Daley Nyae

Ad Astra🦿

[sdiv @sdiv172632]

Contributing to Kubernetes was the highest ROI thing I did in college.

It came up in almost every interview I gave afterward.

almost no one asked me about my projects,

Most talked about the PRs and what it was like contributing to a codebase used by thousands of companies.

[Jahir Sheikh @jahirsheikh8]

Go + Gin → Backend Engineer
Go + Fiber → API Engineer
Go + Echo → Web Services Engineer

Go + GORM → Database Engineer
Go + sqlc → Data Access Engineer

Go + gRPC → Distributed Systems Engineer
Go + Kafka → Event-Driven Systems Engineer
Go + NATS → Realtime Systems Engineer

Go + Docker → Cloud Engineer
Go + Kubernetes → Platform Engineer
Go + Terraform → Infrastructure Engineer

Go + WebSockets → Realtime Application Engineer
Go + Temporal → Workflow Systems Engineer

Go + Cobra → CLI Developer
Go + Bubble Tea → Terminal UI Engineer

Go + Ebiten → Game Developer
Go + WASM → Web Performance Engineer

Go + TinyGo → Embedded Systems Engineer
Go + eBPF → Systems Engineer

one language…multiple six-figure engineering paths 🫡

[avrl ☘ @avrldotdev]

Step-1: Learn Go
Step-2: Master structs, interfaces & pointers
Step-3: Learn goroutines & channels
Step-4: Build an HTTP server with std-lib
Step-5: Read the Go runtime & standard library source. Embrace humility
Step-6: Build a production-grade backend (REST/gRPC, DB, caching, etc)
Step-7: Make it load-bearing
Step-8: Learn profiling & optimization (pprof, trace, benchmarks)
Step-9: deploy with Docker (& K8s)
Step-10: Ship it

[Puneet Patwari @system_monarch]

Senior backend interview in 2026.

How many of these can you explain clearly:

Event sourcing
Saga pattern
Bulkhead isolation
Token bucket vs leaky bucket
Consistent hashing
Write-ahead logging
Backpressure
Tombstone records
Bloom filters
Vector clocks
Gossip protocol
Idempotency keys
Read-your-writes consistency

If it's less than 8, you're not ready.

[Shruti @heyshrutimishra]

Elon just created 4,400 millionaires in a single day.

400 of them are now worth over $100 million.

These aren't VCs. They're SpaceX employees, and the list includes welders, technicians, and cafeteria staff, because for two decades the company paid every level of the workforce in stock instead of higher salaries.

Juan Hernandez immigrated from Mexico and took a $28 an hour contractor welding job in 2015. He says he didn't even know what SpaceX was. The company gave him a $10,000 equity grant and let him buy more shares through payroll deductions. That stake is now worth $880,000.

Trevor Hise's parents wanted him to take a stable job at General Electric. He picked SpaceX instead, stayed 12 years, and accumulated over 100,000 shares. At the $135 listing price that's $13.5 million. He's 37 and semiretired. His words: "The magnitude of this has been ridiculous."

The most telling detail came before the listing. Over 100 employees quietly banded together and negotiated a group wealth management deal covering up to $5 billion, because none of them had ever needed a wealth manager before.

Software IPOs have minted millionaires for 30 years. This is the first one where the money went to the factory floor.

[Elon Musk @elonmusk]

@iam_smx *trillioniare

[Puneet Patwari @system_monarch]

I've been a backend Engineer for 12+ years. Today, I'm a Principal Engineer at Atlassian.

I've designed systems that handle millions of requests. Sat on both sides of system design interviews.

Reviewed more architecture docs than I can count.

Starting today, I'm breaking down the fundamentals of scaling for the next 25 days.

If you're learning system design bookmark this thread, you're going to get a lot of learning from this.

[Branko @brankopetric00]

Your Docker image is 1.2GB and takes 4 minutes to build.

It should be 80MB and build in 20 seconds.

Here's how to fix it:

[Ritesh Roushan @devXritesh]

Go Roadmap: From Zero to Production (2026)

Most people learn Go the wrong way.

They watch endless tutorials but never reach production level.

Here’s the exact path I recommend:

Phase 1: Fundamentals (2 weeks)
Syntax, slices, structs, pointers, error handling

Phase 2: Core Concepts (3 weeks)
Interfaces, methods, testing, benchmarking

Phase 3: Concurrency (The Real Go)
Goroutines, channels, context, worker pools

Phase 4: Real Projects
REST API, CLI tools, background workers

Phase 5: Production Ready
Observability, graceful shutdown, Docker, CI/CD, clean architecture

Phase 6: Advanced
gRPC, distributed systems, performance tuning

Stop watching tutorials after the basics.

Start building real projects early.

This is how you actually become a production-grade Go developer.

Save this roadmap.

Which phase are you currently in?

Drop it below 👇

[avrl ☘ @avrldotdev]

Day 5 of learning Go after office hours.

Started with implementing Raft algo & project design is:

N number of nodes (Go servers) inside a K8s StatefulSet with a gateway service deployed separately routing requests from the clients to the leader of that cluster.

Gateway service can ping the current leader but if it changed, the node will respond with the new leaders address & the service will send a new req to the new leader. (You can loosely say its acting like a reverse proxy. We can also route the req from the follower internally to the new leader but I want to keep that limited to Gateway)

Each node will have its own persistence (sql DB) & a log file (for recording ops from client).

It's a fairly simple setup & I aim to learn some DevOps too with it projects on orchestration & deployments.

(Design diagram in comments)

[Daley Nyae @_dnyae]

@ntvkenya Broad daylight theft

[Daley Nyae @_dnyae]

Handwritten test cases for AI generated code are very essential

[Daley Nyae @_dnyae]

@Bill_Valar Does he have a prototype to showcase his innovation?

[Daley Nyae @_dnyae]

@IamAroke :=

[Ashutosh Maheshwari @asmah2107]

Backend Engineering is the hidden engine of scalable AI.

If you are an ML Engineer, Go deeper:

> gRPC & Protobufs (Low latency payloads)
> AsyncIO & Event Loops (Non-blocking concurrency)
> Connection Pooling (DB efficiency)
> Kafka & CDC (Real-time data ingestion)
> Backpressure Handling (Surviving inference bursts)
> Redis Pipelining (Batching feature fetch)
> Vector Indexing (HNSW/IVF in Qdrant)
> Graph Traversal (Cypher in Memgraph)
> Semantic Caching (Saving GPU compute)
> Distributed Locking (Race condition safety)
> Rate Limiting (Token buckets for LLMs)
> Idempotency (Safe retries)
> Database Sharding (Horizontally scaling state)
> OpenTelemetry (Tracing request lifecycles)

Architecture > Algorithms.

[Aliaksandr Valialkin @valyala]

This is a foundational publication which taught me how to optimize code for speed on modern computers. CPUs are bottlenecked by slow memory access most of the time. Optimize the code for memory access and get >10x performance improvements.

I've read this publication ~19 years ago at https://t.co/oT6plLunJu - https://t.co/TaAW7GRdre

[John Crickett @johncrickett]

This week I went back too 100% writing my code by hand.

It was the most productive path.

[avrl ☘ @avrldotdev]

10 backend projects that teach you scalability:

0. Notification system
1. Video processing queue
2. Search autocomplete
3. Real-time leaderboard
4. Payment retry engine
5. Email delivery service
6. Analytics event pipeline
7. Collaborative text editor
8. Distributed job runner
9. Social media feed

[Daley Nyae @_dnyae]

@karthikponna19 Go

[Daley Nyae @_dnyae]

@virusi_bad 🤣🤣