Prithwi Kumar

Fullstack web developer

[Prithwi Kumar @PrithwiSingh_]

Starting to build in public 🚀

I'll share my:
→ Projects
→ Things I'm learning
→ Bugs & lessons
Learning by building, breaking, and fixing things.

If you're building too, let's connect 🤝
GitHub: https://t.co/7N3LvRreZv

[Param @ParamSiddh]

If you are preparing for System Design Interviews,

This one is simply THE BEST. Get everything at one place.

GitHub: https://t.co/OES2s9dJCZ

[Prithwi Kumar @PrithwiSingh_]

Build in Public...

Today's i build Autocomplete search-bar like googled search suggestion.

Here is the Code :- https://t.co/oH0Bgzq4cl

#buildinpublic #public #searchbar

[Nandkishor @devops_nk]

DevOps looks easy until the interviewer goes DEEP.

- You can run Docker.
- You can deploy to Kubernetes.
- You can build CI/CD pipelines.

But then the interviewer asks:

“What happens internally?”

Here are 20 DevOps interview questions that test whether you actually understand what’s happening under the hood:

1. How does Kubernetes decide which node to schedule a Pod on?
2. What happens internally when you run `kubectl apply`?
3. How does Kubernetes Service Discovery work?
4. What is the difference between readiness and liveness probes internally?
5. How does HPA make scaling decisions?
6. What happens internally when you run `docker run`?
7. How does Docker layer caching work?
8. How does Terraform’s dependency graph (DAG) work internally?
9. How does Terraform handle state locking and consistency?
10. What happens internally in a CI/CD pipeline from commit → deploy?
11. How does a pipeline handle parallel jobs and dependencies?
12. How does an AWS Load Balancer route traffic?
13. What happens internally when you hit a CloudFront URL?
14. How does DNS resolution work step by step?
15. How do Git merge and rebase differ internally?
16. How does Kubernetes handle Pod failures and self-healing?
17. What happens during a rolling deployment in Kubernetes?
18. How do logs, metrics, and traces work together in observability?
19. Your production system goes down. How do you approach troubleshooting?
20. What are the most common production mistakes in DevOps setups?

Knowing the commands makes you a user.Understanding what happens underneath makes you an engineer.

Save this for your next DevOps interview.

[Prithwi Kumar @PrithwiSingh_]

@noorsababuild Thank You🥰

[Prithwi Kumar @PrithwiSingh_]

🚀 Introducing Mentis 🧠

A personal AI-powered second brain to help you save, understand, and revisit the things you find online.
Save articles, videos, tweets & documents.

🔗Live :- https://t.co/BoLqrMnHpp
💻 Github :- https://t.co/FSEUxc4TkP

Would love your feedback 🙌

[Prithwi Kumar @PrithwiSingh_]

Starting to build in public 🚀

I'll share my:
→ Projects
→ Things I'm learning
→ Bugs & lessons
Learning by building, breaking, and fixing things.

If you're building too, let's connect 🤝
GitHub: https://t.co/7N3LvRreZv

[SCR @SCR01111]

