Let’s begin with Conway’s famous law:

“Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations.”

This powerful perspective provides a crucial lens for understanding the current trend of expanding API Gateway scope with concepts like Event Gateway, Kafka Gateway, AI Gateway, and Agent Gateway…etc.

While this expansion carries the risk of turning API gateways into “do-everything” tools reminiscent of cumbersome ESB (Enterprise Service Bus) architectures of the past, we also shouldn’t ignore scenarios where certain integrations can provide value due to technological evolution and pragmatic needs. Striking this balance is central to modern architectural decisions.

Examining the relationship between API Gateway and Service Mesh technologies offers a good starting point. In the generally accepted approach, API Gateways manage “north-south” traffic (from external clients to internal services), while Service Meshes focus on “east-west” traffic (inter-service communication). Having these two technologies specialize in their respective domains and used together often yields a more scalable, manageable, and performant architecture for most large-scale and complex systems.

However, especially in small-scale projects with limited resources or low system complexity, or within the capabilities of certain platform products, consolidating these two functions into a single tool might be a pragmatic and reasonable solution.

Organizational Structures and Technological Echoes

The link between organizational structures and technology choices is inescapable. In structures where different teams develop systems within their own silos, and communication and coordination are challenging, integration can become a significant problem. API Gateways gained popularity to bridge these organizational gaps and build connections between silos.

ESBs, born from a similar need, can still be functional in specific corporate integration scenarios. However, their claim to be the “single tool that solves everything” often led them to become bloated and obstacles to change over time. Whether API Gateways fall into a similar trap today largely depends on how organizations position these tools, how clearly they draw responsibility boundaries while being mindful of Conway’s Law, and whether they attempt to mask underlying organizational problems with technology.

Business Logic Creep into Gateways: Risks and Pragmatic Considerations

The issue of business logic seeping into API Gateways requires conscious evaluation rather than rigid rules. While this situation is often symptomatic of organizational problems (lack of communication, avoidance of responsibility), it can also offer pragmatic benefits in some cases:

  • Data Transformations: Simple data formatting or field mapping might provide efficiency within the gateway. However, transformations involving complex business rules (e.g., detailed financial calculations) or those that change frequently are generally healthier to implement in the application layer or a dedicated integration service to maintain the gateway’s focus and ease maintenance.
  • Authorization Rules: Basic authentication and simple role checks (e.g., general endpoint access) can be managed centrally at the gateway. However, resource-specific, business-rule-based, or highly granular authorization logic is often better handled by the relevant microservice or a dedicated authorization service for proper distribution of responsibilities.
  • Event Processing: Basic event filtering or simple routing rules might reside in the gateway in some scenarios. But for complex event correlation, anomaly detection, or stateful event processing logic, using dedicated event processing platforms or messaging systems is more suitable for architectural clarity and scalability.

The key here is not a dogmatic “never put business logic in the gateway” stance, but rather a conscious evaluation: “Which piece of business logic belongs in which layer for the best architectural principles, performance, security, scalability needs, and organizational capabilities?” Drawing the boundaries correctly is essential.

From Developer to Specialized Roles: Opportunities and Pitfalls

The specialization of software teams around specific platform components (like API Gateways) reflects an organization’s talent management and technology strategy, carrying both opportunities and risks. For instance, rapidly integrating AI services using a dedicated AI Gateway product can shorten time-to-market and provide focused expertise. However, this approach can also have downsides:

  • Advantages: Faster value delivery, deep expertise in a specific area, fully leveraging platform capabilities.
  • Disadvantages: Teams becoming dependent on a narrow technology or product (vendor lock-in risk), erosion of general software development skills, reduced organizational flexibility to adapt to different solutions.

The ideal balance depends on the organization’s size, strategic goals, resources, and culture. Large organizations might prefer creating roles and teams requiring deep specialization, while smaller or more agile organizations might encourage T-shaped skills with broader responsibilities.

