GolangStepByStep
From intern to principal engineer — one step at a time.
Master Go programming, system design, distributed systems, and architecture through carefully crafted lessons. Each step builds on the last, turning concepts into engineering instincts.
Intern
Go FundamentalsBasics
Control & Loops
Functions
Functions
Define, call, and return values from functions
Multiple Return Values
Return multiple values from a function — the Go idiom for results + errors
Variadic Functions
Accept an arbitrary number of arguments with the ... syntax
Closures
Functions that capture variables from their surrounding scope
Defer
Schedule cleanup code to run when a function exits
Panic & Recover
Handle unrecoverable errors and recover from panics safely
Data Structures
Pointers
Understand memory addresses, indirection, and when to pass by pointer
Arrays & Slices
Fixed arrays and dynamic slices — Go's most-used collection type
Maps
Key-value lookups with hash maps — create, read, delete, iterate
Strings & Runes
Go strings are UTF-8 byte slices — runes represent Unicode code points
Type System
Structs
Group related data into a named struct — Go's primary data type
Methods
Attach functions to types with value and pointer receivers
Interfaces
Define behaviour with interfaces — Go's key abstraction mechanism
Type Assertions
Extract concrete values from interfaces with type assertions and switches
Concurrency Intro
Software Engineer
Go in DepthAdvanced Go
Advanced Go: Real-world
Channel Patterns
Select, timeouts, cancellation — real-world channel idioms
Concurrency Patterns
Worker pools, fan-in, fan-out — scaling concurrent workloads
Race Conditions & -race Debugging
Detect and fix data races with Go's -race detector
Sync Primitives
Mutex, RWMutex, atomic, Once, Cond — low-level synchronization
Context in Production
Deadlines, request-scoped values, cancellation — do's and don'ts
Error Strategy
Wrapping, sentinel errors, typed errors, boundary handling
API Design in Go
Package boundaries, public surface minimization, clean APIs
HTTP Servers
Middleware, request lifecycle, graceful shutdown
HTTP Clients
Timeouts, retries, connection pooling, transport tuning
Structured Logging
Log levels, correlation IDs, JSON logs, observability
Observability Advanced
Metrics, tracing, OpenTelemetry concepts, production monitoring
Performance Profiling
pprof CPU/heap, benchmarking, allocation hunting, optimization
Memory Model Basics
Escape analysis, stack vs heap, memory symptoms
Generics
Constraints, type parameters, practical use cases in Go 1.18+
Data Access
SQL patterns, transactions, connection pools, migrations
Caching Strategies
In-memory vs distributed, invalidation patterns, design trade-offs
Rate Limiting & Backpressure
Token buckets, leaky buckets, circuit breakers, resilience patterns
Background Jobs
Job queues, idempotency, retries, poison messages, durability
Testing Advanced
Mocks/fakes, httptest, golden tests, fuzz testing, benchmarks
Dependency Injection
DI patterns, testability, avoiding over-frameworking
Secure Coding
Input validation, secrets, crypto pitfalls, SSRF, common vulnerabilities
Go Build & Deploy
Multi-stage Docker, static builds, distroless, optimization
Versioning & Compatibility
Modules, semantic versioning, import versioning, deprecations
Libraries vs Services
API stability, documentation conventions, design contrasts
Sr. Software Engineer
System DesignFoundations
System Design Fundamentals
Load balancers, CDNs, DNS, reverse proxies — the building blocks of every production system
Networking for Backend Engineers
TCP/UDP, HTTP/2, HTTP/3, TLS handshakes, DNS resolution, latency budgets
API Design
REST vs gRPC vs GraphQL — versioning, pagination, idempotency, backward compatibility
Data Systems
Database Design & Modeling
Relational modeling, normalization vs denormalization, indexing strategies, schema evolution
SQL vs NoSQL Trade-offs
When to use what — consistency guarantees, query patterns, CAP implications, migration paths
Caching at System Scale
Multi-tier caching (local, Redis, CDN), invalidation strategies, stampede protection, consistency
Integration Patterns
Message Queues & Event-Driven Design
Kafka, NATS, RabbitMQ — pub/sub, exactly-once semantics, dead letter queues, event sourcing
Service-to-Service Communication
gRPC in Go, service discovery, retries, timeouts, circuit breakers, load balancing strategies
