Architecture of Autom Mate
Explains the structural design of Autom Mate, focusing on its components and how they interact to facilitate automation.
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Explains the structural design of Autom Mate, focusing on its components and how they interact to facilitate automation.
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Autom Mate's architecture is built on an Automation and Integration platform, designed to automate and streamline business processes effectively. This robust architecture consists of two primary components:
Autom Center
Mate Agent
Autom Center is designed to be user-friendly and accessible to both technical users and citizen developers (non-technical users). It includes the following key modules:
This is a visual tool that allows users to design automation workflows using . Users can create and visualize workflows by arranging (such as sending an , updating a , or calling an ) and connecting them to define the sequence of operations. This approach simplifies the creation of complex automation processes without requiring extensive coding knowledge.
is a critical component of Autom Mate, operating on the server side. It consists of a microservice infrastructure that includes:
Autom Mate provides flexibility in deployment by offering three deployment types: Cloud, Hybrid, and On-Premises. Each type is tailored to meet different infrastructure and operational requirements.
The Cloud Deployment leverages the robust infrastructure of Amazon Web Services (AWS).
In this model, both Autom Center and Mate Agent are fully hosted and managed in AWS.
This option is ideal for users seeking a fully cloud-based solution that eliminates the need for maintaining local infrastructure.
The architecture ensures high availability, scalability, and secure access via AWS services.
Architecture of the Cloud Deployment.
The Hybrid Deployment combines the benefits of cloud and on-premises environments:
Autom Center is hosted on AWS, ensuring centralized management, security, and cloud-based scalability.
Mate Agent, however, is installed locally on the user's Local Server or in the user's own cloud environment.
This approach is ideal for organizations that require local processing for specific tasks or need to comply with data sovereignty or privacy regulations while benefiting from cloud-based management.
Architecture of the Hybrid Deployment.
The On-Premises Deployment provides the highest level of control for end-users who prefer to manage everything within their own infrastructure:
Both Autom Center and Mate Agent are installed on the end-user's Local Server or private cloud environment.
To enable logging functionality, the end-user must also install Elasticsearch within their environment.
This implementation is best suited for organizations with strict compliance, security, or operational requirements that demand full control over their data and systems.
Architecture of the on-premises deployment.
User Interaction
The Autom information, which includes details about the actions to be performed and the sequence of operations, is sent to the backend operation via a REST API call.
Backend Processing
The backend handles initial validations, data transformations, and any necessary preliminary steps to set up the Autom for execution.
Data Transfer
Autom Distribution
The microservices handle tasks such as interacting with external systems, processing data, and performing specific automation actions as defined in the Autom.
Real-Time Monitoring
Real-time monitoring allows users to track the execution of Autom, view logs, and receive alerts for any errors or issues. This ensures that users are always informed about the state of their automation processes and can take corrective actions if needed.
REST API Call Limit: Be mindful of API rate limits or restrictions, as frequent Autom triggers may impact backend processing speed.
Data Format Requirements: Ensure data sent for backend processing meets the required format; incompatible formats can lead to errors or delays.
Real-Time Monitoring: Regularly check the monitoring page to track Autom progress and quickly identify any issues.
Automation Distribution: Each library microservice handles specific tasks, so monitoring individual task statuses can help pinpoint performance bottlenecks.
Error Management: Set alerts for key Autom's to catch potential errors early and ensure automation runs smoothly.
A user an from the Autom Center's user interface (UI). This can be done through a simple click or based on a predefined schedule or event.
Autom Center's backend operation receives the request and completes the preprocessing phase. This phase involves preparing the data and ensuring it is in the correct format for further processing by the .
The prepared data is transferred to the gateway using gRPC (gRPC Remote Procedure Calls), a high-performance, open-source framework for communication. gRPC ensures efficient and secure data transfer between the backend and the
The gateway distributes Autom actions to the appropriate microservices for execution. Each microservice processes its assigned task and returns the results to the gateway. This communication is also managed using gRPC, ensuring reliability and speed.
Users can the progress of their Autom in real-time from the monitoring page in Autom Center. This feature provides updates and insights into the status and performance of each task within the Autom.
These are specialized services that handle specific automation tasks, such as data processing, system integration, and action execution. Each microservice is developed, deployed, and maintained independently, allowing for easier updates and scalability. The microservices architecture ensures that the system can handle a large number of tasks simultaneously without performance degradation.
