Many organizations operate on applications that still fulfill their primary function. The system processes orders, manages customers, records invoices, or manages inventory. From a strictly technical perspective, it could be argued that it works. However, each modification takes months, any integration generates uncertainty, and launching a new digital experience involves modifying multiple components that no one wants to touch.
The company then begins to work around its own technology. Teams export data to spreadsheets, create parallel applications, and rely on manual processes to connect systems that were never designed to collaborate. The software remains operational, but it gradually becomes a constraint for the business.
The arrival of Artificial Intelligence makes this difficulty even more apparent. An agent needs to query data, use services, execute actions, and connect with different applications. When all business logic is locked within monolithic platforms, point-to-point integrations, or systems without clear interfaces, implementing AI requires building a new layer of makeshift solutions.
Compostable architecture proposes an alternative: transforming business capabilities into modular blocks that can be combined, reused, and evolved without replacing the entire ecosystem every time a need changes.
Composable architecture is an approach that structures applications and business capabilities as modular, interoperable, and replaceable components. Each block fulfills a clearly defined function and communicates with the others through contracts, APIs, or events.
Gartner describes composable applications as a combination of applications, APIs, and services designed to offer greater agility, flexibility, integration, and modularity. The goal is to enable organizations to assemble capabilities according to business needs, rather than relying exclusively on rigid, closed platforms.
This idea can be compared to building with blocks. An organization might have components for customers, payments, billing, inventory, authentication, notifications, and analytics. A new digital product uses some of those components without duplicating or rebuilding them.
When a capability needs to evolve, it can be modified or replaced with a more controlled impact on the rest of the system. The architecture ceases to be organized solely around complete applications and begins to be structured around reusable business capabilities.
One of the most common mistakes is assuming that composable architecture automatically equates to dividing a system into dozens or hundreds of microservices. While microservices can be part of the approach, they are not the goal in and of themselves.
Martin Fowler defines microservices as small services, organized around business capabilities and deployable independently. This model can improve autonomy and allow for isolated changes, but it also introduces costs related to distributed communication, observability, testing, infrastructure, and coordination.
An organization can have many microservices and still be difficult to change. This happens when boundaries are poorly defined, services are overly dependent on each other, or each team uses incompatible technologies without common standards.
It's also possible to build a composable architecture using a modular monolith, managed services, well-designed APIs, and events. The decision should depend on the complexity of the business, the size of the teams, and the actual need for independence.
Composability is not measured by the quantity of services. It is measured by the ease with which a company can combine, change, and reuse capabilities without triggering a chain reaction.
In many discussions about modernization, the monolith is presented as an obsolete architectural style that must be replaced immediately. This view can lead to costly and unnecessary transformations.
A well-structured monolith may be suitable for applications with a controlled domain, few teams, and relatively simple deployment needs. Martin Fowler has pointed out that most systems can start as monolithic applications, provided they maintain clear modular boundaries, and that microservices should be considered when complexity exceeds what can be reasonably managed within that model.
The problem isn't that the entire application is deployed as a single unit. The problem arises when the logic is mixed, the modules lack clear boundaries, and any modification affects seemingly independent areas.
A modular monolith can be internally composable. Capabilities are separated through contracts, ownership, and dependency rules, even though they continue to operate within the same deployment.
Mature architecture avoids ideological decisions. It doesn't choose microservices because they seem modern, nor does it maintain a monolith for convenience. It evaluates which structure allows for evolution with the least risk and complexity.
An API allows a capability to be used by different applications without directly exposing its internal implementation. A billing system might offer operations to create invoices, check statuses, or void documents. A web application, a mobile app, a customer portal, and an AI agent can all use these operations through consistent interfaces.
The API-first approach involves designing the contract before building the implementation. The team defines what the capability can do, what data it receives, what results it delivers, how it handles errors, and how it will evolve without breaking its consumers.
Microsoft notes that API management platforms allow you to securely publish services, enforce policies, control access, and manage their lifecycle in hybrid and multicloud environments.
Without an API strategy, integrations often connect directly to databases or rely on undocumented internal behaviors. Every change can break external applications, and the company accumulates invisible dependencies.
A well-designed API transforms an internal function into a reusable business capability. However, simply publishing endpoints is not enough. The organization needs clear contracts, security, versioning, documentation, observability, and ownership.
A company can replace direct connections with APIs and still face the same structural problem. If each application directly calls many others, the network of dependencies grows rapidly. A change in one system can affect multiple consumers, and the architecture becomes difficult to visualize.
API management helps centralize policies, authentication, consumption limits, observability, and publishing. An API gateway can act as a control point for requests, enforce rules, and collect telemetry without requiring each service to implement all mechanisms separately.
