Distributed Systems Paradox - Avoid turning your system into Distributed Monolith: Part 1 - Command vs Events

Decomposing a monolith into services doesn't automatically grant you the promised land of microservices virtues. In fact, service decomposition merely transformed your system into a "big ball of mud"—exponentially more complex, with all the original problems now amplified by network fallacies.

The Hidden Tax of Poorly Designed Distribution:

When architectural decisions are made without understanding fundamental distributed computing principles, you don't just fail to gain microservices benefits—you actively accumulate liabilities:

• Network partition vulnerabilities that didn't exist in your monolith
• Cascading latency amplification from synchronous service chains over network
• Consistency boundaries that leak across service boundaries
• Security attack surfaces multiplied by every new network hop
• Operational complexity that scales super-linearly with service count
• Infrastructure costs that can 10x without corresponding value delivery

Hence, distributed system without distributing thinking often makes your system more complex and slower.

The Architectural Decisions That Actually Matter:

True microservices architecture emerges from deliberate decisions about boundaries, communication patterns, and failure modes. It requires deep understanding of distributed systems primitives—not just containerization and REST APIs.

Part1: Commands vs Events

Not everything is an event, and not everything is a command. This isn't philosophical—it's a fundamental architectural decision that determines whether your distributed system achieves consistency or descends into chaos.

The Intuitive Definitions That Matter:

Commands capture intent—they represent what we expect the system to do. When a command fails, the requester must be informed immediately. This isn't optional; it's architectural law. Commands establish a contract: "Execute this action and tell me if you succeeded."

Events capture facts—they announce that something has already happened. The sender publishes into the void, blissfully unaware of who consumes these facts or whether consumers successfully process them. This ignorance isn't negligence; it's architectural decoupling.

The Critical Distinction: Primary Operations vs Side Effects

Commands are your primary requests—the main business operations that users explicitly trigger. Events are the side effects—the cascading reactions that ripple through your system after a command succeeds.

Consistency Boundaries:

Commands must complete or fail atomically. This isn't negotiable. A half-executed command leaves your system in an inconsistent state—the distributed systems equivalent of corruption. This is why we implement the Aggregate pattern religiously: one command, one aggregate, one transaction boundary.

When ProcessPayment command executes, it either fully completes (payment processed, inventory reserved, order confirmed) or fully fails with rollback. No middle ground. No partial states.

Events enable eventual consistency—and this is by design, not compromise. When PaymentProcessed event fires, downstream systems react asynchronously: email service sends confirmation, analytics updates dashboards, shipping prepares fulfillment. If the email fails? The payment remains processed. The system remains consistent, just not yet complete.

The Architectural Implications:

This distinction drives every subsequent decision:

• Commands require request -response pattern with immediate feedback loops
• Events demand asynchronous processing with retry resilience
• Commands validate before execution; events recover after failure
• Commands modify single aggregates; events trigger cross-boundary reactions