Authentication & Authorization
OAuth2, JWT, RBAC, API keys, session management — securing Go services end-to-end
Production Readiness
Reliability & SLOs
SLIs, SLOs, SLAs, error budgets, incident response, on-call best practices, chaos engineering
CI/CD & Deployment Strategies
Blue-green, canary, feature flags, rollbacks, pipeline design for Go services
Design Patterns in Go
Factory, strategy, options pattern, decorator, middleware chains — idiomatic Go design
Staff Software Engineer
Scale & ReliabilityDistributed Systems
Distributed Systems Fundamentals
CAP theorem, consistency models, consensus algorithms (Raft, Paxos), vector clocks, leader election
Distributed Transactions
Two-phase commit, saga patterns, eventual consistency, the outbox pattern, idempotency at scale
Event Sourcing & CQRS
Event stores, projections, command/query separation, replaying history, audit trails
Scaling Deep Dives
Database Scaling
Sharding strategies, read replicas, connection pooling at scale, distributed SQL (CockroachDB, Spanner)
Horizontal Scaling Patterns
Consistent hashing, partitioning strategies, stateless vs stateful services, auto-scaling triggers
Data Pipelines & Stream Processing
Kafka streams, batch vs stream, backpressure handling, exactly-once processing, dead letter queues
Observability & Reliability
Observability at Scale
Distributed tracing (OpenTelemetry), metrics pipelines, log aggregation, alerting strategies, dashboarding
Chaos Engineering & Resilience
Failure injection, game days, fault domains, blast radius reduction, graceful degradation
Incident Management & Postmortems
On-call excellence, runbooks, blameless postmortems, escalation frameworks, SLO burn-rate alerts
Infrastructure & Operations
Kubernetes & Container Orchestration
Pod design patterns, service mesh, autoscaling, resource management, rolling deployments
Infrastructure as Code
Terraform patterns, GitOps workflows, immutable infrastructure, drift detection, environment parity
Multi-Region & Global Systems
Active-active architecture, failover strategies, data replication across regions, latency-aware routing
Principal Engineer
Architecture & LeadershipArchitectural Thinking
Architecture Decision Records
ADRs, documenting trade-offs, building institutional memory, decision frameworks that outlast you
Monolith to Microservices Migration
When to decompose, strangler fig pattern, domain boundaries, data migration strategies, rollback plans
Event-Driven Architecture
Event buses, choreography vs orchestration, eventual consistency at org scale, schema registries
Domain-Driven Design
Bounded contexts, aggregates, ubiquitous language, strategic vs tactical DDD, context mapping
Platform & Developer Experience
Platform Engineering
Internal developer platforms, golden paths, self-service infrastructure, reducing cognitive load for teams
API Strategy & Governance
Org-wide API standards, API gateways, versioning policies, contract testing, API-first culture
Developer Productivity
Build systems, CI/CD at org scale, developer experience metrics, reducing inner-loop friction
Technical Strategy
Tech Debt Strategy
Quantifying tech debt, prioritization frameworks, debt budgets, communicating debt to leadership
Build vs Buy Decisions
Evaluation frameworks, total cost of ownership, vendor lock-in, open source strategy, migration costs
Technology Radar & Adoption
Evaluating new technologies, RFC processes, controlled rollouts, managing technology sprawl
Reliability & Scale Strategy
Org-Wide Reliability Strategy
Reliability as a product, error budgets across teams, reliability reviews, production readiness checklists
Data Architecture at Scale
Data mesh, data lakes vs warehouses, governance, lineage, privacy-by-design, cross-team data contracts
Security Architecture
Threat modeling, zero-trust architecture, security reviews, compliance frameworks, secure SDLC
Engineering Leadership
Technical Vision & Roadmapping
Writing a technical vision document, aligning architecture with business goals, multi-year tech strategy
Cross-Team Technical Leadership
Influence without authority, design reviews, technical mentorship, building technical communities
Engineering Culture & Excellence
Code review culture, on-call fairness, knowledge sharing, postmortems that drive change, hiring for technical depth
The journey never ends...
Go → System Design → Scale → Architecture