21 SYSTEM DESIGN RESOURCES TO LEARN 📌

1. System Design Concepts 101
https://t.co/5HZbs1A1wJ

2. Microservices Patterns
https://t.co/JLAVo7enu5

3. How DNS Works
https://t.co/tjXXjLL2GP

4. How JWT Works
https://t.co/81HanLJe3l

5. How Does HTTPS Work
https://t.co/pkXlaUTMJe

6. API Design Best Practices
https://t.co/MQLgMvuiUC

7. Redis Use Cases
https://t.co/F7reezVMmZ

8. Distributed Systems 101
https://t.co/Tc1wVOF3i8

9. How Message Queues Work
https://t.co/sff9LLhoaZ

10. How WebSockets Work
https://t.co/pxXHb1xRTd

11. Frontend System Design Concepts
https://t.co/3WQLh1DLn0

12. How Databases Keep Passwords Securely
https://t.co/EOctkdElWx

13. Modular Monolith Architecture
https://t.co/p4BGnBIow6

14. Saga Design Pattern
https://t.co/UImzkMUetV

15. Microservices Lessons From Netflix
https://t.co/QeQwphNIiy

16. How Consistent Hashing Works
https://t.co/whEO51kZl4

17. How Idempotent API Works
https://t.co/gJwYjK3Vw1

18. How RPC Actually Works
https://t.co/q6jOieFCC7

19. API Versioning: A Deep Dive
https://t.co/YSJqSbFZaM

20. How Bloom Filters Work
https://t.co/6TZS5PqAnR

21. How Service Discovery Works
https://t.co/IFTlHT57Tg

[Tech Fusionist | Kushal Gangil @techyoutbe]

System Design — Quick Roadmap 🌲

├── 01. Foundations
│ ├── Client-Server
│ ├── Monolith vs Microservices
│ ├── Scaling
│ └── CAP Theorem
│
├── 02. Networking
│ ├── DNS
│ ├── HTTP/HTTPS
│ ├── TCP/UDP
│ └── Load Balancers
│
├── 03. APIs
│ ├── REST
│ ├── GraphQL
│ ├── gRPC
│ └── API Gateway
│
├── 04. Databases
│ ├── SQL vs NoSQL
│ ├── Indexing
│ ├── Replication
│ └── Sharding
│
├── 05. Caching
│ ├── Redis
│ ├── CDN
│ ├── Cache Strategies
│ └── Eviction Policies
│
├── 06. Messaging
│ ├── Kafka
│ ├── RabbitMQ
│ ├── Queues
│ └── Event-Driven Systems
│
├── 07. Reliability
│ ├── High Availability
│ ├── Fault Tolerance
│ ├── Retries
│ └── Circuit Breakers
│
├── 08. Observability
│ ├── Logs
│ ├── Metrics
│ ├── Tracing
│ └── SLA / SLO / SLI
│
├── 09. Deployment
│ ├── Docker
│ ├── Kubernetes
│ ├── CI/CD
│ └── Blue-Green / Canary
│
└── 10. Advanced
├── Serverless
├── Edge Computing
├── Distributed Systems
└── AI-Native Systems

Learn to design systems, not just write code.

[PA13L0 @Fluyeporlaweb]

Ex ingeniero de Google te enseña como crear agentes de IA que se automejoran solos.

Simplemente puedes transcribir este vídeo con grok y pasarselo a tu hermes para que aprenda jiu-jitsu.

[Kashaf @noor36758]

API Technologies Ranked by Learning Curve

🟢 REST API — Easy
🟢 GraphQL — Easy
🟢 Webhooks — Easy
🟢 Server Sent Events — Easy

🔵 WebSockets — Moderate
🔵 gRPC — Moderate
🔵 tRPC — Moderate
🔵 API Gateways — Moderate

🟠 Message Queues — Hard
🟠 Kafka — Hard
🟠 Event Driven Architecture — Hard
🟠 Microservices — Hard

🔴 Distributed Systems — Very Hard
🔴 Eventual Consistency — Very Hard
🔴 Consensus Algorithms — Very Hard
🔴 Distributed Transactions — Very Hard

Which one took you the longest to understand 👀

[Aryan Mittal @aryan_mittal007]

you JUST need to know all these to be a good backend engineer

[Sakshi @Sakshi50038]

Who's gonna tell vibe coders about...