The Balance Between Pragmatic Solutions and Ideal Architectures

Real-world projects rarely proceed with purely “ideal” architectures. Often, pragmatic decisions are necessary due to existing constraints, time pressures, and business needs:

  • “Saving the Day” and Pragmatic Approaches: A bank temporarily adding “AI features” to its existing API Gateway to meet an urgent business need might be a reasonable step if resources are limited, market pressure is high, or it’s planned as a stopgap until a more permanent solution is developed. Such decisions can be viewed as consciously incurred and managed “technical debt.”
  • “Ideal” and Long-Term Approaches: The same bank, aligning with its long-term strategy, developing a purpose-built orchestration layer or a dedicated AI Gateway solution for AI services offers a more scalable, sustainable, and flexible architecture. This approach allows leveraging the strengths of each technology optimally and facilitates future architectural evolution. However, it requires more initial investment, time, and organizational coordination.

Successful organizations strike a conscious balance between these two approaches; they neither always jump to the quickest fix nor miss opportunities while waiting for perfection.

Technological Evolution, Differentiating Needs, and Decision Factors

The proliferation of concepts like Event Gateway, Kafka Gateway, AI Gateway, and Agent Gateway indicates that technology and business needs are constantly evolving, leading to different communication patterns. The decision whether to handle this new functionality within existing API Gateways or develop them as separate, specialized products/components is a strategic one with no simple right or wrong answer, depending on factors like:

  • Organization’s Scale and Complexity: Large, complex systems usually benefit from specialized components.
  • Team Structure and Expertise: The competencies and responsibilities of existing teams.
  • Specificity and Urgency of Business Needs: The complexity of the required functionality and how quickly it needs to be implemented.
  • Cost, Resource Constraints, and Management Overhead: The total cost of ownership for adding a new tool versus extending an existing one.
  • Long-Term Strategic Goals and Architectural Vision: Future expectations for flexibility and scalability.
  • Capabilities of the Existing API Gateway: Modern API Gateway platforms might have more modular and plugin-based architectures compared to ESBs, potentially making some integrations more manageable. However, this modularity shouldn’t be a justification for consolidating everything under one roof.

Solution: Conscious Decisions and a Balanced Approach

Managing the effects of Conway’s Law and building healthy technological architectures require conscious steps on both organizational and technological fronts:

  1. Define Conscious and Pragmatic Boundaries: Clearly define the core responsibilities of each technology (API Gateway, Service Mesh, Event Broker, AI Gateway, etc.). Draw these boundaries not as rigid dogmas, but pragmatically, considering the project’s and organization’s context. Controlled overlaps might be acceptable in some cases.
  2. Align Technology Choices with Business Needs and Organizational Context: Make technology decisions based on their ability to solve real business problems, aligned with your organization’s scale, resources, and team competencies, not just popular trends. There’s no “one size fits all.”
  3. Apply Conway’s Law Consciously (Acknowledge Bi-Directional Influence): Aim for organizational structures that support your desired architecture. However, acknowledge that organizational change takes time and that sometimes technology choices can also trigger organizational evolution.
  4. Focus on Organizational Improvements: Technology can be a tool to address organizational problems (communication gaps, silos, unclear responsibilities), but it’s never the sole solution. Focus on the root causes.
  5. Phased Transition and Manageable Technical Debt: Reaching the ideal architecture rarely happens overnight. Develop phased transition strategies while deriving value from existing systems, and consciously manage incurred technical debt.

Conclusion: Context-Driven Conscious Architectural Choices

The answer to whether concepts like Event Gateway, Kafka Gateway, or AI Gateway should be integrated into API Gateways or treated as separate products depends on the organizational context.

For large-scale, complex, and long-lived systems, designing these functions as separate, specialized products or components connected via well-defined interfaces generally offers a more sustainable, scalable, and manageable approach. This helps prevent API Gateways from sharing the fate of ESBs.

However, for smaller organizations, prototypes, situations with resource constraints, or specific, simple integration needs, pragmatically resolving some functions within the existing API Gateway platform might be more efficient.

The crucial part is making these decisions consciously — not hastily or based on assumptions — by carefully evaluating the factors mentioned above and weighing the potential benefits and risks.

Learning from past ESB experiences, we should keep API Gateways focused on their core value propositions (API management, security, traffic control), make expansion decisions measuredly, and prefer specialized solutions for different needs, without entirely dismissing pragmatic integration possibilities. Ultimately, the future of API Gateways will depend on how skillfully we manage this complex dance between technology and organization.