However, the gateway should also not become a system that centralizes all business logic. Its primary function is to manage traffic, policies, and exposure. When it starts transforming complex processes and excessively coordinating every interaction, it creates a new bottleneck.
Composable architecture requires balance. APIs facilitate direct interactions when a consumer needs an immediate response. For processes where multiple systems must react independently, an event-driven architecture may be more appropriate.
In synchronous integration, one application requests an action from another and waits for a response. This pattern is useful when the result is needed immediately, but it creates a time dependency. If the receiving service is unavailable or responds slowly, the entire process can be affected.
In an event-driven architecture, a system announces that something has happened: an order was created, an invoice was issued, a customer updated their information, or a payment was confirmed. Other components can listen for that event and act upon it without the producer knowing all of its consumers.
AWS defines event-driven architecture as a model composed of decoupled services that publish, consume, or route events. This approach allows different components to react to state changes without rigid integrations between each producer and consumer.
For example, when a purchase is confirmed, inventory can reserve units, billing can generate the invoice, marketing can update the customer profile, and logistics can prepare the shipment. The sales system doesn't need to directly coordinate each activity.
This separation improves flexibility, but also requires managing duplicates, order, errors, traceability, and eventual consistency.
Dividing an architecture solely by technical layers can produce components that don't reflect the actual operation of the business. A database service, a validation service, and a utility service don't necessarily constitute independent business capabilities.
The most sustainable boundaries are typically aligned with domains such as orders, customers, payments, inventory, contracts, or support. Each component focuses on rules and data related to consistent accountability.
This approach reduces the amount of knowledge shared between teams. The payments team can evolve its processes without understanding all the inventory details, as long as it adheres to the established contracts.
The difficulty lies in correctly identifying those boundaries. A domain that is too broad creates an internal monolith. One that is too small generates multiple services that must collaborate to complete any operation.
Composable architecture requires understanding the business before dividing the technology. Technical diagrams should reflect business responsibilities, not just tools or databases.
When capabilities have clear limits, they can become reusable building blocks. When limits are arbitrary, modularity exists only in the infrastructure.
The promise of reuse can lead to overly generic components. A team attempts to build a "universal customer service" capable of meeting all current and future needs. The result is often a complex solution, slow to evolve, and burdened with contradictory rules.
Effective reuse occurs when there is a stable and clearly defined capacity that multiple consumers need. Authentication, notifications, payments, identity, and certain master data often offer good opportunities.
Other functions need to remain close to a specific product or domain. A particular business rule may not make sense outside of the application that uses it.
The goal of composability is not to force everything to be reusable. It's about separating what can be shared from what needs to evolve independently.
A component should have a clear responsibility, identified end users, and a maintenance cost justified by its value. Creating an internal platform for a one-time use can increase complexity rather than reduce it.
Mature architecture avoids two extremes: duplicating everything or trying to centralize everything.
A business agent can interpret a request, query information, and select tools to complete a goal. However, its capabilities depend on the available interfaces.
When systems expose documented APIs, events, and services with clear permissions, the agent can use specific functions without directly accessing the entire infrastructure. They can check the status of an order, create an opportunity, prepare an invoice, or schedule an activity using controlled contracts.
Gartner has noted that legacy application and data architectures hinder the creation of intelligent solutions, and that combining composable architecture with AI-ready data allows agents to be connected with business capabilities more effectively.
The alternative is to build unique integrations for each agent. This strategy might work during a test, but it quickly creates a new layer of dependencies, duplicate credentials, and logic.
An agent-ready company doesn't develop a different tool for every case. It exposes reusable, governed capabilities that can be used by both human applications and intelligent systems.
AI then becomes a new consumer of enterprise architecture, not a disconnected parallel solution.
Granting an agent broad access to a CRM, ERP, or database can accelerate prototyping, but it introduces security, traceability, and control risks. The agent could access unnecessary information or perform actions outside their role.
Composable architecture allows for the exposure of specific operations. A customer service agent can view orders and create cases, but doesn't need to modify financial configurations or download entire databases.
APIs and gateways can enforce authentication, authorization, limits, policies, and logging. Each tool used by the agent has a known contract and a controlled surface.
This structure also makes it easier to change the underlying system. The agent continues to use the same capabilities even if the company replaces the CRM or migrates part of its infrastructure, as long as the contract remains in place.
Modularity not only improves flexibility, it also creates safety boundaries. Instead of relying on the agent to avoid incorrect actions, the architecture technically restricts what it can do.
Replacing a core system in a single project can be prohibitively expensive and risky. The company needs to maintain operations while transforming applications, data, and integrations that have evolved over years.
An incremental strategy might begin by exposing legacy system functions through APIs, capturing events, and building new capabilities around its perimeter. Certain modules are then gradually replaced when there is a clear business reason.