> Rate Limiting
> Caching
> Load Balancing
> Reverse Proxies
> API Gateways
> CI/CD
> Docker
> Kubernetes
> Service Discovery
> Circuit Breakers
> Timeouts
> Retries
> Exponential Backoff
> Idempotency
> Message Queues
> Pub/Sub
> Event-Driven Architecture
> Distributed Transactions
> Saga Pattern
> Dead Letter Queues
> Cron Jobs
> WebSockets
> Long Polling
> Server-Sent Events
> Database Indexing
> Query Optimization
> N+1 Queries
> Connection Pooling
> Read Replicas
> Sharding
> Partitioning
> Replication
> Leader Election
> CAP Theorem
> Eventual Consistency
> Optimistic Locking
> Pessimistic Locking
> Distributed Locks
> Race Conditions
> Deadlocks
> Memory Leaks
> Garbage Collection
> Thread Safety
> Backpressure
> Autoscaling
> Horizontal Scaling
> Vertical Scaling
> CDN
> Edge Caching
> Cache Invalidation
> Feature Flags
> Blue-Green Deployments
> Canary Releases
> Rolling Deployments
> Rollbacks
> Health Checks
> Liveness & Readiness Probes
> Monitoring
> Logging
> Distributed Tracing
> Metrics
> Alerting
> SLOs
> SLIs
> Error Budgets
> Observability
> Secrets Management
> IAM
> OAuth
> JWT Rotation
> TLS
> Encryption at Rest
> Encryption in Transit
> WAF
> DDoS Protection
> CORS
> CSRF
> SQL Injection
> XSS
> SSRF
> Database Migrations
> Schema Versioning
> Disaster Recovery
> Backups
> Failover
> Multi-Region Deployments
> Chaos Engineering
> Cost Optimization
> Cold Starts
> Serverless Limits
> Latency
> Throughput
> P99 Latency
> Tail Latency
> Network Partitions
> Clock Skew
> DNS
> TCP vs UDP
> HTTP/2 & HTTP/3
> gRPC
> Webhooks
> API Versioning
> Semantic Versioning
> Infrastructure as Code
> Terraform
> Helm Charts
> Build Caching
> Dependency Hell
> Production Incidents
> On-call
> Postmortems

...until the app gets its first million users.

[Dan Kornas @DanKornas]

🔗 GitHub: https://t.co/EXvJpY1IBG
---
✉️ If you’re into AI, ML, agents, and building real systems, join my newsletter (it’s free): https://t.co/zpXbSNVTis

[SCR @SCR01111]

Goldmine for AI Engineers! 📌

If you're learning AI, ML, LLMs, or AI agents, don't waste hours jumping between random tutorials.

These are 10 repositories I'd actually keep bookmarked - from Python fundamentals to ML, LLMs, agents, and production AI.

1. Python - 100 Days

jackfrued/Python-100-Days

A 100-day Python learning path covering fundamentals, data analysis, web development, and more.

GitHub:
https://t.co/NMCNWjp4GT

2. Generative AI for Beginners

microsoft/generative-ai-for-beginners

A practical introduction to building Generative AI applications.

Covers:

• LLM fundamentals
• Prompt engineering
• RAG
• AI agents
• Fine-tuning
• AI application development

GitHub:
https://t.co/5QXAC1rsUZ

3. LLMs From Scratch

rasbt/LLMs-from-scratch

Want to understand what's actually happening inside an LLM?

Build one step by step.

Covers:

• Tokenization
• Embeddings
• Attention
• Transformers
• Training
• Fine-tuning

GitHub:
https://t.co/iEtPYVPpXV

4. Machine Learning for Beginners

microsoft/ML-For-Beginners

A structured 12-week, 26-lesson curriculum covering classical machine learning.

A good starting point if you want ML fundamentals before jumping into LLMs.

GitHub:
https://t.co/sLijf46NKB

5. OpenAI Cookbook

openai/openai-cookbook

A collection of practical examples and guides for building applications with OpenAI models.

Useful when you want to move from:

Learning → Building

GitHub:
https://t.co/H3ZiMmpMAq

6. Stable Diffusion

CompVis/stable-diffusion

Interested in generative image models?

This repository contains the original Stable Diffusion implementation and research code.

GitHub:
https://t.co/DFwSLqOlyn

7. AI Agents for Beginners

microsoft/ai-agents-for-beginners

A practical course for understanding and building AI agents.

