A tailored course, built for your situation
Architecting Serverless Systems for Scale and Resilience
A 12-module mastery path for engineers building high-uptime serverless platforms
The situation this course is for
Serverless offers speed and efficiency, but without intentional architecture, it leads to fragmented ownership, hidden failure points, and technical debt that compounds under load. You're expected to deliver resilient systems, yet most guidance stops at 'hello world' patterns.
Who this is for
Mid-to-senior backend or full-stack engineer with hands-on experience in serverless functions, now tasked with designing or maintaining large-scale, long-lived serverless platforms requiring observability, fault tolerance, and lifecycle governance.
Who this is not for
This course is not for beginners learning to deploy their first Lambda function, nor for managers seeking high-level overviews. It’s not for those focused only on frontend integration or one-off scripts.
What you walk away with
- Design serverless systems with built-in resilience and observability
- Implement event-driven architectures that scale predictably
- Apply ownership patterns to prevent distributed monoliths
- Integrate automated recovery and rollback at the service level
- Ship updates safely using canary and circuit-breaker patterns
The 12 modules (with all 144 chapters)
- Event-first mindset
- Stateless execution
- Function lifecycle
- Cold start dynamics
- Concurrency limits
- Execution context
- Memory allocation
- Timeout tradeoffs
- IAM granularity
- Error handling basics
- Retries and backoff
- Observability entry
- Event sourcing basics
- Event vs command
- Message routing
- Fan-out strategies
- Event filtering
- Dead letter handling
- Event schema design
- Event versioning
- Event replay
- Event capture
- Event consistency
- Event ownership
- Failure domains
- Retry strategies
- Circuit breakers
- Bulkheads
- Graceful degradation
- Chaos testing
- Timeout tuning
- Backpressure
- Error budgets
- Recovery SLIs
- Failure injection
- Resilience metrics
- Structured logging
- Trace context
- Span propagation
- Metric dimensions
- Log filtering
- Alert correlation
- Latency percentiles
- Error rate tracking
- Custom dashboards
- Log retention
- Trace sampling
- Correlation IDs
- IAM role design
- Principle of least
- Secrets management
- Environment isolation
- Token propagation
- OAuth integration
- API key controls
- Request validation
- Input sanitization
- VPC design
- Network isolation
- Audit logging
- CI/CD pipeline
- Canary releases
- Rollback triggers
- Pipeline stages
- Build artifacts
- Version promotion
- Deployment safety
- Smoke testing
- Traffic shifting
- Blue-green function
- Pipeline speed
- Approval gates
- Concurrency tuning
- Cost per invocation
- Memory scaling
- Burst capacity
- Throttling strategy
- Provisioned concurrency
- Cold start tradeoffs
- Batch sizing
- Event batching
- Cost monitoring
- Usage alerts
- Budget enforcement
- Durable storage
- Eventual consistency
- Saga pattern
- Transaction boundaries
- Data versioning
- Schema migration
- Data lifecycle
- TTL strategies
- Backup approaches
- Restore workflows
- Cross-region sync
- Data ownership
- Unit test scope
- Contract testing
- Integration tests
- Event replay
- Load testing
- Chaos scenarios
- Test environments
- Mock services
- Test data
- Failure simulation
- Test coverage
- Automated validation
- Runbook creation
- On-call readiness
- Incident response
- Postmortem process
- Ownership clarity
- Team handoff
- Service documentation
- Change logging
- Monitoring ownership
- Alert fatigue
- Escalation paths
- Blameless culture
- Interface versioning
- Function renaming
- Deprecation policy
- Backward compatibility
- Migration tracking
- Legacy identification
- Service retirement
- API gateways
- Routing rules
- Feature flags
- Canary migration
- Decommission checklist
- Compliance checks
- Audit trails
- Lifecycle stages
- Service catalog
- Policy enforcement
- Resource tagging
- Cost allocation
- Security scanning
- Dependency updates
- Patch cycles
- Access reviews
- Disaster recovery
How this maps to your situation
- You're designing a new serverless platform
- You're debugging recurring failures in existing functions
- You're scaling a system that worked at small volume
- You're being asked to own uptime and reliability
Before vs. after
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3-4 hours per module, designed for engineers to apply concepts incrementally while working.
How this compares to the alternatives
Unlike generic tutorials or video playlists, this course delivers actionable, text-based patterns used in production systems, structured for engineers who learn by doing and need clarity, not fluff.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.