Q-Cloud is a No Code platform for deploying cloud infrastructure resources. We are thrilled to announce the support for Azure native resources. Q-Cloud can be used to deploy resources across AWS and Azure. Besides deploying infrastructure resources such as Virtual Networks, Virtual Machines, Security groups and access control lists, and Load balancer etc., Q-Cloud now supports deploying PaaS services.
Azure App Service is an HTTP-based service for hosting web applications, REST APIs, and mobile back ends in various languages including .NET Core, Java, Ruby, Node.js, PHP, or Python. Azure App Service provides pre-defined application stacks with support for various languages.
If you cannot find any predefined stack in App Service that suits you, you can use and deploy a custom Docker image to run the web app on an application stack. In this blog (and the accompanying details on the documentation site), we will walk you through to deploying a custom docker image to Azure App Service.
Even though you can use the Azure portal to deploy the App Service manually or develop an ARM template, deployment using Q-Cloud make it relatively easier to deploy and maintain the infrastructure components.
The following are the high-level steps:
1. Pre-requisites include Azure account, subscription, container registry, and the appropriate credentials
2. Build and upload a custom docker image to the Azure Container Registry
3. Create a Q-Cloud stack with a Resource Group, Azure App Service Plan and a Web App
4. Define connections and properties for each of the components
5. Deploy and test
Refer to the documentation here for the detailed steps:
The following diagram depicts the resources on the canvas.
Q-Cloud now supports Azure in addition to AWS as the cloud provider. In Summary, Q-Cloud accelerates the deployments and reduces the effort and cost involved in cloud deployments. Q-Cloud specifically provides the following advantages over other method of deployments:
1) Allows one to visualize the desired stack and to view the various dependencies
2) Automatically generates the appropriate code (in Typescript) when the stack is deployed and can store the code in GitHub repository.
3) When you are deploying a greenfield environment, as the resources may not exist yet in Azure, Q-Cloud allows to define the resource properties as variables and pass the appropriate output properties when created to the dependent components. This is done using the "Connections" object in Q-Cloud. This is equivalent to defining variables programmatically.
4) Q-Cloud allows a stack to be stored as a reusable template. The template can be used to create a new stack with different properties, backup and recovery purposes and promote the app to various application environments such as Dev, Test and Prod.
5) Adds pre-defined tags (system and/or user defined) automatically as part of a policy to all resources that are deployed.
6) Q-Cloud deployments can be subject to security policies to maintain the desired security posture. This capability works in conjunction with the Pulumi security policies feature.
You can get started with Q-Cloud using a set of Docker containers in your choice of the infrastructure or the marketplace appliance in AWS. We will be soon releasing the appliance in Azure marketplace.
The AWS marketplace appliance for "Developer Edition" is here: