Sandip Das

217 Kubernetes ONLY labs released: app.learnxops.com/labs/kubernetes

#kubernetes #labs

1 month ago | [YT] | 12

Sandip Das

Learner’s: Sandip dada , please add labs so we can practice what we learn from you
Me: Ok, I will get that done 👍
2 weeks fast towards , now we have Learn X Ops Labs , more than 50 labs across Linux, Docker, Networking , AI, MLOps and adding today AWS & Azure Labs ( best part you will be able to practice cloud without cloud account from your local machine )

I personally made sure labs works on every kind of machine ( as you can see from picture 😎)

Try it out today 👍 : app.learnxops.com/download

Repost this to spread the good news!

#cloud #devops #mlops #labs

2 months ago | [YT] | 7

Sandip Das

I used my idle raspberry Pi devices as scraping and data collector agent and via Local AI filtered and store most relevant 1303 Cloud , DevOps , MLOps , Platform Engineering & Software Engineering Jobs!

Now this job listing page is live! find the job list link here: app.learnxops.com/jobs



#joblisting #ai #cloud #devops #mlops #platformengineering

2 months ago | [YT] | 9

Sandip Das

Just release some awesome learn for LearnXops Members:
The AI Projects, under AI & Cloud & DevOps: app.learnxops.com/ai-for-cloud-devops-engineers-se…
Awesome Resume Builder (with AI) with ATS Score analyzer : app.learnxops.com/resume-builder

Finally these ware the things I was working on and finally done , now I will continue working on videos and courses

2 months ago | [YT] | 4

Sandip Das

I spent 2+ weeks designing and building a real-world, production-ready setup for Amazon EKS with auto-scaling using Karpenter — and I’m giving it away for FREE.

🔥 What’s inside this project?
✔️ Full-stack CRUD application
✔️ Deployed on Amazon EKS
✔️ Karpenter-based auto-scaling
✔️ Smart mix of Spot + On-Demand nodes
✔️ Load balancing, resilience & cost optimization
✔️ Infrastructure designed the way it’s done in production, not tutorials

💡 Why this matters

Most engineers struggle with:
Correctly configuring Spot + On-Demand together
Avoiding node churn & interruptions
Making Karpenter work reliably in real workloads

This project solves those exact problems with a clean, practical setup you can actually reuse.

👉 Try it yourself (FREE):
🔗 www.learnxops.com/aws-project-challenge-9-deploy-a…

If you’re working with EKS, Kubernetes, or Cloud cost optimization, this is for you.

💬 Let me know in the comments:
Are you using Karpenter or Cluster Autoscaler in production?


Cheers,
Sandip Das

hashtag#AWS hashtag#EKS hashtag#Kubernetes hashtag#Karpenter hashtag#DevOps hashtag#CloudEngineering hashtag#AutoScaling hashtag#LearnXops

7 months ago | [YT] | 18

Sandip Das

Project: 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦 𝐰𝐢𝐭𝐡 𝐀𝐖𝐒 𝐅𝐚𝐫𝐠𝐚𝐭𝐞, 𝐂𝐞𝐥𝐞𝐫𝐲, 𝐒𝐐𝐒 & 𝐓𝐞𝐱𝐭𝐫𝐚𝐜𝐭
Link: www.learnxops.com/aws-project-challenge-8-intellig…

‪@learnTechWithSandip‬

#aws #projects

8 months ago | [YT] | 20

Sandip Das

Hi @everyone,

I’m thrilled to share some great news 🎉

Over the last two years, I’ve been silently pursuing my Master of Science and doing specialization on Cloud, DevOps, and AI/ML — and I’m happy to say it’s now completed!

Balancing this journey alongside content creation, client project deliveries, and teaching wasn’t easy — but it’s been incredibly rewarding.

Six years ago, when I first tried learning AI & ML, I completely failed. I genuinely believed it wasn’t for me. But two years back, I decided — it’s now or never. I treated it as a personal challenge, took it up as a Master’s pursuit, and today, I can proudly say I made it through.

Many of the AI/ML and MLOps projects you’ve seen on LearnXops came directly from the clarity and foundation I gained through this journey. My goal has always been to simplify complex concepts so anyone can learn them with confidence.

