Connect Detrack and Microsoft Azure Functions to Build Intelligent Automations
Enable Integrations or automations with these events of Detrack and Microsoft Azure Functions
Enable Integrations or automations with these events of Detrack and Microsoft Azure Functions
Actions
Create Job
Creates a Job in the Detrack Dashboard.
List Jobs
List all jobs
Create Batch
Create multiple delivery or collection jobs in Detrack as a single batch.
Update Job
Update one or more Detrack jobs (DO numbers). Modify job date, type, address, contact, phone, notification email, tracking number, and items — any fields left blank remain unchanged.
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Frequently Asked Questions
To start, connect both your Detrack and Microsoft Azure Functions accounts to viaSocket. Once connected, you can set up a workflow where an event in Detrack triggers actions in Microsoft Azure Functions (or vice versa).
Absolutely. You can customize how Detrack data is recorded in Microsoft Azure Functions. This includes choosing which data fields go into which fields of Microsoft Azure Functions, setting up custom formats, and filtering out unwanted information.
The data sync between Detrack and Microsoft Azure Functions typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Detrack and Microsoft Azure Functions. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Detrack
Detrack is a live delivery tracking system that offers a robust Proof of Delivery system to last-mile couriers and logistics.
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About Microsoft Azure Functions
Microsoft Azure Functions is a serverless computing service that enables developers to run event-driven code without having to explicitly provision or manage infrastructure. It allows for the execution of code in response to various triggers, such as HTTP requests, database changes, or message queue events, making it ideal for building scalable and efficient applications.
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