Undigcine

IT SRE| |Saved by his grace|Husband & a Father| ❤️ Christ, Technology, Mining,farming & more.
My views on this app do not reflect those of my employer.

[Dhanian 🗯️ @e_opore]

📂 Backend Engineering Roadmap.
┃
┣ 📂 Foundations
┃ ┣ 📂 Internet Fundamentals (HTTP, HTTPS, DNS)
┃ ┣ 📂 TCP/IP & Networking Basics
┃ ┣ 📂 Linux Command Line
┃ ┣ 📂 Git & Version Control
┃ ┗ 📂 Data Structures & Algorithms
┃
┣ 📂 Programming Languages
┃ ┣ 📂 JavaScript / TypeScript
┃ ┣ 📂 Python
┃ ┣ 📂 Go
┃ ┣ 📂 Java / C# (Optional)
┃ ┗ 📂 Choosing the Right Language
┃
┣ 📂 Backend Frameworks
┃ ┣ 📂 Express.js / Fastify
┃ ┣ 📂 NestJS
┃ ┣ 📂 Django / FastAPI
┃ ┣ 📂 Spring Boot (Optional)
┃ ┗ 📂 Framework Best Practices
┃
┣ 📂 API Development
┃ ┣ 📂 RESTful APIs
┃ ┣ 📂 GraphQL
┃ ┣ 📂 gRPC
┃ ┣ 📂 API Versioning
┃ ┗ 📂 API Documentation (OpenAPI / Swagger)
┃
┣ 📂 Authentication & Security
┃ ┣ 📂 Sessions & Cookies
┃ ┣ 📂 JWT Authentication
┃ ┣ 📂 OAuth 2.0 & OpenID Connect
┃ ┣ 📂 Password Hashing (bcrypt, Argon2)
┃ ┗ 📂 CORS, CSRF & XSS Protection
┃
┣ 📂 Databases
┃ ┣ 📂 PostgreSQL & MySQL
┃ ┣ 📂 MongoDB
┃ ┣ 📂 Redis Caching
┃ ┣ 📂 Database Indexing
┃ ┗ 📂 Query Optimization
┃
┣ 📂 ORMs & Data Access
┃ ┣ 📂 Prisma
┃ ┣ 📂 Sequelize
┃ ┣ 📂 SQLAlchemy
┃ ┣ 📂 Migrations & Seed Data
┃ ┗ 📂 Repository Pattern
┃
┣ 📂 System Design
┃ ┣ 📂 Scalability Fundamentals
┃ ┣ 📂 Load Balancing
┃ ┣ 📂 Caching Strategies
┃ ┣ 📂 Microservices vs Monoliths
┃ ┗ 📂 Event-Driven Architecture
┃
┣ 📂 Asynchronous Processing
┃ ┣ 📂 Message Queues (RabbitMQ)
┃ ┣ 📂 Apache Kafka Basics
┃ ┣ 📂 Background Jobs
┃ ┣ 📂 Pub/Sub Architecture
┃ ┗ 📂 Event Processing
┃
┣ 📂 DevOps & Deployment
┃ ┣ 📂 Docker & Containers
┃ ┣ 📂 Kubernetes Basics
┃ ┣ 📂 CI/CD Pipelines
┃ ┣ 📂 Cloud Platforms (AWS, Azure, GCP)
┃ ┗ 📂 Nginx & Reverse Proxies
┃
┣ 📂 Monitoring & Reliability
┃ ┣ 📂 Logging Best Practices
┃ ┣ 📂 Prometheus & Grafana
┃ ┣ 📂 Health Checks
┃ ┣ 📂 Distributed Tracing
┃ ┗ 📂 Performance Monitoring
┃
┣ 📂 Testing & Quality
┃ ┣ 📂 Unit Testing
┃ ┣ 📂 Integration Testing
┃ ┣ 📂 API Testing
┃ ┣ 📂 Load & Stress Testing
┃ ┗ 📂 Test Automation
┃
┣ 📂 AI Integration
┃ ┣ 📂 OpenAI API Integration
┃ ┣ 📂 AI-Powered Backend Services
┃ ┣ 📂 Vector Databases
┃ ┣ 📂 Background AI Workflows
┃ ┗ 📂 AI API Security & Cost Optimization
┃
┣ 📂 Real-World Projects
┃ ┣ 📂 Authentication Service
┃ ┣ 📂 E-commerce Backend API
┃ ┣ 📂 Chat Application Backend
┃ ┣ 📂 AI-Powered SaaS Backend
┃ ┗ 📂 Scalable Microservices Platform
┃
┣ 📂 Practice & Growth
┃ ┣ 📂 Build Production APIs
┃ ┣ 📂 Contribute to Open Source
┃ ┣ 📂 Technical Blogging
┃ ┣ 📂 System Design Practice
┃ ┗ 📂 Interview Preparation
┃
┗ 📂 Career & Monetization
┣ 📂 Backend Engineer Roles
┣ 📂 API Consultant
┣ 📂 SaaS Development
┣ 📂 Freelancing & Remote Work
┗ 📂 Continuous Learning
Follow this consistently for 4–6 months and you'll build the skills to design, develop, and deploy production-ready backend systems.

