Open Host Service Pattern — Published API for Subsystems

In this tutorial, you'll learn how the Open Host Service pattern provides a published API for external subsystems to interact with a bounded context.

What You'll Learn

how the Open Host Service pattern provides a published API for external subsystems to interact with a bounded context.

Why It Matters

Internal model changes should not break external consumers. Open Host Service provides a stable published protocol.

Real-World Use

REST APIs with versioning, gRPC services, and SOAP web services are Open Host Service examples.

The Open Host Service Pattern

The Open Host Service pattern addresses a specific recurring design problem by providing a reusable solution structure. Understanding when and how to apply it is essential for writing maintainable, scalable code.

Key Concepts

• Registry/Tracking: Open Host Service maintains a registry of objects or operations.
• Atomicity: Changes are grouped into units that succeed or fail together.
• Isolation: Each unit operates independently.
• Consistency: The pattern ensures data integrity across operations.

Structure

The following diagram shows the structure of this pattern:

classDiagram
    class OpenHostService {
        -new: List
        -dirty: List
        -removed: List
        +registerNew()
        +registerDirty()
        +registerRemoved()
        +commit()
    }
    class Entity { id data }
    class DataMapper { +insert() +update() +delete() }
    OpenHostService --> Entity : tracks
    OpenHostService --> DataMapper : persists

Implementation

from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import List, Dict

@dataclass
class Entity:
    id: int
    data: str = ""

class OpenHostServiceRegistry:
    def __init__(self):
        self._new: List[Entity] = []
        self._dirty: List[Entity] = []
        self._removed: List[Entity] = []

    def register_new(self, e: Entity):
        self._new.append(e)

    def register_dirty(self, e: Entity):
        if e not in self._dirty:
            self._dirty.append(e)

    def register_removed(self, e: Entity):
        self._removed.append(e)

    def commit(self):
        print(f"Inserting {len(self._new)} new entities")
        print(f"Updating {len(self._dirty)} dirty entities")
        print(f"Deleting {len(self._removed)} removed entities")
        self._new.clear()
        self._dirty.clear()
        self._removed.clear()

# Usage
reg = OpenHostServiceRegistry()
e1 = Entity(1, "Alice")
e2 = Entity(2, "Bob")
reg.register_new(e1)
reg.register_new(e2)
e1.data = "Alice Updated"
reg.register_dirty(e1)
reg.register_removed(e2)
reg.commit()

Expected output:

Inserting 2 new entities
Updating 1 dirty entities
Deleting 1 removed entities

Key Participants

• Open Host Service: Coordinates tracking and persistence of changes.
• Entity: The domain object being tracked.
• Client: Code that uses the Open Host Service.
• Data Mapper: Handles actual database operations.

Real-World Examples

• DodaTech uses this pattern internally for consistent cross-cutting concerns.
• Major frameworks and libraries implement this pattern as a core architectural element.
• Production systems at scale depend on this pattern for reliability.

Related Patterns

• Published Language

• Anti Corruption Layer

• Facade

• Design Patterns — the complete patterns catalog.

Pros and Cons

Common Mistakes

1. **Over-engineering: Applying Open Host Service where a simpler solution suffices, adding unnecessary complexity.

2. **Wrong granularity: Implementing Open Host Service at the wrong level of abstraction.

3. **Thread Safety ignored: Using Open Host Service in concurrent context without proper synchronization.

4. **Tight coupling: Violating the pattern intent by creating hidden dependencies.

5. **Premature optimization: Introducing Open Host Service before there is evidence it is needed.

Practice Questions

1. What problem does the Open Host Service pattern solve? Describe a real-world scenario where using it improves code quality.

2. How does Open Host Service differ from alternative approaches? What are the trade-offs?

3. What testing Strategy would you use for code that implements Open Host Service?

4. How would you refactor legacy code to introduce Open Host Service?

5. When should you NOT use Open Host Service? Describe scenarios where it adds unnecessary complexity.

Challenge

Implement a complete Open Host Service example in Python with unit tests. Include error handling, edge cases (empty data, null values, concurrent access), and a performance comparison against a simpler alternative. Document your design decisions.

Real-World Task

Find a section of code in your current project that could benefit from the Open Host Service pattern. Refactor it, write tests, and measure the improvement in testability, coupling, and cohesion.

Security Tip: When implementing Open Host Service, ensure proper input validation, avoid exposing internal state, and follow Least Privilege. At DodaTech, all implementations undergo security review.

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