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TIER A · ENGINEERING

AI-Assisted Microservices & Distributed System Design

Decompose Monoliths and Design Distributed Systems — Where AI Does the Most Damage

AdvancedCohort-Based13 sessions · 26hDhaka + Global
Join the waitlist·Get the full syllabus

Decompose monoliths and design distributed systems — where AI does the most damage.

Distributed systems are where confident-but-wrong AI output is most expensive. Ask a model to 'split this into microservices' and it will happily hand you a distributed monolith — services that can't be deployed independently, share a database, and fail together — wrapped in the vocabulary of good architecture. The failure shows up six months later as a system nobody can change without breaking three other things.

This course teaches you to design microservices and distributed systems deliberately, using AI to accelerate the work while you supply the judgment it lacks. You'll learn to find correct service boundaries, choose synchronous vs asynchronous communication on purpose, manage data across services without corruption, and design for the failure that distribution guarantees.

Why this course exists

Distributed systems are where confident-but-wrong AI output is most expensive. Ask a model to 'split this into microservices' and it will happily hand you a distributed monolith — services that can't be deployed independently, share a database, and fail together — wrapped in the vocabulary of good architecture.

The failure won't show up in a demo. It shows up six months later as a system nobody can change without breaking three other things. The two things AI hand-waves most — data consistency and failure handling — are precisely what distributed systems are mostly about.

This course teaches you to design microservices and distributed systems deliberately, using AI to accelerate the work while you supply the judgment it fundamentally lacks.

Before

"Microservices = good, monolith = bad. I asked AI to split my monolith and it gave me services that share a database. That's fine, right?"

After

"I know when a modular monolith is the right answer. I split by bounded context, design data ownership away from the dual-write problem, and detect the distributed monolith AI generates before it ships."

What you'll walk away with
  1. 1Detects and refuses the distributed monolith AI defaults to — splits by bounded context, not by technical layer
  2. 2Designs data ownership across services and closes the dual-write problem before it ships
  3. 3Chooses synchronous vs. asynchronous communication on purpose, with explicit delivery and consistency guarantees
  4. 4A defended capstone: decompose a real monolith into a distributed target architecture across data, resilience, and deployment
Curriculum

13 sessions · 26h across 4pillars · every session ends with a working, reviewable artifact. Expand any pillar for the session lineup.

FoundationsMonoliths, DDD, decomposition · Week 1–2
▼
  • Session 1 — Monolith, Modular Monolith, Microservices: Choosing Honestly
  • Session 2 — Domain-Driven Design for Service Boundaries
  • Session 3 — Decomposing a Monolith (Strangler Fig, Incremental Extraction)
CommunicationSync, async, and event-driven · Week 3–4
▼
  • Session 4 — Synchronous Communication: REST & gRPC
  • Session 5 — Asynchronous Communication & Event-Driven Architecture
Distributed DataOwnership, transactions, consistency · Week 5–7
▼
  • Session 6 — Distributed Data I: Ownership & the Dual-Write Problem
  • Session 7 — Distributed Data II: Transactions, Sagas & Idempotency
  • Session 8 — Consistency, CAP & Eventual Consistency Patterns
Production & CapstoneResilience, observability, deployment · Week 8–13
▼
  • Session 9 — Resilience: Timeouts, Retries, Circuit Breakers, Bulkheads
  • Session 10 — Service Discovery, API Gateway & Service Mesh
  • Session 11 — Observability for Distributed Systems
  • Session 12 — Deployment & Distributed Anti-Patterns
  • Session 13 — Capstone: Decompose & Defend

Want the full session-by-session syllabus with objectives and deliverables? Request it here— we'll send it over.

Format & schedule
DeliveryCohort-based, live, instructor-led
Class length2 hours per class
Cadence2 classes/week (4 hours/week)
Total length13 sessions · 26h over 6.5 weeks
LocationDhaka + Global (remote seats available)
PrerequisitesAI-Assisted System Design or equivalent system-design experience. Comfort with REST APIs and databases.
Pricing

৳4,500

$69 global

Coming soon

This course launches soon. Join the waitlist for early access and launch-day pricing.

FAQ
What's the difference between this and Course 2 (System Design)?▼

Course 2 teaches general system design. This specializes in microservices and distributed systems — the hardest domain where AI does the most damage.

Do I need Kubernetes experience?▼

No. This course covers deployment concepts at the architecture level. Deep Kubernetes is outside scope.

Will we build microservices in class?▼

The capstone is a design exercise — you decompose a monolith and defend the target architecture. This is a design course, not a coding bootcamp.

Part of a longer track?

This course is part of the TIER A · ENGINEERING. Explore the full catalog to find related courses that build on each other.

View all courses →

৳4,500

Cohort — 6.5 weeks