Instagram story viewer> @dietcokecode> Posts

Diet code

@dietcokecode

33.4K

followers

3

following

2 Senior Software Engineers trying to make sense of their code

POSTS STORIES REELS TAGGED

Agar aapko system design, AI ya tech mein interest hai, toh ho sakta hai Diet Code aapke liye hi bana ho.

Ho sakta hai aap interviews ki preparation kar rahe ho, ya bas naye concepts seekhna pasand karte ho.

Diet Code humne isi liye shuru kiya tha.

Jo humein aata hai, use simple banakar aapke saath share karne ke liye.

Ek aisi community banane ke liye, jahaan aap bina hesitation ke sawaal poochh sako.

Humne hamesha koshish ki hai ki aapko practical, useful content mile, bina aapki feed ko unnecessary promotions se bhare.

Lekin reels ki ek limitation hai.

Hum concept samjha sakte hain, par aapki interview preparation mein exactly kahaan problem aa rahi hai, woh tabhi samajh aayega jab hum aapse directly baat karenge.

Isiliye ab hum Topmate par bhi available hain.

Agar system design interview questions approach karne mein dikkat hoti hai, DSA ya backend concepts mein doubts hain, ya mock interview ke baad honest feedback chahiye, toh hum one-on-one sessions mein aapke saath un problems par kaam kar sakte hain.

Apne experience se relevant resources aur practical guidance bhi share karenge, taaki aap apni preparation ko next level par le ja sako.

Sessions paid hain, lekin pricing affordable rakhi hai. College students ke liye special lower pricing bhi hai.

Students aur working professionals ke liye alag session options hain, taaki aap apni needs ke according choose kar sako.

Diet Code par learning toh chalti rahegi.

Ye bas ek opportunity hai aapse personally connect karne ki, aapki journey samajhne ki, aur saath grow karne ki.

Toh agar aapko system design, backend development, AI ya software engineering interviews mein help chahiye, Topmate ka link bio mein hai.

Apne questions lekar aaiye.

Milkar aapka next step figure out karte hain.

Aur comments mein batao — aapki preparation mein sabse badi challenge kya hai? by @dietcokecode

51

1

4 days ago

Cache penetration explained in simple terms. 🚀
Random IDs → cache miss → DB overload.

#systemdesign #backend #redis #softwareengineering #coding by @dietcokecode

15k

227

a month ago

Most people think Redis is the solution to database performance.

And it is… until your cache expires at the exact same time.

A tiny mistake in your TTL configuration can create millions of cache misses in a single second, overwhelming your database and taking production down.

This problem is called Cache Stampede, and the fix is surprisingly simple: TTL Jitter.

Sometimes preventing a production outage is as simple as adding a few seconds of randomness.

Would you like to see more real-world backend engineering concepts explained like this?

#Redis #SystemDesign #Backend #SoftwareEngineering #Java by @dietcokecode

21k

104

2 months ago

Kafka khud production mein problem nahi hai. Usko galat use karna hai.

Infinite retention, unnecessary partitions, giant topics, oversized messages aur ignored consumer lag — ye 5 mistakes tumhari Kafka pipeline ko silently break kar sakti hain.

Aur sabse dangerous part? Har baar CPU ya error logs mein kuch suspicious dikhe, zaroori nahi. Kabhi-kabhi problem tab tak dikhti hi nahi jab tak production impact na ho jaaye.

Is reel mein samjho 5 common Kafka anti-patterns, real-world scenarios aur unke practical fixes.

Agar tum Backend Developer ho, System Design ki preparation kar rahe ho, ya production mein Kafka use karte ho, toh save kar lo. Interview mein bhi kaam aayega.

Follow @DietCode for practical System Design, Backend Engineering and AI concepts.

#ApacheKafka #SystemDesign #BackendDevelopment #SoftwareEngineering #TechInterview by @dietcokecode

36

1

3 hours ago

Kafka interview mein sirf “Retry laga denge” bolna enough nahi hai.

Interviewer pooch sakta hai:
Event loss kaise prevent karoge?
Duplicate events se double payment kaise rokoge?
Bug fix ke baad poori event history replay kaise karoge?

Aur in teeno problems ka solution alag hai.

1. Event Loss — Producer + Broker Reliability

acks=all, min.insync.replicas aur idempotent producer.

2. Duplicate Events — Idempotent Consumer

Unique event ID, deduplication aur atomic database transactions.

3. Reprocessing — Deterministic Consumer

Same events, same final state. Aur replay ke time unnecessary side effects nahi.

Yaad rakho: Event loss, duplicate processing aur reprocessing ek hi problem nahi hain.

Agar tum Java Backend, Kafka ya System Design interviews ki preparation kar rahe ho, toh is concept ko save kar lo. Interview mein kaam aayega.

Follow @DietCode for practical System Design, Backend Engineering aur AI concepts, explained simply.

#ApacheKafka #SystemDesign #BackendDevelopment #JavaDeveloper #SoftwareEngineering by @dietcokecode

449

0

a day ago

Cron job lagana easy hai. But what if your system needs to execute 10,000 jobs per second? 🚀

In this 2-part system design series, we build a distributed job scheduler from scratch using Kafka, Redis, database indexing, retries, heartbeats, and idempotency.

Learn how to handle worker crashes, prevent missed jobs, retry failures, and design for at-least-once execution.

Save this for your next System Design interview! 💻

Comment below: Which system should we design next?

