Advanced Product & Infrastructure Engineering
Production engineers, backend specialists and cloud engineers who operate systems at scale.
Production-grade multi-service platform — Kubernetes-deployed, load-tested at 10k concurrent users.
Learning outcomes
Graduate this track able to work as:
Module timeline
18 modules across 6 phases. Tap any module to see its topics. P Practical H Hybrid T Theory
Advanced Backend Systems
8 weeks- Monolith vs microservices tradeoffs
- Service decomposition
- API gateway patterns
- BFF architecture (deep)
- Internal vs external APIs
- Backward compatibility
- Versioning strategies
- Timeout & retry design
- Circuit breakers
- Bulkheads
Upgrade from Track 1: you learned to build APIs — now learn why systems break at scale and how to architect against it.
- Sync vs async patterns
- Message queues (BullMQ)
- Job scheduling
- Dead letter queues
- Retry with exponential backoff
- Idempotency patterns
- Event ordering
- Fan-out systems
- Saga pattern basics
- Outbox pattern
Lab: Build a distributed notification system — email + SMS + push via queues, with retry, dead-letter handling and delivery-status tracking.
- Cache invalidation strategies
- Write-through / write-back / write-around
- Cache stampede prevention
- Distributed locking
- Token bucket algorithm
- Sliding window rate limiting
- Per-user vs per-IP limits
- Redis cluster patterns
Database Internals & Storage Engineering
8 weeks- B+ tree internals
- LSM tree internals
- WAL deep dive
- MVCC
- Query planner internals
- EXPLAIN ANALYZE
- Isolation levels deep dive
- Locking vs MVCC tradeoffs
- Storage engines compared
- Vacuum & bloat management
Upgrade from Track 1: you learned to write queries — now learn why a query is slow and how to fix it at the engine level.
- Index design strategies
- Partial indexes
- Composite indexes
- Index-only scans
- N+1 problem patterns
- Query rewriting
- Materialized views
- Connection pooling (PgBouncer)
- Slow-query detection & logging
- Primary-replica replication
- Logical vs physical replication
- Read replicas in practice
- Horizontal sharding strategies
- Shard key selection
- Cross-shard queries
- Distributed DBs (PlanetScale, CockroachDB)
- Vector databases (pgvector, Pinecone)
Lab: Take a slow multi-tenant query from Track 1’s HRMS, diagnose with EXPLAIN ANALYZE, redesign schema and indexes, and benchmark before/after.
Security & Cryptography Engineering
6 weeks- Cryptography foundations
- Symmetric encryption (AES)
- Asymmetric encryption (RSA, ECC)
- Diffie–Hellman key exchange
- ECDH
- Hash functions (SHA family)
- HMAC
- Digital signatures
- PKI & certificates
- TLS handshake internals
- HTTPS internals
- mTLS
- OWASP Top 10 in depth
- SQL injection patterns
- XSS & CSRF
- JWT attack vectors
- OAuth2 security edge cases
- Secrets management (HashiCorp Vault)
- API key rotation
- Input sanitization systems
- Dependency vulnerability scanning
- SAML deep dive
- OIDC flows
- Enterprise SSO
- SCIM provisioning
- Attribute-based access control (ABAC)
- Zero-trust principles
- Service-to-service auth
- mTLS for internal services
Phase project: Implement SAML SSO + SCIM on the HRMS. Add secrets rotation with Vault. Run OWASP ZAP against the APIs and fix all critical findings.
Messaging, Realtime & Search Infrastructure
6 weeks- Kafka architecture & internals
- Topics, partitions, offsets
- Consumer groups
- Producer acknowledgment modes
- Exactly-once semantics
- Kafka vs RabbitMQ vs BullMQ
- Event-streaming pipelines
- Schema registry
- Kafka Connect basics
Upgrade from Track 1: BullMQ handled simple job queues — Kafka handles event streaming at scale where ordering, replay and consumer lag matter.
- WebRTC architecture
- STUN & TURN servers
- ICE framework
- SDP negotiation
- RTP protocol
- NAT traversal
- Signaling server design
- Peer-to-peer vs SFU vs MCU
- Media server basics
- Presence systems
- Elasticsearch internals
- Inverted indexes
- Full-text search
- Relevance scoring (BM25)
- Analyzers & tokenizers
- Aggregations
- Fuzzy search
- Syncing Postgres → Elasticsearch
- Vector search basics
Phase project: Add a real-time activity feed to the HRMS using Kafka (event stream) + Elasticsearch (searchable audit log) + WebSocket (live push to dashboard).
Cloud, DevOps & Production Infrastructure
10 weeks- Multi-stage Dockerfiles
- Container security scanning
- Docker layer optimization
- Kubernetes architecture deep dive
- Pod lifecycle
- Deployments & rollbacks
- StatefulSets
- Ingress controllers
- Secrets management in K8s
- Horizontal pod autoscaling
- Helm charts
- Namespace isolation
Upgrade from Track 1: basic Docker and EC2 become production Kubernetes with autoscaling, rollbacks, secrets and zero-downtime deploys.
