Server-side Google Tag Manager has an excellent Preview mode, which lets you inspect incoming requests, monitor the event data object, view console messages, and identify outgoing requests, among other things. To enable this Preview mode on the web, you simply need to click the Preview button in the container, after which any requests sent from the same browser instance will be automatically shown in the Preview mode window. However, what about if you want to send requests from another browser?

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If you want to manually install server-side Google Tag Manager on App Engine in the Google Cloud Platform, you are of course welcome to do so. The main benefits of doing this are that you get to choose the region where App Engine is deployed and that you can use existing project resources instead of having a new project automatically created for you. However, to run the script without errors, there are a number of things you need to enable first.

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With asynchronous variables recently released in server-side Google Tag Manager, it’s time to dig into data enrichment flows using another release from the Google team. * drum roll * We have a new Google Cloud Platform API! It’s fast. It’s sleek. It’s beautiful. It’s Firestore! Firestore is a NoSQL, transactional, and scalable database that offers near-real-time write/read and sync operations for data. In practice, it’s a great way to enrich and widen the data that you pass through your Server container.

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OK, that’s one unappealing title for a blog post, but rest assured that the content more than makes up for this obscurity. Recently, my favorite toy in the world, Google Tag Manager’s server container, introduced the capability to handle asynchronous operations in variables. This is done through a JavaScript interface known as Promise. A Promise is a way to run code in JavaScript without knowing what its eventual value will be.

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While Google App Engine, the default implementation pattern of server-side Google Tag Manager, is straightforward to setup with the automatic provisioning steps, it’s certainly not the only way to deploy the server. You can set it up in Amazon AWS (this blog) You can set it up in Microsoft Azure (this blog) You can set it up with Cloud Run (Mark Edmondson’s blog) In fact, the manual setup guide gives you the details on how to deploy a Google Tag Manager Server in any environment that runs Docker.

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Although most of Server-side Tagging in Google Tag Manager revolves, quite rightfully, around Clients, there’s still plenty of value to be derived from tags, too. Naturally, the most common use case for server-side tags is to map the incoming requests to the Server container (filtered through Clients) and dispatch them to their respective endpoints. But in addition to dispatching HTTP requests, tags can do so much more. In this article, I’ll share with you a neat way how to utilize tags to manipulate the HTTP responses the Server container sends back to the request source.

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To continue my extensive collection of Google Tag Manager’s server-side tagging articles, in this guide I’ll walk you through how to set up a Server container in Microsoft Azure’s App Service platform. For my previous guides on manually provisioning a Server container, follow these links: Amazon AWS (Elastic Beanstalk): Deploy Server-side Google Tag Manager In AWS Google Cloud (App Engine): Provision Server-side Tagging Application Manually Azure’s App Service is similar to AWS Elastic Beanstalk and GCP App Engine, in that it lets you create a web application from scratch with minimal effort.

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