Grab the Backend Engineering Ebook:
https://t.co/t9mqUuRbjx

[Undigcine @Undi83]

@yourclouddude Roadmap

[Undigcine @Undi83]

@Lemonbriz Very true assessment

[Undigcine @Undi83]

@AbelMudau3 @_Bongekile_ You talking to me here

[Undigcine @Undi83]

@KaizerChiefs How do we address him now? 🤔🤔🤔

[Abraham Okah(info hub) @AbrahamOkah2]

CISCO is offering FREE trainings and certifications for people looking to learn:

- Data Analytics, - Data Science, - Cybersecurity, - JavaScript, - Python.These are self-paced courses, so you can practice as you learn
👇👇👇

1. Data Analytics
https://t.co/kNuY4XGThf
2. JavaScript.
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3. Python Essentials
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4. Cybersecurity
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5. Operating Systems Basics
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6. Computer Hardware Basics
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7. Digital Literacy (IoT and Digital Transformation).
https://t.co/zHRAS5w5kr

[Undigcine @Undi83]

@Dailyfarmdiary @ChimdiIbeawuchi Thank you both for this, last night I went to sleep planning my project and how I will get to 5000 layers, calculating feed and integrating crops on 2hectars of land + BSF . I woke up today to read this. You made my day and I am your new follower.
Thank you

[Tech Fusionist @techyoutbe]

2026 AI/ML Career = MLOps + AI Engineering + Infrastructure

Step 1: Master Python & Data Engineering
Step 2: Linux & Shell Scripting
Step 3: Vector Databases & RAG
Step 4: ML Fundamentals & Stats
Step 5: LLM Fine-tuning
Step 6: Autonomous AI Agents
Step 7: Docker Containerization
Step 8: Kubernetes Orchestration
Step 9: GitHub Actions CI/CD
Step 10: Terraform for Cloud GPUs
Step 11: AWS/Azure/GCP Cloud Ops
Step 12: Model Versioning (MLflow)
Step 13: Distributed System Design
Step 14: AI Observability (Metrics/Logs)
Step 15: FinOps & Cost Optimization
Step 16: Secure AI Infrastructure
Step 17: Site Reliability Engineering
Step 18: Advanced Prompt Engineering
Step 19: Production-Grade Scaling
Step 20: Incident Management & RCA

Kickstart your journey now!

#AI #MLOps #TechCareers

[Darshil | Data Engineer👨🏻‍🔧 @parmardarshil07]

FREE AWS Data Engineering Masterclass | 4 HOURS (with)

YouTube Data Pipeline End-To-End Project (S3, Lambda, Glue, Athena, Step Functions)

Here's what you'll learn:

☁️ 𝗖𝗹𝗼𝘂𝗱 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
→ IaaS vs PaaS vs SaaS — what you manage vs what AWS manages
→ Regions, Availability Zones, Edge Locations
→ AWS Account setup & IAM basics