The pattern known as Strangler Fig He proposes precisely to replace parts of an application progressively, directing certain functionalities to new components while the original system continues to operate. Martin Fowler also recommends decomposing systems according to capabilities that can provide independent value, avoiding massive migrations without intermediate results.
For example, a company can keep its core ERP system but build a new customer portal and order layer that connects via APIs. Later, it can modernize inventory or billing without shutting down the entire program.
Compostable architecture transforms modernization into a sequence of controlled decisions, not a single gamble.
When a company has multiple applications, it often creates a central layer to connect them. This strategy can improve visibility and reduce direct integrations. However, it can also concentrate too much logic in a single location.
If every transformation, rule, and process resides within the integration platform, any change depends on the same team. The organization replaces many small couplings with one large, central bottleneck.
The integration layer should facilitate communication, technical transformation, security, and coordination, but the fundamental business rules must remain close to the responsible domain.
Microsoft presents enterprise architectures where API management, messaging, and automation work together to connect applications, but these capabilities must be selected according to the integration pattern and process requirements.
There is no single tool suitable for every interaction. Some needs require synchronous APIs, others events, queues, orchestration, or file sharing.
Composable architecture uses several patterns consistently. It does not attempt to solve all problems with the same mechanism.
Many processes must comply with internal controls, regulations, and policies. A purchase may require approval based on its value. A sensitive case may need specific review. A payment should not be completed without certain validations.
Process mining allows you to compare actual performance with the expected model. The organization can identify instances where a required activity was omitted, an incorrect sequence was followed, or a time limit was exceeded.
This capability transforms compliance. Instead of reviewing small samples after events have occurred, the company can observe deviations more continuously and prioritize those with the highest risk.
Not all deviations indicate fraud or noncompliance. Some may reveal that the policy is too complex or that the system forces users to work outside the official workflow.
The evidence allows us to distinguish between legitimate exceptional behavior and a control weakness. It also facilitates the design of automations that incorporate validations from the outset.
Compliance ceases to be merely a post-audit and begins to become an observable property of the process.
When each team can freely select languages, vendors, protocols, and patterns, the organization can end up with an ecosystem that is too diverse to operate effectively. Unrestricted autonomy creates duplication, increased costs, and support difficulties.
Composable governance establishes minimum standards. It defines how APIs are designed, how contracts are versioned, what identity mechanisms are used, how events are published, and what information observability should include.
These standards don't need to eliminate all local decisions. Teams can maintain autonomy within approved technology pathways. The internal platform can offer templates, pipelines, security components, and reusable services.
Effective governance makes the recommended option the easiest one. If complying with the rules requires weeks of paperwork, teams will create parallel integrations to move forward.
Modularity needs freedom to evolve, but also agreements that allow components to collaborate. Without common contracts, composability becomes a collection of pieces that don't fit together.
A component can be built in any language or platform, but its consumers depend primarily on its contract: available operations, data, errors, availability, and behavior.
When teams change these contracts without managing compatibility, the supposed independence disappears. Each update requires coordinating multiple consumers, and deployments become coupled again.
APIs need versioning strategies. Events require schemas and evolution rules. Shared data needs clear definitions. Teams need to know what changes they can make without affecting others.
Microsoft includes versioning and the relationship between APIs and domains among the essential decisions of microservices design.
A stable contract doesn't mean it can never change. It means that changes are managed through compatibility, new versions, transition periods, and communication.
Composable architecture doesn't just depend on separating code. It depends on creating sufficiently robust technical and organizational agreements so that each part can evolve without surprising the others.
In a monolithic system, an operation can be executed within a single process. In a distributed architecture, a request can traverse APIs, queues, events, functions, and services.
If each component records information in isolation, investigating a problem becomes complex. The team knows that all services are available, but the client still doesn't receive the expected result.
Composable architecture requires end-to-end traceability. Correlation identifiers, metrics, logs, and distributed traces allow the reconstruction of an operation's path.
This visibility is also necessary for AI agents. The company needs to know what tools the agent used, which services responded, and where an incorrect decision occurred.
Modularity shifts some of the complexity from the code to the interaction between components. Observability is the mechanism that allows this complexity to be managed.
An architecture is not truly composable if no one can understand how its pieces behave when they work together.
In a distributed architecture, each new API, event, or service expands the interaction surface. Managing security independently for each component leads to inconsistent policies and increases the likelihood of errors.
The organization needs common capabilities for identity, authentication, authorization, secrets management, encryption, auditing, and API protection.
Gartner points out that heterogeneous environments require modular access control architectures and specific practices for machine identities that consume APIs.
This is especially relevant for agents and automation. Each agent should have a distinct identity and permissions related to its role. The architecture's capabilities must validate who is making the request, what operation they are trying to execute, and within what context.
