Use the MySQL Executer module to execute any SQL command directly within your workflow, making it an excellent tool for a variety of database management tasks.

1. environment:
2. - TZ = Europe/Stockholm"

With the Data Trigger module you can monitor any number of data sources and trigger actions based on the data. The module uses a list of trigger definitions to analyze the data. When new data is received the trigger conditions are validated and when the conditions for a trigger are met an output message is sent. These messages can then be used to trigger actions, like creating a work order or sending a notification.

All Crosser modules can keep messages until successfully delivered. To enable this feature you need to set the ‘Max Number of Retries’ setting to a value larger than the default 0.

Maintain a stable, efficient, and secure production environment while enabling a dynamic and flexible space for development activities.

There is no automatic scaling but processing can be split over multiple nodes by for example selecting subsets of data using filter conditions or separate by data sources.

One of the great benefits with Crosser is the performance, tests show that we can process >100 000 messages per second on a pretty basic VM. A Raspberry Pi3 can process about 8000 messages per second.

In this article we describe what options you have and how to utilize provided interfaces for integration into your monitoring solution.

Split your use cases into smaller Flows and bind them together with the concept of Flow-to-Flow communication.

Explore how to maximize the efficiency of your data management with Node-to-Node communication.