ACCELERATOR PROGRAM

Architecture for Multi-Product Platforms

Design resilient, evolvable architectures for platforms that support multiple products and teams.

Joseph Kanon
LED BY Joseph Kanon
0 ENROLLED
3 months DURATION
5 MODULES
CAPITAL COMMITMENT
$1,697.00 USD
Duration 3 months
Format Self-paced
Level All Levels
SECURE POSITION

About This Accelerator

Program overview and objectives

Most architecture advice assumes a single product. Reality is messier. This program teaches you how to design systems where multiple products share infrastructure, data, and identity — without creating a tangled monolith. You will learn domain modeling, service decomposition, API governance, data ownership patterns, and platform team operating models drawn from real multi-product platform builds.
Self-paced Format
3 months Duration
5 modules, 25 lessons Content
All Levels Level
Included Certificate

Projected Returns

Operational capabilities upon completion

Produce a complete multi-product architecture blueprint with domain maps
service boundaries
and API contracts
Design a data ownership model that assigns clear stewardship across product teams
Build an API governance playbook tailored to your organization's scale and maturity
Create a platform maturity roadmap that sequences infrastructure investments with business impact
Deliver an architecture decision record library covering the key trade-offs in platform design

Investment Structure

5 modules · 25 lessons · 20h 5m

Explore how to identify and map bounded contexts across a multi-product platform. Through event storming workshops and context mapping exercises, you will build a shared domain language that scales across teams and products.

Bounded Contexts in Multi-Product Systems PREVIEW
Event Storming Workshop Walkthrough
Context Mapping Patterns
Domain Model Design Lab
Live Domain Modeling Session

Learn proven strategies for breaking apart monolithic systems into well-bounded services. Explore migration patterns, anti-patterns to avoid, and decision frameworks that help you decompose with confidence rather than guesswork.

Monolith to Microservices: Migration Patterns
Service Boundary Anti-Patterns
Strangler Fig Pattern in Practice
Decomposition Decision Framework
Service Boundary Design Exercise

Master the discipline of API design at platform scale. Learn versioning strategies, contract-first development, GraphQL federation, and how to build governance processes that keep APIs consistent without slowing teams down.

API Versioning Strategies
Contract-First Development with OpenAPI
GraphQL Federation for Platform APIs
API Governance Playbook
API Design Review Lab

Tackle the hardest problem in multi-product platforms: data. Learn data mesh principles, event sourcing, CQRS, data contracts, and how to assign clear data ownership without falling into the shared database trap.

Data Mesh Principles for Product Teams
Event Sourcing and CQRS in Practice
Shared Database Anti-Pattern
Data Contract Design
Data Ownership Mapping Exercise

Bring it all together by learning how to build an internal developer platform and organize teams to sustain a multi-product architecture. Cover golden paths, platform maturity models, and the capstone architecture blueprint.

Building an Internal Developer Platform
Team Topologies for Platform Organizations
Golden Paths and Paved Roads
Platform Maturity Assessment
Capstone: Multi-Product Architecture Blueprint

Deliverables

Tangible assets you'll create

Domain Model Design Lab
Apply everything from this module in a hands-on project. Given a realistic multi-product platform scenario, you will produce a domain model with bounded contexts, context maps, and integration contracts ready for peer review.
Service Boundary Design Exercise
Put theory into practice by analyzing a monolithic codebase and proposing service boundaries. Submit your decomposition plan with rationale for each boundary decision, including coupling analysis and migration sequencing.
API Design Review Lab
Design and review a set of APIs for a multi-product platform scenario. Apply versioning strategies, write OpenAPI specifications, and conduct a peer review using the governance playbook criteria from this module.
Data Ownership Mapping Exercise
Map data ownership across a multi-product platform scenario. Identify data domains, assign stewardship, define data products, and create contracts between producers and consumers. Submit your ownership matrix with rationale for each assignment.
Capstone: Multi-Product Architecture Blueprint
Synthesize everything from the program into a comprehensive architecture blueprint for a multi-product platform. Deliver domain models, service boundaries, API contracts, data ownership maps, team structures, and a platform maturity roadmap in a single cohesive document.

The Advisory Board

Program architects and mentors

Joseph Kanon

Joseph Kanon

Included Assets

Proprietary resources included with enrollment

Decomposition Decision Framework
A structured decision framework document that guides you through evaluating whether a module should be extracted as a service. Covers coupling analysis, deployment frequency, team ownership, data affinity, and scalability requirements.
API Governance Playbook
A comprehensive document outlining how to establish API governance in a multi-team organization. Covers style guides, review processes, linting automation, breaking change detection, and how to balance governance rigor with developer velocity.
Data Contract Design
A reference document covering data contract specification patterns. Learn how to define schema expectations, quality guarantees, SLAs, and change management processes between data producers and downstream consumers.
Platform Maturity Assessment
A structured assessment document to evaluate your organization's platform maturity across dimensions including self-service capabilities, observability, deployment automation, documentation, and developer experience metrics.

Entry Requirements

Prerequisites for admission

At least 5 years of professional software engineering experience
including work on distributed systems
Familiarity with at least one cloud platform (AWS
Azure
or GCP) and containerized deployments
Experience working in or leading engineering teams that ship production software