Difficulty: Beginner
Estimated Time: 60 minutes

Macrometa supports Serverless functions created using C#, Go, Node, Python 2, Python 3, Ruby and the ability to provide a custom Dockerfile definition. The multi-language support provides you with out-of-the-box flexibility to match your skills and preferences.

The scenario explains:

This scenario explains how to deploy Serverless functions that are available across the global fabric, reducing latency and increasing reliability.

  • Create Python Function

  • Deploy Function to Fabric

  • Execute Function

  • Update Function code and Redeploy changes

  • Scale functions to match your requirements

In this scenario you learned how to deploy Serverless functions that are available across the global fabric, reducing latency and increasing reliability.

You completed:

  • Creating a Python Function

  • Deploying Function to Fabric

  • Executing Function

  • Updating Function code and Redeploy changes

  • Scaling functions to match your requirements

Deploying Serverless Functions at the Edge

Step 1 of 8

Understanding Serverless

According to Wikipedia, "Serverless computing is a cloud-computing execution model in which the cloud provider runs the server, and dynamically manages the allocation of machine resources". The aime of Serverless is to remove the overhead of managing and scaling of the underlying infrastructure, allowing focus to shift to the application and business value.

Within the concept of Serverless is a category of Functions as a Service (FaaS). FaaS enables the creation of focused building blocks that can be executed without the the complexity of building and maintaining the infrastructure. These functions can solve very targeted problems in various languages to give you flexibility and increased velocity.