Security should not be added after components are published. It should be part of your contracts and the platform that exposes them.
Safe composability allows reusing functions without reusing excessive permissions.
Not all organizations need a profound transformation. However, there are clear signs of architectural rigidity.
A company should review its design when launching a new channel requires duplicating logic, each integration requires modifying multiple systems, or a minor update needs to coordinate numerous teams. It should also review its design when data can only be obtained through direct queries, applications rely on manual processes, or the organization cannot replace a tool without impacting the entire operation.
Another red flag appears when each AI initiative needs to build its own connectors to access the same enterprise capabilities. This indicates that the company has applications, but not a reusable service layer.
The answer should not be to immediately fragment the entire ecosystem. First, capabilities, dependencies, and strategic objectives need to be identified.
Composable architecture must solve specific problems: accelerate releases, facilitate integrations, modernize a system, enable agents, or reduce the impact of changes.
Modularity generates value when it responds to a real need for evolution.
The first step is to create a map of the current ecosystem. The company must identify critical applications, data, integrations, owners, and processes. This analysis reveals hidden dependencies and components that pose the greatest risk.
Next, select a business capability with high demand for change. This could involve customers, orders, payments, authentication, or notifications. The team defines its boundaries, users, and contract.
Modernization can begin by exposing an API, publishing events, or creating a separate module. There's no need to rebuild the entire system. Each new capability should demonstrate that it reduces time, risk, or duplication.
Standards for security, observability, documentation, and versioning must also be established. Without these foundations, each module will evolve in an incompatible way.
The company can continue extracting capabilities according to priority. Some will remain within the existing system, others will be transformed into standalone services, and some may be acquired through external platforms.
Compostable architecture is not a project with a final date. It is the ability to evolve continuously without losing control.
In The Cloud Group We help organizations modernize their architecture, integrate systems, and turn business capabilities into reusable services ready for applications, automation, and AI agents.
Our approach begins by understanding existing processes, systems, data, and dependencies. We don't recommend microservices, APIs, or cloud platforms as one-size-fits-all solutions. We select the appropriate patterns based on complexity, team, and business objectives.
We design API-first architectures, integrations, events, internal platforms, custom software, and incremental modernization strategies. We also incorporate security, observability, governance, and cost control from the design stage.
The goal is not simply to replace outdated technology. It's to build a foundation that allows for launching new experiences, connecting tools, and adapting processes without starting from scratch for each initiative.
Because modern architecture is not necessarily the one that uses the most technology.
It is what allows the company to change direction without all its software becoming an obstacle.
It's an approach that organizes business applications and capabilities as modular, interoperable, and replaceable components. These building blocks can be combined to create products and processes without rebuilding the entire ecosystem.
No. Microservices can be part of a composable architecture, but they are not mandatory. A modular monolith, APIs, events, and managed services can also be used.
This means first designing the contract through which other systems will consume capacity. The implementation is then built, respecting previously defined operations, data, errors, and evolution rules.
It's a model where systems publish events when a change occurs, and other components react in a decoupled manner. For example, a confirmed payment event can trigger billing, inventory, and notifications.
Yes. It allows for gradual modernization through APIs, events, and progressive extraction of capabilities, avoiding replacing the entire platform in a single project.
No. Microservices can introduce unnecessary complexity to small systems or small teams. A modular monolith can be a more efficient option when it offers clear boundaries and ease of maintenance.
It exposes business capabilities through controlled tools and contracts. Agents can query data or execute specific actions without directly accessing entire systems.
It can increase operational complexity, network dependencies, partial failures, and difficulty of monitoring. That's why it needs automation, traceability, security, standards, and clear ownership.
Using indicators such as time to launch features, ease of integration, deployment frequency, reduction of duplication, impact of changes, and ability to replace components.
For years, many companies built applications to solve specific needs. Each system served a purpose, but also created new dependencies. Over time, the ecosystem began to resist any modification.
Compostable architecture proposes a different way of evolving. Instead of rebuilding all the software when a new need arises, the company uses modular capabilities, APIs, and events that can be combined in various ways.
This approach doesn't require converting every application into a microservice or immediately replacing legacy systems. It allows for gradual modernization, starting with areas where technological rigidity directly impacts the business.
Composability also prepares the organization for Artificial Intelligence. Agents need clearly defined tools, data, and operations. A company with reusable capabilities can connect them securely and in a controlled manner. A company with closed systems will have to build ad hoc integrations for each new case.
Architecture should not be designed solely to support current operations. It must enable the organization to respond to changes it cannot yet predict.
Because digital transformation is not about replacing a rigid platform with another that appears more modern.
It consists of building a company capable of evolving without having to dismantle itself every time the market changes.
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