

[3] Controller manager for tracking the nodes and handling failures

[4] etcd for storing the cluster’s configuration

👉 There are multiple worker nodes controlled by the master node. Think of them as employees.

A worker node consists of:

[1] A container runtime such as Docker

[2] Kubelet for talking to the API server and managing containers.

[3] kube-proxy for communication between pods and outside the network

✅ Top Kubernetes Resources
You can create many resources using Kubernetes.

However, these 4 are probably the most used.
- Pod
- Service
- Deployment
- Volume

👉 Pods are the smallest atomic unit you can create in Kubernetes.

Kubernetes groups multiple containers into a single unit known as Pod.

Containers host your applications and a Pod provides a single execution environment to these containers.

👉 Kubernetes Service provides a uniform interface for various pods to talk to each other internally.

They also help load balance requests between multiple pods running the same app.

👉 Deployment is a high-level resource used for deploying applications declaratively.

Think of the deployment as a template for multiple pods.

Depending on the configuration, the Deployment ensures that the desired number of pods is always running.

👉 Kubernetes Volumes are a component of a pod.

They are a form of storage and are used when you want the application to persist some data across container restarts.

⏰ So - have you used Kubernetes in your project?

[Manish Kumar Shah @manishkumar_dev]

𝐅𝐑𝐄𝐄 𝐃𝐞𝐯𝐎𝐩𝐬 & 𝐂𝐥𝐨𝐮𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬:

1. DevOps
https://t.co/ChuIldPa6T

2. CI/CD
https://t.co/FytakWeZBy

3. Docker
https://t.co/NN7s1bICs4

4. Kubernetes
https://t.co/iO9NryQAEh

5. GIT
https://t.co/B7phySann8

6. GitHub
https://t.co/zhF4OhcZAq

7. Linux
https://t.co/cUfNLlqW4W

8. Cloud Computing
https://t.co/nnAZTovji4

9. AWS
https://t.co/chxzvlfheu

10. Azure
https://t.co/4to0qKYE1a

11. AWS
https://t.co/chxzvlfheu

12. Azure
https://t.co/4to0qKYE1a

13. Cloud Computing
https://t.co/nnAZTovji4

14. Linux
https://t.co/cUfNLlqW4W

15. GCP
https://t.co/qUw6W48XjG

16. Serverless
https://t.co/HfInDDjLQo

17. Docker
https://t.co/WdlbiuHT3V

18. Kubernetes
https://t.co/iO9NryQAEh

19. CI/CD
https://t.co/FytakWeZBy

20. Jenkins
https://t.co/pbxre5Z5nv

21. Puppet
https://t.co/GxnrwFO4Mp…

22. Chef
https://t.co/yHktfaHikF

23. Ansible
https://t.co/zhMvN25g8b

24. Selenium
https://t.co/w3r3toq4rQ

25. VirtualBox & vSphere
https://t.co/ggIQJJpmVs

Follow @manishkumar_dev for such free resources.

[Sahn Lam @sahnlam]

Top Redis Use Cases

I've used Redis in production for almost a decade. It's reliable and easy to use (if used correctly). Here are my top 5 use cases where it shines:

1. Caching

The most common use case is to utilize Redis for caching. This helps protect the database layer from overloading. Redis offers fast lookup for cached data and can help improve application performance.

2. Session Store

We use Redis to share user session data among stateless servers. Redis provides a centralized place to store session data and makes it easy to scale out servers.

3. Distributed lock

We use Redis distributed locks to grant mutually exclusive access to shared resources. This prevents race conditions in distributed systems. Redis locks are easy to implement and automatically expire.

4. Counter and Rate Limiter

We use Redis to track like counts, view counts etc on social media apps. Redis counters provide atomic increments/decrements. We also use Redis to enforce rate limits on our API endpoints. This helps prevent abuse.

5. Leaderboard

Sorted sets make it easy to implement gaming leaderboards in Redis. We can add, update, or remove users from the leaderboard and query ranges efficiently.

There are many other features in Redis. What are some other real-world use cases where you've used Redis successfully?

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

[Sahn Lam @sahnlam]

How C++, Java, and Python Work Under the Hood?

Compiled languages like C++ and Go transform source code into machine code using a compiler before execution. The compiled machine code can then be directly executed by the CPU.

Java first compiles source code into bytecode, which is platform-independent and executed by the Java Virtual Machine (JVM). The JVM can further boost performance using Just-In-Time (JIT) compilation to convert bytecode to machine code at runtime.

Interpreted languages like Javascript and Ruby don't undergo compilation. Instead, their code is processed line-by-line by an interpreter during execution. However, modern JavaScript engines like V8 also utilize JIT compilation for enhanced performance.

Python is a mix of both worlds. It first compiles source code into platform-independent bytecode, which is then executed line-by-line by the platform-dependent interpreter. In addition, implementations like PyPy use JIT compilation for a speed boost.

Generally, compiled languages can offer speed advantages, but the line between compiled and interpreted languages is increasingly blurred thanks to modern optimization techniques.

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

[Pranay Pathole @PPathole]

A single SpaceX's Starship is designed to do in a day what all rockets on Earth currently do in a year. Not many fully understand the insane capability of Starship 🤯 @elonmusk

[Savukku_Shankar @savukku]

Brilliant.

[ANI @ANI]

Delhi: 1000 Made in India drones make different formations as part of the Beating Retreat ceremony at Vijay Chowk

[John Papa @John_Papa]

Announcing a lightweight version of VS @Code in the browser!

🗂 Local file viewing & editing
💻Code client-side HTML, JavaScript, & CSS
🐞Debug
🔋use lower powered machines like Chromebooks & iPads
☁️ Work with GitHub
🦚Enjoy Peacock v3.10+

https://t.co/Tgwfxwznix

[GitHub @github]

A browser in your terminal that supports HTML, CSS, JS, images, videos, 𝘢𝘯𝘥 WebGL?!? Whoah. https://t.co/WTNFHPo2H0

[Jason Miller 🦊⚛ @_developit]

👩‍🚀 Introducing 𝗪𝗠𝗥:

The tiny all-in-one development tool for modern web apps.

Everything you need to build a fast Preact site, from dev to prod.

🦄 TSX, HMR, CSS Modules, etc
🦦 use npm modules without installing
📦 one 2mb file, no dependencies

→ https://t.co/B9738JEgsY