#systemdesign #softwareengineering #kafka #backenddevelopment #interviewprep by @dietcokecode

404

3

2 days ago

Production mein order save ho gaya, lekin Kafka event kabhi publish hi nahi hua. Result? Order lost nahi hua database mein, par warehouse ko uske baare mein pata hi nahi chala. 🚨

Ye hai Dual Write Problem — aur backend system design interviews mein ek important concept.

Is reel mein samjho:
🔹 Dual Write Problem kya hai?
🔹 MySQL aur Kafka ke beech consistency kaise break hoti hai?
🔹 @Transactional Kafka ko guarantee kyun nahi karta?
🔹 Transactional Outbox Pattern is problem ko kaise solve karta hai?
🔹 Debezium polling se better approach kyun ho sakta hai?

Agar aap Java, Spring Boot, Kafka ya System Design seekh rahe ho, toh ye concept production systems aur interviews dono ke liye important hai.

Part 2 mein samjhenge Debezium aur Change Data Capture (CDC) — jisse database ke logs read karke events publish kiye ja sakte hain.

Follow @dietcokecode for practical system design, backend engineering aur AI concepts, simple language mein.

Comment “PART 2” if you want the Debezium explanation! 👇

#SystemDesign #ApacheKafka #SpringBoot #BackendDevelopment #SoftwareEngineering by @dietcokecode

387

8

3 days ago

10 lakh users ko ek saath notification bhejni hai. System crash kiye bina. 🚀

Simple loop laga ke API se notifications bhejna? Production mein ye approach fail ho sakti hai.

Real-world systems mein kaam aati hai Queue + Workers + Parallel Processing ki power. 🔥

Is reel mein samjho:
✅ Synchronous processing kyun fail hoti hai
✅ Message Queue traffic ko kaise handle karti hai
✅ Workers ko independently scale kaise karte hain
✅ Ek notification provider down ho toh baaki services kaise chalti rehti hain

Aur interview ka golden rule? Pehle requirements, phir architecture, aur sabse last mein technology.

Part 2 mein cover karenge Retries, Dead Letter Queues aur Duplicate Notifications ko prevent karna.

💬 Comment karo: PART 2 agar iska next part chahiye!

Follow for more System Design & AI concepts, explained simply.

#SystemDesign #BackendDevelopment #SoftwareEngineering #ScalableSystems #TechInterviews by @dietcokecode

4k

27

5 days ago

Connection is not available.”

Production down hai, aur aapka solution hai pool size badha dena?

Bigger connection pools won’t fix connection leaks. They might just delay the crash.

In this video, we break down 3 real-world mistakes that can exhaust your HikariCP connection pool:

JDBC connections that never close
Slow API calls inside transactions
Error paths that don’t release resources properly

Learn how to use try-with-resources, handle async processing with Kafka or RabbitMQ, and monitor active and pending connections before production goes down.

Remember: Bigger pools don’t fix leaks. Better code does.

Follow for more practical Java, Spring Boot, System Design & production engineering lessons.

#Java #SpringBoot #SystemDesign #BackendDevelopment #SoftwareEngineering by @dietcokecode

294

2

6 days ago

Redis ki memory full ho jaaye, toh kya hoga?

Crash ya automatic key deletion? The answer is Eviction Policies.

Is video mein samjho:
🔹 Expiration vs Eviction
🔹 maxmemory & maxmemory-policy
🔹 LRU vs LFU — kab kya use karein?
🔹 noeviction aur Volatile policies
🔹 Redis LRU kaise kaam karta hai
🔹 Production debugging: INFO MEMORY, TTL & MEMORY USAGE

💡 Interview ke liye ek line yaad rakho:
Expiration is time-based. Eviction is memory-based.

Follow for more System Design, Backend Engineering & AI concepts in simple language.

#Redis #SystemDesign #BackendDevelopment #Java #TechInterview by @dietcokecode

620

5

8 days ago

1 crore Redis keys aur har key pe TTL…

Toh kya Redis 1 crore timers chala raha hai? ⏱️

Bilkul nahi.

Redis expiry ko timers ki tarah nahi, timestamps ki tarah track karta hai. Aur expired keys clean karne ke liye use karta hai:

• Lazy Expiration — key access hui, tab expiry check
• Active Expiration — background mein random keys sample karke cleanup

Lekin agar expired keys delete hone ke baad bhi Redis ki memory full ho toh?

Wahan aata hai ek aur important concept: Eviction.

Part 2 mein dekhenge Redis decide kaise karta hai ki memory full hone par kis key ko nikaalna hai.

Comment “PART 2” if you want the next one.

Follow for more System Design + Backend concepts in simple language.

#redis #systemdesign #backenddevelopment #softwareengineering #interviewprep by @dietcokecode

3k

17

9 days ago

Designing YouTube end to end — Part 4 🚀

Ab baat karte hain ek deceptively simple problem ki: 3 GB video upload kaise hoga?

Weak network, connection drop at 80%… kya poora video dobara upload karna padega?

Is part mein dekho:
→ Chunked & resumable uploads
→ Pre-signed URLs
→ Parallel uploads
→ Failed chunks ka retry
→ Transactional Outbox + Kafka
→ Incomplete uploads ka cleanup

Aur ye sirf upload nahi hai — interview mein failure scenarios handle karna bhi equally important hai.

Part 5 mein raw video ko watchable banayenge: transcoding + safety checks + processing pipeline.

Comment “PART 5” if you want the next part.

Follow for more System Design & AI concepts in simple language.

#SystemDesign #SystemDesignInterview #YouTubeArchitecture #BackendEngineering #SoftwareEngineering by @dietcokecode

82

1

11 days ago