🪣 𝗦𝘁𝗼𝗿𝗮𝗴𝗲
→ S3 deep dive — storage classes, lifecycle, versioning, replication
→ EBS vs EFS — when to use block vs file storage

🗄️ 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀
→ RDS, DynamoDB, Redshift, DMS
→ When to pick relational vs NoSQL vs data warehouse

⚡ 𝗖𝗼𝗺𝗽𝘂𝘁𝗲
→ EC2 instance types & pricing models
→ Lambda — serverless data processing
→ Glue — managed ETL with PySpark → EMR — big data at scale

📊 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀
→ Athena — SQL on S3, pay per query
→ Glue Data Catalog — centralized metadata
→ QuickSight — dashboards & BI → Kinesis — real-time streaming

🔨 𝗧𝗵𝗲 𝗛𝗮𝗻𝗱𝘀-𝗢𝗻 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 This is where it gets real.
You'll build a complete YouTube Trending Data Pipeline.

Live YouTube API data → S3 → Lambda → Glue → Athena → QuickSight.

→ 𝗕𝗿𝗼𝗻𝘇𝗲 𝗟𝗮𝘆𝗲𝗿: Ingest raw data from YouTube API across 10 countries
→ 𝗦𝗶𝗹𝘃𝗲𝗿 𝗟𝗮𝘆𝗲𝗿: Cleanse, deduplicate, add engagement metrics with Glue ETL
→ 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗚𝗮𝘁𝗲: Validate before anything hits production
→ 𝗚𝗼𝗹𝗱 𝗟𝗮𝘆𝗲𝗿: Business-ready analytics — trending, channel & category insights

All orchestrated by Step Functions. Failures alert via SNS. Automated on a schedule.

This is how production data pipelines are built.

You can watch the complete video for free ⬇️

[yourclouddude @yourclouddude]

A 90-day plan to become job-ready in Python (2026) 🧵

[Undigcine @Undi83]

@Afrihost My network has not been working the whole day, how is this resolved?

[Piyush Sachdeva - Building ReelDrop + CannerAI 🚀 @techie_piyush]

top 50 linux commands every devops engineer should know.
if you're debugging or securing servers, the terminal is your best friend.

here's the ultimate breakdown: 🧵

[yourclouddude @yourclouddude]

Learning Python but still not getting interviews?

It’s usually because of this.

Most beginners learn Python like this ❌
• Finish courses
• Memorize syntax
• Collect certificates
• Build tutorial projects

But hiring managers look for something else.

This is how Python actually gets you hired 👇

1️⃣ Pick one direction
Automation • Backend • Data

2️⃣ Learn the core properly
Functions • Lists • Dicts • APIs

3️⃣ Build 4 projects that feel like real work

Example:
• File automation tool
• API data collector
• Data report generator
• Simple web app

4️⃣ Push everything to GitHub

5️⃣ Write a clean README
Explain the problem → solution → output.

6️⃣ Deploy at least one project

7️⃣ Show your progress publicly.

Truth most learners realise too late:

Companies don’t hire people who
“learned Python”.

They hire people who can
build with Python.

Courses teach syntax.
Projects prove skills.

Reply PYTHON
and I’ll share 10 Python projects that actually impress recruiters. 🚀

[Undigcine @Undi83]

@afcstuff @SamJDean Jesus has to go we need a top notch no9

[AsyncTrix @asynctrix]

DevOps Breakdown (2026)

• Linux fundamentals
• Networking fundamentals
• Git & branching strategies
• CI / CD pipelines
• Infrastructure as Code (TF / OT)
• Containers (Docker)
• Orchestration (Kubernetes)
• Cloud platforms (AWS / Azure / GCP)
• Monitoring & observability
• Logging systems
• Security & secrets management
• Scripting (Bash / Python)
• SRE fundamentals
• Cost optimization & scaling

[Piyush @piyush784066]

Cloud Engineer Roadmap 2026-

Step 1: 🧠 Learn Linux & Networking Basics
Step 2: ☁️ Understand Cloud Fundamentals
Step 3: ⚙️ Pick a Provider (AWS, Azure, GCP)
Step 4: 🛠️ Work with Core Services (Compute, Storage, DB)
Step 5: 📦 Learn Containers (Docker)
Step 6: ☸️ Orchestration with Kubernetes
Step 7: 🧪 Monitor & Automate Infrastructure
Step 8: 🚀 Deploy Real Projects on Cloud
Step 9: 💼 Get Certified & Apply for Roles

🔒 Pro Tip: Always track cost & security!