Covers:

• Agentic AI
• RAG
• Agent frameworks
• Tool use
• Multi-agent systems

GitHub:
https://t.co/zNeYlZRQqa

8. AI for Beginners

microsoft/AI-For-Beginners

A structured 12-week, 24-lesson introduction to AI.

Covers:

• Neural networks
• Computer vision
• NLP
• Deep learning
• Classical AI

GitHub:
https://t.co/V7Oilwt7nA

9. LLM App

pathwaycom/llm-app

Focused on building practical LLM applications.

Explore:

• RAG
• AI pipelines
• Enterprise search
• Real-time data
• Vector search

GitHub:
https://t.co/2FdeXjZfQ8

10. Segment Anything

facebookresearch/segment-anything

A foundation model for promptable image segmentation.

Worth exploring if you're interested in computer vision and multimodal AI.

GitHub:
https://t.co/yCSrZH8b5w

Don't bookmark all 10 and forget about them.

Pick based on where you are:

Python → Python-100-Days

ML → ML-For-Beginners

AI Fundamentals → AI-For-Beginners

LLMs → LLMs-from-scratch

Generative AI → Generative-AI-for-Beginners

Agents → AI-Agents-for-Beginners

Building → OpenAI Cookbook / LLM App

Computer Vision → Segment Anything

Pick one.

Build something.

Then move to the next.

[Harshit Khosla @Harry_The_Nerd]

Currently, this repo contains all 53 of the articles I've posted (HLD, LLD, Backend, etc.)... I want to turn it into a learning haven for software engineers.

https://t.co/PxDvVqmfx6

[Puneet Patwari @system_monarch]

I'm a Principal engineer & I passed system design rounds of Amazon, Atlassian, Walmart, Saleforce, and Deliveroo.

Trust me, learning system is not hard. Start from these fundamental concepts:

1) Load Balancing: https://t.co/3jKCLiI6vl

2) CDN: https://t.co/dxzCmm9gAf

3) Caching: https://t.co/pRgn0FTPp2

4) Cache Invalidation: https://t.co/QrfRjJ57gd

5) Rate Limiting: https://t.co/LE5ECM2tGt

6) API Gateway: https://t.co/DgU8cBDUVr

7) CAP Theorem: https://t.co/a8WydnAIxd

8) Sharding: https://t.co/XQLU6eDriD

9) Replication: https://t.co/KuDkFH0fjx

10) Partitioning: https://t.co/3WXKeZLbLa

11) Queues: https://t.co/JchEoCcFmF

12) Microservices: https://t.co/aAQfM6AWMq

13) Microservices Vs Monoliths: https://t.co/bTaIIWkPU3

14) Fault Tolerance: https://t.co/qXNBoyOqYT

15) Database Scaling: https://t.co/D2lvPm1wkB

16) Service Discovery: https://t.co/z2DpwbJBVI

17) Consistency models: https://t.co/K2r3nMcCQu

18) Eventual Consistency: https://t.co/SWiz4ckIKR

19) Distributed Transactions: https://t.co/xqL7BTJxXn

20) Leader Election: https://t.co/ApNaYSnSFj

21) Horizontal vs Vertical Scaling: https://t.co/IFuEmzMfob

22) Back of the Envelope Estimation: https://t.co/7ntEmtVggQ

23) Idempotency, Data Latency & Finale: https://t.co/fNArLx4MrW

Let me know what you'd like me to cover, would love to help :)

[Prithwi Kumar @PrithwiSingh_]

@spiderboii24 Ctrl+ z

[Kingsama @Kingsama_12]

POV you are in the early 2000's, here is my submission for @ChaiCodeHQ cohort, I thought the deadline was today and ended up submitting T-T, it still needs a lot of polish, it also has some songs for @piyushgarg_dev 👀, everyone pls try it out

[Prithwi Kumar @PrithwiSingh_]

after long time we again start revise backend concept and today's i learn pagination & regex