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DE-202026100981-U1 - System for unified middleware integration control with Service Bus coordination, API Gateway authentication, cloud AI prediction operations and Java-based microservices

DE202026100981U1DE 202026100981 U1DE202026100981 U1DE 202026100981U1DE-202026100981-U1

Abstract

A system (100) for the unified control of middleware integration, consisting of: a unified integration control engine (1) configured to define and enforce integration control policies for an enterprise-wide integration landscape; a service bus coordination layer (2) coupled with the unified integration governance engine (1) and configured to coordinate message handling, routing, transformation and orchestration between heterogeneous applications and services; an API gateway authentication and authorization module (3) configured to authenticate clients, authorize access to APIs and apply traffic control for the north-south API entry; a cloud AI module for predictive operations (4) configured to analyze runtime telemetry and generate predictive operational actions to prevent or mitigate integration failures; a Java-based microservices runtime layer (5) configured to provide and execute a variety of microservices that implement integration adapters and domain APLS; a compliance and audit ledger module (6) configured to store governance events and operational actions in a tamper-proof manner; and a developer self-service portal and an automation module (7) configured to publish regulated artifacts and automate onboarding and lifecycle operations, wherein the unified integration governance engine (1) distributes enforceable governance controls to at least the service bus coordination layer (2), the API gateway authentication and authorization module (3) and the Java-based microservices runtime layer (5), and wherein the cloud AI prediction operations module (4) generates at least one proactive corrective instruction that is applied to at least one of the service bus coordination layers (2) and the Java-based microservices runtime layer (5).

Assignees

  • ROY ABHIJIT

Dates

Publication Date
20260513
Application Date
20260223
Priority Date
20260223

Claims (9)

  1. A system (100) for unified middleware integration governance, consisting of: a unified integration governance engine (1) configured to define and enforce integration governance policies for an enterprise-wide integration landscape; a service bus coordination layer (2) coupled with the unified integration governance engine (1) and configured to coordinate message handling, routing, transformation, and orchestration between heterogeneous applications and services; an API gateway authentication and authorization module (3) configured to authenticate clients, authorize access to APIs, and apply traffic control for north-south API inbound traffic; a cloud AI predictive operations module (4) configured to analyze runtime telemetry and generate predictive operational actions to prevent or mitigate integration failures; a Java-based microservices runtime layer (5) configured to provide and execute a variety of microservices that implement integration adapters and domain APLS; a compliance and audit ledger module (6) configured to securely store governance events and operational actions; and a developer self-service portal and an automation module (7) configured to publish governed artifacts and automate onboarding and lifecycle operations, whereby the unified integration governance engine (1) distributes enforceable governance controls to at least the service bus coordination layer (2), the API gateway authentication and authorization module (3), and the Java-based microservices runtime layer (5), and wherein the cloud AI prediction operations module (4) generates at least one proactive corrective instruction that is applied to at least one of the service bus coordination layers (2) and the Java-based microservices runtime layer (5).
  2. System (100) according to Claim 1 , wherein the unified integration governance engine (1) comprises a policy repository (11) that stores versioned governance policies, a rule evaluation engine (12) configured to evaluate the versioned governance policies against runtime metadata, an approval workflow manager (13) configured to enforce multi-stage approvals for the deployment of integration artifacts, and a service catalog register (14) configured to maintain a catalog of the managed APIs, services, and integration flows.
  3. System (100) according to Claim 1 , wherein the service bus coordination layer (2) comprises an adapter framework (21) that provides connectors to external systems, a mediation pipeline (22) configured to perform transformations and enrichments, a canonical schema registry (23) configured to store canonical data models used for transformations, and an orchestration coordinator (24) configured to manage distributed integration transactions across multiple endpoints.
  4. System (100) according to Claim 1 , wherein the API gateway authentication and authorization module (3) comprises an identity provider interface (31), a token service (32) configured to issue or validate access tokens, a mutual TLS termination unit (33), a rate limiting and quota engine (34), and a context propagation component (35) configured to append trace and policy context to downstream calls directed to the service bus coordination layer (2) and the Java-based microservices runtime layer (5).
  5. System (100) according to Claim 1 , wherein the cloud AI predictive operations module (4) includes a telemetry collector (41) configured to collect logs, metrics, and traces to capture, a feature store (42) configured to generate prediction features from the captured telemetry data, a model training pipeline (43) configured to train prediction models using historical governance and runtime data, a prediction engine (44) configured to output predicted risk assessments for integration components, and a remediation orchestrator (45) configured to automatically initiate at least one of the following actions: rerouting, throttling, scaling, failover, or circuit isolation based on the predicted risk assessments.
  6. System (100) according to Claim 1 , wherein the Java-based microservices runtime layer (5) includes: a service register (51) configured to register microservice instances, a configuration manager (52) configured to distribute managed configurations from the unified integration management engine (1), a resilience controller (53) implementing circuit-breaking and retry policies, and a service-to-service authorization component (54) configured to enforce identity-based access between microservices.
  7. System (100) according to Claim 1 , wherein the compliance and audit ledger module (6) comprises: a hash-linked event logger (61) configured to store governance and operational events as hash-linked records, a digital signature module (62) configured to sign at least a subset of the records, a retention and legal hold manager (63) configured to enforce retention policies, and an audit query interface (64) configured to generate legally valid audit reports relating approvals, deployments, and runtime enforcement actions.
  8. System (100) according to Claim 1 , wherein the developer self-service portal and automation module (7) includes: an artifact publishing interface (71) for publishing managed APIs and integration flows, a template generator (72) configured to generate standardized integration templates for the Java-based microservices runtime layer (5), a CI/CD integrator (73) configured to control deployments based on approvals from the approval workflow manager (13), and a policy-as-code exporter (74) configured to provide machine-readable policy bundles that can be enforced by the API gateway authentication and authorization module (3) and the service bus coordination layer (2).
  9. System (100) according to Claim 1 , wherein the unified integration governance engine (1) further includes a governance assessment component (15) configured to calculate a compliance score for each integration artifact based on at least one of the following criteria: security status, data classification, dependency risk and operational safety, and wherein the cloud AI predictive operations module (4) uses the compliance score as an input feature to generate the proactive corrective instruction.