📍Last week, I was on an onsite trip in Hyderabad, which delayed the Advanced AWS Projects release — but this week, it’s happening! I’ll be releasing 5 Real-Life Advanced AWS Projects, wrapping up 30 Days of AWS (part of 90 Days of Cloud), and kicking off 30 Days of Azure (same format — 20 Days Theory + 10 Days Projects).

Alongside that, I’ll also be launching new Case Studies, Projects, and eBooks — exclusively for LearnXops Premium Members.

🎁 Special Announcement:
To celebrate this milestone, I’m introducing the LearnXops Lifetime Membership — with 50% off exclusively for all existing LearnXops Premium Members.
Use code ProMembers50PercentOff or use this pre-applied link:
👉 topmate.io/sandip_das_official/1756332?coupon_code…

This is my way of showing gratitude and commitment to delivering never-ending quality content through LearnXops.

Thank you all for your continuous support and encouragement 🙌
Here’s to learning, growing, and building — together.

Also, started making YouTube videos, stay tuned!

Regards,
‪@learnTechWithSandip‬

8 months ago (edited) | [YT] | 12

Sandip Das

Durga Pooja is one of our biggest festivals, and I want to make it special for all my followers and well-wishers, especially those who are Learning from LearnXops.com (it's limited to 100 persons, so get it FAST! )
Use code "DurgaPooja25" to get 25% off on LearnXops Premium Plan
This is only applicable when you use the "CashFree" Payment Gateway
www.learnxops.com/membership-payment/

What about the international Members (or actually anyone)?
You can use the Topmate to pay and avail this offer: topmate.io/sandip_das_official/1513567?coupon_code…

Cheers,
‪@learnTechWithSandip‬

10 months ago | [YT] | 5

Sandip Das

If you would like to start learning MLOps in 2025, start with this :

Day 1: Intro to MLOps: ML Meets DevOps: lxop.in/day1

Day 2: MLOps Tools Landscape: lxop.in/day2

Day 3: Data Versioning with DVC: lxop.in/day3

Day 4: Reproducible ML environments (Conda & Docker): lxop.in/day4

Day 5: Feature Engineering & Feature Stores: lxop.in/day5

Day 6: Training ML Models with Scikit-learn & TensorFlow: lxop.in/day6

Day 7: Model Experiment Tracking with MLflow: lxop.in/day7

Day 8: Model Evaluation & Metrics: lxop.in/day8

Day 9: ML Pipelines with Kubeflow Pipelines - lxop.in/day9

Day 10: Serving ML Models with FastAPI & Flask: lxop.in/day10

Day 11: Packaging Models with Docker: lxop.in/day11

Day 12: CI/CD for ML with GitHub Actions: lxop.in/day12

Day 13: ML Model Deployment: lxop.in/day13

Day 14: Data Drift & ML Model Drift Detection : lxop.in/day14

Day 15: Automated Retraining ML Pipelines: lxop.in/day15

Day 16: Security in MLOps: lxop.in/day16

Day 17: Explainable AI (XAI) in Production: lxop.in/day17

Day 18: ML Model Governance & Compliance: lxop.in/day18

Day 19: Monitoring ML Systems in Production: lxop.in/day19

Day 20: Model Registry: lxop.in/day20

Day 21: Scaling ML Model Inference with Kubernetes: lxop.in/day21

Day 22: MLOps with ML Platforms: lxop.in/day22

Day 23: Managing LLMs in Production: lxop.in/day23

Day 24: Agentic AI & RAG: lxop.in/day24

Day 25: MCP Explained for MLOps Engineers: lxop.in/day25

Day 26: Project: End-to-End MLOps Pipeline: lxop.in/day26

Day 27: Model Deployment with Serverless Architectures: lxop.in/day27

Day 28: Cost & Performance Tuning in MLOps: lxop.in/day28

Day 29: Disaster Recovery & HA for ML Systems: lxop.in/day29

Day 30: MLOps Interview Question & Answers: lxop.in/day30



🔁 Consider a Repost if this is helpful



Cheers,

‪@learnTechWithSandip‬

#mlops #devops #cloud

11 months ago | [YT] | 14

Sandip Das

Disaster Recovery & High Availability for ML Systems
Read: www.learnxops.com/disaster-recovery-high-availabil…

11 months ago | [YT] | 7