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The standard layers of PIPEFORCE
There are standardenterprise standard enterprise grade layers, any business solution must address to seamless integrate, run and scale inside an enterprise, so PIPEFORCE does.
Usually, for any of these layers at least one technical expert and sometimes also a bigger team of software engineers and technical experts is required to implement and/or maintain the specific layer. But since PIPEFORCE is a turnkey solution, most of these layers are already covered by the maintenance subscription fee without extra cost or can be easily implemented and maintained by non-technical users using our Low Code, No Code and AI toolings.
Below you can find a mapping from these the enterprise standard layers to the sections in the documentation for faster navigation.
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Manages business logic and rules for data processing. Deals with processing operations on data, including computation and applying logic. Handles document evaluation, extraction, and processing, applying business logic and rules.
In PIPEFORCE:
Data Pipelines
Functions
Data Access Layer
Responsible for data management and interaction with internal and external databases.
In PIPEFORCE:
Integration Layer
Facilitates communication between different systems and services, often through APIs or middleware.
In PIPEFORCE:
Workflow Layer
Coordinates stateful processes and workflows where manual steps and interactions with humans are required within the system.
In PIPEFORCE:
Workflow Service (Camunda)
Workflow Designer
TaskviewWorkflows (BPMN)
Security and Management Layer
Focuses on authentication, authorization, encryption, logging, and security management.
In PIPEFORCE:
Log Service
Log View
OAuth via KeyCloak
Microservice Layer
Manages and provides services used by the application or other systems.
In PIPEFORCE:
services.* commands in order to start / stop microservices
Services UI
Microservice Layer
Provides a runtime environment to execute, scales and manage microservices and containers.
Application Infrastructure Layer
Provides the infrastructure necessary for the application, including servers and cloud services.
In PIPEFORCE:
KubernetesPIPEFORCE runs entirely Cloud Native inside Kubernetes.
Can by hosted on any hyperscaler (like Google Gloud, AWS or Azure for example) or OnPremises in a private cloud.
Caching Layer
Responsible for storing frequently accessed data to reduce latency.
In PIPEFORCE:
Redis
In Memory-Caching in hub
Hibernate CacheDifferent types of caches in the backend.
Orchestration Layer
Coordinates complex workflows and service interactions, often in microservice architectures.
In PIPEFORCE:
Kubernetes
Services UI
service.* commandsBuilt-in in infrastructure and backend architecture.
Reporting and Analytics Layer
Handles business intelligence, analytics, and reporting functions.
In PIPEFORCE:
Reporting FrameworkReports and Charts
Identity and Access Management (IAM) Layer
Manages user identities and controls access to system resources.
In PIPEFORCE:
IAM (KeyCloak)Authentication
Audit Layer
Captures logs and audit data for compliance.
In PIPEFORCE:
Audit Logging
https://logabit.atlassian.net/wiki/spaces/PA/pages/2548465885/Logging%2C+Tracing+and+Monitoring
Communication & Messaging Layer
Manages communication between services, often using messaging systems.
In PIPEFORCE:
RabbitMQMessaging and Events
Security Architecture Layer
Provides security mechanisms across all system layers, including encryption and SSL/TLS.
In PIPEFORCE:
HTTPS Allows only HTTPS communication with external
Encrypted storage
Encrypted secret management
https://logabit.atlassian.net/wiki/spaces/PA/pages/2548465885/Logging%2C+Tracing+and+Monitoring
Notification Layer
Manages notifications and real-time alerts for users or systems.
In PIPEFORCE:
(Push) Notification FrameworkEmailling
Monitoring and Logging Layer
Focuses on system health monitoring, performance metrics, and logging.
In PIPEFORCE:
Via Google Cloud Monitoring
Log Viewer
Commands
External Tools / connects
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Integrate external Monitoring and Logging tools via REST API.
AI Layer
The artificial intelligence (AI) layer helps to speed up implementation and operation time and helps in optimizations afterwards.
Document Understanding Components
ChatBot integrations
Data Mapping Support
Security Checks
Automated workflow creation and optimization