- VPC design
- Private vs public subnets
- Security groups & NACLs
- ALB & NLB
- Auto-scaling groups
- RDS multi-AZ
- ElastiCache
- SQS & SNS
- S3 lifecycle policies
- CloudFront
- IAM roles & policies
- AWS Secrets Manager
- Terraform fundamentals
- State management
- Modules & workspaces
- GitHub Actions deep dive
- Blue-green deployments
- Canary deployments
- Feature flags
- Rollback strategies
- Secrets in CI/CD
- Pipeline security
- Three pillars: logs, metrics, traces
- OpenTelemetry
- Distributed tracing (Jaeger)
- Metrics (Prometheus + Grafana)
- Log pipelines (Loki / ELK)
- Alerting design
- SLIs, SLOs, SLAs
- Error budgets
- Incident response playbooks
- RCA process
Phase project: Deploy the full HRMS stack to AWS with Terraform. Kubernetes with autoscaling. Full observability. CI/CD with blue-green deploys. Simulate a production incident and run an RCA.
Performance Engineering & Capstone
8 weeks- CPU profiling
- Memory profiling & leak detection
- Node.js performance tools
- Flame graphs
- Load testing (k6 / Artillery)
- Throughput vs latency tradeoffs
- Connection pool tuning
- GC pressure analysis
- Network latency diagnosis
- APM tooling
- Extend the HRMS into a multi-service platform
- Add Kafka event streaming
- Add SAML SSO
- Add Elasticsearch search
- Add a WebRTC video-calls module
- Full Kubernetes deployment
- Observability dashboard
- Load-test to 10k concurrent users
- Performance report & architecture review
Final deliverable: A production-deployed, multi-service platform — Kafka-driven events, Elasticsearch search, SAML SSO, WebRTC video, full K8s infra, observability, and a load-test report proving it handles 10k concurrent users.
Practical labs & phase projects
Upgrade from Track 1: you learned to build APIs — now learn why systems break at scale and how to architect against it.
Lab: Build a distributed notification system — email + SMS + push via queues, with retry, dead-letter handling and delivery-status tracking.
Upgrade from Track 1: you learned to write queries — now learn why a query is slow and how to fix it at the engine level.
Lab: Take a slow multi-tenant query from Track 1’s HRMS, diagnose with EXPLAIN ANALYZE, redesign schema and indexes, and benchmark before/after.
Phase project: Implement SAML SSO + SCIM on the HRMS. Add secrets rotation with Vault. Run OWASP ZAP against the APIs and fix all critical findings.
Upgrade from Track 1: BullMQ handled simple job queues — Kafka handles event streaming at scale where ordering, replay and consumer lag matter.
Phase project: Add a real-time activity feed to the HRMS using Kafka (event stream) + Elasticsearch (searchable audit log) + WebSocket (live push to dashboard).
Upgrade from Track 1: basic Docker and EC2 become production Kubernetes with autoscaling, rollbacks, secrets and zero-downtime deploys.
Phase project: Deploy the full HRMS stack to AWS with Terraform. Kubernetes with autoscaling. Full observability. CI/CD with blue-green deploys. Simulate a production incident and run an RCA.
Final deliverable: A production-deployed, multi-service platform — Kafka-driven events, Elasticsearch search, SAML SSO, WebRTC video, full K8s infra, observability, and a load-test report proving it handles 10k concurrent users.
Projects you'll ship
Distributed Notification System
Email + SMS + push via queues, with retry, dead-letter handling and delivery-status tracking.
Query Optimization Overhaul
Diagnose a slow multi-tenant query with EXPLAIN ANALYZE, redesign schema/indexes, and benchmark before/after.
SSO + Zero-Trust Hardening
SAML SSO, SCIM provisioning, Vault-backed secrets rotation and OWASP ZAP-verified API security.
Realtime Activity Feed
Kafka event stream + Elasticsearch audit log + WebSocket live push to the dashboard.
Production Infra on AWS
Terraform + Kubernetes with autoscaling, full observability, blue-green CI/CD and a simulated incident RCA.
Multi-Service Platform (Capstone)
A K8s-deployed platform with Kafka, SSO, search and WebRTC video — load-tested at 10k concurrent users.
Tools & technologies covered
Career outcomes
This track is built to make you employable at the level above where you started. Pair it with your deployed capstone and public write-ups, and you walk into interviews with proof, not promises.
See the full career roadmapTrack 2 FAQs
Enroll in Track 2
Track 1 graduates or engineers with equivalent production experience — this is where you start. Talk to an advisor to confirm it's the right fit.