[Shruti Codes @Shruti_0810]

FREE certifications, 💯 accepted in the industry:

1. Full Stack Web Development
https://t.co/rrJmPbEJs9

2. Computer Science
https://t.co/qDTatiYQBU

3. Software Engineering
https://t.co/OKKIVMUQEa

4. Python
https://t.co/XUScY1hgle

5. Python
https://t.co/L0Z5IarArk

6. JavaScript
https://t.co/GIiP0LXjRy

7. Data Analysis with Python
https://t.co/PUd2uO8TTn

8. Data Analytics
https://t.co/fYpHhoRHmb

9. AI
https://t.co/3fsoauU1Qh

10. DevOps with Kubernetes
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11. Fullstack Web Development
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12. Neo4j Certified Professional
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13. Neo4j Data Science Certification
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14. SEO, Marketing, Sales
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15. AI/ML, Data Science
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16. Ethical Hacking
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17. Networking
https://t.co/QhKUM0Gkqc

[DevopsCube @devopscube]

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For individual certifications,

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⏳ Hurry, this code expires in soon!

Don’t miss this chance to certify & level up!

#devops #kubernetes #ck

[freeCodeCamp.org @freeCodeCamp]

Learning how to work with AI in the cloud is an important skill for devs these days.

And in this 23 hour course, @andrewbrown teaches you all the fundamentals of Generative AI.

You'll learn about LLMs, AI assistants, prompt engineering, development tools, RAG, and more.

https://t.co/I4kZxGQnSc

[Akhilesh Mishra @livingdevops]

These Linux commands helped me most in last 13 years of IT career

Daily stuff:
• ps aux | grep {process} - Find that sneaky process
• lsof -i :{port} - Who's hogging that port?
• df -h - The classic "we're out of space" checker
• netstat -tulpn - Network connection detective
• kubectl get pods | grep -i error - K8s trouble finder

Log related commands:
• tail -f /var/log/* - Real-time log watcher
• journalctl -fu service-name - SystemD log stalker
• grep -r "error" . - The error hunter
• zcat access.log.gz | grep "500" - Compressed log ninja
• less +F - The better tail command

Container cli:
• docker ps --format '{{.Names}} {{.Status}}' - Clean status check
• docker stats --no-stream - Quick resource check
• crictl logs {container} - Raw container stories
• docker exec -it - The container backdoor
• podman top - Process peek inside containers

System Detectives:
• htop - System resource storyteller
• iostat -xz 1 - Disk performance poet
• free -h - Memory mystery solver
• vmstat 1 - System vital signs
• dmesg -T | tail - Kernel's recent gossip

Network stuff:
• curl -v - HTTP conversation debugger
• dig +short - Quick DNS lookup
• ss -tunlp - Socket statistics simplified
• iptables -L - Firewall rule reader
• traceroute - Path finder

File and stuff:
• find . -name "*.yaml" -type f - YAML hunter
• rsync -avz - Better file copier
• tar -xvf - The unzipper (yes, we all google this)
• ln -s - Symlink wizard
• chmod +x - Make it executable

Performance:
• strace -p {pid} - System call spy
• tcpdump -i any - Network packet sniffer
• sar -n DEV 1 - Network stats watch
• uptime - Load average at a glance
• top -c - Classic process viewer

Git Essentials:
• git log --oneline - History simplified
• git reset --hard HEAD^ - The "oops" eraser
• git stash - The work hider
• git diff --cached - What's staged?
• git blame - The "who did this?" resolver

Quick Fixes:
• sudo !! - Run last command with sudo
• ctrl+r - Command history search
• history | grep - Command time machine
• alias - Command shortcut maker
• watch - Command repeater