LOAD BALANCING: Day 1/25
Your load balancer is lying to you.
It says traffic is "balanced." What it really means is: requests are being distributed. Whether they're distributed well is a completely different question.
I've seen a system with 4 servers where Server 3 was at 95% CPU while Server 1 sat at 12%. The load balancer said everything was fine.
A load balancer doesn't know what's happening inside your servers. It doesn't know one request takes 2ms and the next takes 12 seconds.
Your choice of algorithm, layer, and health check strategy is the difference between actual balance and the illusion of it.
Let me break it down. 🧵Your load balancer is lying to you.
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Composite primary keys = uniqueness through combination. Use them when one column isn’t enough to identify a row, like linking tables (student_id + course_id).
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WebSockets keep connections open, consume resources, and add complexity. overkill for simple requests, harder to scale, cache, secure, and debug.
HTTP is lightweight and stateless. WebSockets shine only when truly need real-time, persistent connections.
Cold starts, execution time caps, vendor lockin, and cost at scale can bite. Long running jobs, heavy compute, low-latency apps, or full control needs still favor servers.
This is the difference between a demo and production code.
How do you handle cache fallbacks?
Stack I used:
- Node.js
- Redis (@upstash )
- Postgres
- Drizzle ORM
#backend#redis#nodejs
Built a leaderboard with Redis Sorted Sets today ⚡
But the important part wasn’t Redis.
It was the fallback strategy.
If Redis cache misses:
- fetch from DB
- rebuild rankings
- seed Redis again
So the system never breaks.
Fast when cached.
Reliable when not.
@sadkatwt It’s not about the language, it’s about the nature of tasks, distributed systems, load balancing, caching, and infrastructure.
Plenty of massive platforms use Node.js successfully, the bottleneck is design, not Node
@sadkatwt It’s not about the language, it’s about the nature of tasks, distributed systems, load balancing, caching, and infrastructure.
Plenty of massive platforms use Node.js successfully, the bottleneck is design, not Node