These 5 Prompts Turn AI Image Models Into Technical Storytellers ⬇️⬇️ 1. Concept Explanation Diagram (Core Style)

Use this for most Kubernetes concepts (Pods, Services, Nodes, etc.)

Prompt:

“Hand-drawn flat illustration explaining a cloud-native concept, simple cartoon style, clean white background, blue and gray color palette, labeled components with arrows, educational tech diagram, friendly developer-focused illustration, minimal shadows, vector-like clarity, visual guide style, no photorealism”

Kubernetes isn’t dying loudly - it’s dying quietly.

Not in blogs.
Not in conferences.
But inside private Slack channels, architecture reviews, and FAANG infra meetings.

The truth? Big Tech engineers are slowly moving away from Kubernetes.

Not because it’s bad -
but because it’s too heavy, too complex, too slow, and too painful to maintain at scale (if not desgined with proper planning).

After managing multiple production clusters myself, I get it.

Here are the 7 orchestration alternatives quietly replacing Kubernetes behind the scenes:

🚀 Want to become an AI Engineer in 2025?

Here’s the ultimate roadmap, from Python to MLOps.

Language ➤ Python
Mathematics ➤ Linear Algebra + Probability + Statistics + Calculus
Data Basics ➤ NumPy + Pandas + SQL
Data Visualization ➤ Matplotlib + Seaborn + Plotly
Classical Machine Learning ➤ scikit-learn + XGBoost + Model Evaluation
Deep Learning ➤ PyTorch/TensorFlow + Keras
Natural Language Processing (NLP) ➤ Hugging Face Transformers + Datasets + Tokenizers
Computer Vision ➤ OpenCV + Image Preprocessing
Embeddings ➤ OpenAI/HF Embeddings
RAG (Retrieval-Augmented Generation) Stack ➤ LangChain/LlamaIndex + FAISS
Agents & Workflows ➤ LangGraph
APIs ➤ FastAPI
Vector Databases ➤ Pinecone

Additional Core Topics ➤ MLOps + Cloud Computing + Ethics + Data Engineering + Monitoring + Security 1. Programming Language: Python

Why Python?
Python's simplicity, extensive libraries, and large community make it the go-to language for AI and data science.

Key Areas:
Fundamentals: Syntax, data structures, control flow, functions, object-oriented programming.
Advanced: Decorators, generators, context managers, asynchronous programming.
Best Practices: Code style (PEP 8), version control (Git), testing (pytest).

Site Reliability Engineering (SRE) 🚀🚀 The SLI → SLO → SLA Flow

Learn Terraform by Doing: 10 Practical Tasks for Beginners ⬇️ 1. Install Terraform & Setup Env.

🚀Thought AWS, Azure, or GCP were your only cloud choices? Ready for a surprise!

(it will keep you 3 steps ahead than the crowd for sure👍)

Here, I have curated a list of 30 Cloud Providers each with a special knack to revolutionize your business, Organization specially your career.

✅ Now, you will have the understanding of "when to choose which cloud provider" based on your requirement🎯

🧵🧵🧵 ➡️Amazon Web Services (AWS) - Extensive service catalog, robust global infrastructure.

➡️Microsoft Azure - Seamless integration with Microsoft tools & services, hybrid capabilities.

➡️Google Cloud Platform (GCP) - Advanced machine learning, big data, and analytics services.

➡️IBM Cloud - Focus on hybrid cloud solutions, AI-powered automation.

➡️Oracle Cloud - Specialized in database management and enterprise applications.

AWS for Beginners to Pros: A Visual Tour of Key Services 🎯🔥

1/7 AWS Database Services 🚀🚀 2/7 AWS Networking Services 🚀🚀

CI/CD (Handbook) - Build, Test, Deploy! 🔥🔥 - What is CI/CD?
- CI/CD pipeline (Explained)
- CI/CD Components
- Why Adopt CD/CD?

AWS Architect Interview Blueprint: Key Topics & Questions 🔥🔥 What this guide will cover, Let's deep dive (one by one) 👇👇

10 tasks to excel in Git/Github (version control) for beginners 🔥🔥 1. Install and Configure Git

- Download and install Git on your computer (from
git-scm.com).

- Set up your identity with
git config --global user.name "Your Name"

and

git config --global user.email "your.email@example.com".

- Verify the setup by running git config --list.

From Docker to ELK Stack, these tools are essential for automation, scalability, and monitoring.

"Use Cases == Problem + Solutions + Benefits"

Learn their real-world use cases and level up your DevOps skills today!

By the way, Which tool is your favorite? Before diving for the tools, let's understand quickly what is DevOps & why it matters?