Description

INVENTION AREA The present invention relates to enterprise integration and middleware governance. In particular, the invention relates to a system for the unified governance of integration artifacts and runtime operations across a service bus coordination layer, an API gateway authentication and authorization module, a cloud AI prediction operation module (4), and a Java-based microservices runtime layer, with tamper-proof compliance tracking and developer automation. BACKGROUND OF THE INVENTION The subject matter discussed in the "Background" section should not be considered prior art solely because it is mentioned in that section. Likewise, a problem mentioned in the "Background" section or related to the subject matter of the "Background" section should not be considered prior art. The subject matter in the "Background" section merely presents various approaches, which could themselves also be inventions. Modern businesses increasingly rely on distributed digital systems that encompass legacy applications, packaged enterprise platforms, cloud-native services, mobile/web channels, partner ecosystems, and data platforms. These systems must work together seamlessly to support business processes such as customer onboarding, payments, claims, logistics, ERP synchronization, analytics, and regulatory reporting. In practice, such interoperability is achieved through integration artifacts like APIs, event streams, message queues, transformation mappings, routing rules, and orchestration workflows. As enterprise landscapes evolve, the number of integrations is growing rapidly and becoming a critical foundation for availability, security, and compliance. Traditionally, organizations implement integration using a combination of middleware components, including API gateways, service bus platforms, message brokers, and microservice runtimes. In many deployments, inbound traffic first passes through an API gateway for client authentication and basic traffic control, then through an integration coordination layer (such as a service bus) for mediation, routing, transformation, and orchestration, and finally reaches domain microservices that execute the business logic and access the underlying systems. This multi-layered approach is often used in hybrid environments that include on-premises data centers and multiple cloud accounts. As a result, operational responsibility is distributed across multiple teams, tooling stacks, and management domains. A key technical problem in such environments is fragmented governance. Security policies, API authentication rules, quotas, throttling parameters, routing restrictions, data classification controls, schema validation rules, and approval requirements are often defined and managed independently in each middleware component. For example, an API gateway might enforce authentication and rate limits, while a service bus enforces message validation and transformation rules, and microservices enforce in-code authorization and configuration restrictions. This separation leads to policy inconsistencies, inconsistent enforcement, and gaps that are difficult to detect at runtime. A change in one layer—such as a token request, schema version, or routing restriction—might not propagate correctly to other layers, potentially leading to failures or unintended disclosure. Another ongoing challenge concerns the lifecycle management of integration artifacts. Integration flows, connectors, transformation mappings, and API specifications are often created and updated under time pressure, sometimes using ad-hoc templates or team-specific standards. Without a unified governance process, artifacts can be deployed without consistent versioning, approvals, dependency mapping, or cataloging. This leads to operational uncertainty when incidents occur: it becomes difficult to determine which artifact version is active, which upstream/downstream dependencies are affected, and which rollback path is safe. Over time, duplication of integration logic increases, and "shadow integrations" emerge outside of standard governance channels. End-to-end traceability is also a major limitation of traditional implementations. Requests that traverse an API gateway, a service bus, and multiple microservices often lose their correlation context because each platform uses different tracing methods. Formats, identifiers, or propagation mechanisms are used. If an error occurs—for example, a transformation failure, a timeout in downstream systems, or a partially completed orchestration—operators may not be able to reconstruct the full transaction path or the policies applied at each hop. This reduces the efficiency of troubleshooting, increases the average recovery time, and makes it more difficult to establish accountability for policy enforcement and operational decisions. Furthermore, most operational tools in current middleware landscapes remain reactive. Monitoring systems typically only issue alerts when thresholds are ex