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FlowX.AI is built on a modern microservices architecture, allowing for scalable, resilient, and flexible deployments. Each microservice operates independently while collaborating with others to provide a complete enterprise solution.

Deployment strategy

Deploying FlowX.AI microservices involves breaking down the application into modular components that can be independently deployed, scaled, and maintained. All microservices are delivered as Docker containers, making them suitable for deployment on any container orchestration platform, such as Kubernetes or Docker Swarm.

Deployment prerequisites

Before beginning the deployment process, ensure you have:
  • A Kubernetes cluster or Docker environment
  • Access to a container registry
  • Persistent storage for databases
  • Network policies configured for inter-service communication
  • Resource quotas and limits defined for each environment
Following the correct installation sequence is crucial for a successful deployment. This ordered approach prevents dependency issues and ensures each service has the required dependencies available when it initializes.
1

Infrastructure Components

First, deploy the foundational infrastructure:
  • Databases: PostgreSQL/Oracle for relational data, MongoDB for document storage
  • Message Broker: Kafka and ZooKeeper
  • Caching: Redis
  • Identity Management: Keycloak or other OAuth2 provider
2

Core Components

Next, deploy these core services in order:
  1. Advancing Controller: Manages process advancement and orchestration
  2. Process Engine: Handles business process execution and state management
3

Backend Services

Once the core components are operational, deploy these services (can be deployed in parallel):
  • Admin Service: Platform administration and configuration management
  • Audit Core: Compliance auditing and activity tracking
  • Task Management: Human task assignment and workflow
  • Scheduler Core: Job scheduling and time-based operations
  • Data Search: Indexing and searching capabilities
  • Events Gateway: Event routing and processing
  • Document Plugin: Document generation and management
  • Notification Plugin: Communication and alerts management
  • Any additional plugins or extensions
4

Frontend Components

Finally, deploy the frontend services:
  • Designer: Process design environment for business analysts
  • Web Components: UI components for custom applications
  • Customer-facing UIs and portals

Environment variables reference

Environment variables are the primary configuration mechanism for FlowX.AI microservices. They provide a secure and flexible way to customize service behavior without modifying the container images. The following sections detail the most commonly used environment variables across FlowX.AI microservices. For service-specific variables, refer to the dedicated setup guides for each component.

Authorization & access management

*Required for some services that need to make authenticated calls to other services

Database configuration

PostgreSQL/Oracle

*Required only for Oracle databases

MongoDB (NoSQL)

*Required if runtime MongoDB connection is enabled

Kafka configuration

Redis configuration

Logging configuration

Deployment best practices

High availability considerations

For production environments, configure these high availability features:
  • Database Clustering: Implement PostgreSQL/Oracle with replication
  • MongoDB Replica Sets: Deploy MongoDB as a replica set with at least 3 nodes
  • Kafka Clustering: Use at least 3 Kafka brokers with replication factor ≥ 3
  • Redis Sentinel/Cluster: Configure Redis for high availability
  • Service Replicas: Run multiple instances of each microservice
  • Load Balancing: Implement proper load balancing for service instances
  • Affinity/Anti-Affinity Rules: Distribute service instances across nodes

Security recommendations

Secure your FLOWX.AI deployment with these measures:
  1. Network Segmentation: Isolate microservices using network policies
  2. Secret Management: Use Kubernetes Secrets or a vault solution
  3. TLS Everywhere: Enable TLS for all service-to-service communication
  4. OAuth2 Scopes: Configure fine-grained OAuth2 scopes for services
  5. Resource Isolation: Use namespaces and pod security policies
  6. Regular Updates: Keep all components updated with security patches
  7. Audit Logging: Enable comprehensive audit logging via the Audit Core service

Troubleshooting

Common issues and solutions

Diagnostic procedures

When troubleshooting FlowX.AI microservices:
  1. Check Service Logs: Examine logs for error messages
  2. Verify Configurations: Ensure all required environment variables are set correctly
  3. Test Connectivity: Verify network connectivity between services
  4. Monitor Resources: Check CPU, memory, and disk usage
  5. Inspect Kafka Topics: Use Kafka tools to inspect message flow
  6. Review Database State: Examine database for data integrity issues
  7. Check OAuth2 Tokens: Verify token validity and permissions

Service-specific documentation

For detailed configuration of individual services, refer to:

Process Engine Setup

Admin Setup

Task Management Setup

Scheduler Core Setup

Data Search Setup

CMS Setup

Events Gateway Setup

Advancing Controller Setup

Application Manager Setup

Integration Setup

Runtime Manager Setup

Notifications Plugin Setup

Documents Plugin Setup

Last modified on November 4, 2025