Master Linux, One Command at a Time! 🚀

These essential commands will make you unstoppable in the terminal. Let’s dive in! 🧵

Bookmark & share with your network! pwd, cd, ls

Quick Guide: Networking Secrets (Cloud & DevOps) 🔥🔥 What it covers?

Master AWS in Minutes (Not in hours)!

This handbook has everything you need. Are you ready? 1. What is Cloud Computing?
2. Scalability
3. Cost Savings
4. Flexibility

𝑴𝒂𝒔𝒕𝒆𝒓𝒊𝒏𝒈 𝑨𝒖𝒕𝒐𝒎𝒂𝒕𝒊𝒐𝒏 𝒂𝒏𝒅 𝑰𝒏𝒇𝒓𝒂𝒔𝒕𝒓𝒖𝒄𝒕𝒖𝒓𝒆 𝒂𝒔 𝑪𝒐𝒅𝒆 (𝑰𝒂𝑪) 𝒊𝒔 𝒆𝒔𝒔𝒆𝒏𝒕𝒊𝒂𝒍 𝒇𝒐𝒓 𝑰𝑻 𝒑𝒓𝒐𝒇𝒆𝒔𝒔𝒊𝒐𝒏𝒂𝒍𝒔 𝒘𝒐𝒓𝒌𝒊𝒏𝒈 𝒊𝒏 𝒕𝒉𝒆 𝒄𝒍𝒐𝒖𝒅.

Here’s a 6-step approach to overcoming challenges and becoming proficient 👇 1. Learn the Fundamentals of Infrastructure as Code (IaC)

- Understand what IaC is and its importance in cloud automation.
- Learn about declarative vs. imperative approaches.
- Get familiar with version control systems (Git, GitHub, GitLab).

Terraform : A Story for Cloud Professionals 🔥🔥 -> What is Terraform
-> Why Terraform
-> Setting up your env.
-> Installing Terraform

Learn Python from Scratch: 5 Hands-On Projects 🔥🔥 -> What is Python?
-> Why Learn Python?
-> Getting Started with Python
-> Installing Python

Serverless vs. Containers vs. Virtual Machines (VMs) – What to Choose and When?

🚀 Which one is right for your workload in AWS? Let's break it down! 1. Virtual Machines (VMs)

A VM is a fully virtualized server running on a hypervisor. You get a full OS, compute, storage, and network control.

🔹 When to Use VMs?
✔️ When you need full control over the OS and runtime environment.
✔️ For traditional applications that require a persistent server.
✔️ If you need to run legacy applications.
✔️ For workloads requiring strong isolation (security & compliance).

Pros & Cons
✅ Pros:
✔️ Full flexibility (custom OS, network, security).
✔️ Strong isolation between workloads.
✔️ Good for monolithic apps and legacy software.

❌ Cons:
- Slower startup times compared to containers.
- Higher cost due to over-provisioning.
- Requires patching, updates, and maintenance.

Cost Implications
💲 Pay for allocated CPU, memory, and storage (even when idle).
💲 Long-running workloads are more cost-effective than bursty ones.

I want to master CI/CD pipelines, but I don’t know how to set them up without getting overwhelmed.

👇👇 1. Understand the Basics

Learn the Concepts: Understand CI (Continuous Integration) and CD (Continuous Deployment/Delivery) principles.
- CI: Automate code integration, testing, and error detection.
- CD: Automate deployment to environments.

Key Benefits: Faster feedback, reduced manual effort, improved quality.

Tools Overview: Get familiar with popular tools like Jenkins, GitHub Actions, GitLab CI, CircleCI, or Azure DevOps.

I want to automate deployments, but I don’t know how to do it without breaking production.

👇👇 1. Embrace Continuous Integration/Continuous Delivery (CI/CD):

- CI: Automate the build, test, and code analysis phases. This catches errors early on before they reach production.

- CD: Automate the release process, allowing for frequent and reliable deployments.

How to deal with Security & Compliance related issues in Cloud Solutions 👇👇

1. How to handle a data breach in Cloud environment
2. Ensure Data Encryption (at rest/ in transit) across clouds
3. How to handle security compliance (eg. GDPR, ISO 27001)
4. Developer accidently exposed credentials in public Git Repo
5. Design a secure CI/CD pipeline for deploying Apps

check now 🧵🧵 1. How to handle a data breach in Cloud environment

●Immediate Action: Isolate affected systems to prevent further damage.

● Investigate: Use audit logs (e.g., AWS CloudTrail) to identify the root cause.

● Mitigate: Patch vulnerabilities and revoke compromised credentials.