Introduction
Microsoft Azure or Azure is a cloud computing service provided and operated by Microsoft for application management. It provides services such as Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and Software as a Service (SaaS) that can be utilized for analytics, virtual computing, storage, and networking. After the brief overview of Azure, let us now understand the app services, functions, and logic applications provided by Azure.
Azure App service
Azure App Service is a Platform as a Service (PaaS) provided by Microsoft. Azure App Service lets you easily create enterprise-ready web and mobile apps for any platform or device and is used to host web applications, REST API, and backend services for mobile applications. Name any programming language or framework, be it .NET, .NET Core, Java, Ruby, Node.js, PHP, or Python, web applications and services that are developed using any of the following languages above can be hosted using the Azure app service.
The Azure App Service enables you to easily create Web + Mobile + Logic + API Apps:

Public preview limitations
The following public preview limitations apply to App Service Kubernetes environments. This list of limitations is updated as changes and features are made available.
| Limitations | Details |
| Supported Azure regions | East US, West Europe |
| Cluster networking requirement | Must support LoadBalancer service type |
| Cluster storage requirement | Must have cluster attached storage class available for use by the extension to support deployment and build of code-based apps where applicable |
| Feature: Networking | Not available |
| Feature: Managed identities | Not available |
| Feature: Key vault references | Not available (depends on managed identities) |
| Feature: Pull images from ACR with managed identity | Not available (depends on managed identities) |
| Feature: FTP publishing | Not available |
| Logs | Log Analytics must be configured with cluster extension; not per-site |
Pods created by the App Service extension
The following table describes the role of each pod that is created by default:
| Pod | Description |
| <extensionName>-k8se-app-controller | The core operator pod that creates resources on the cluster and maintains the state of components. |
| <extensionName>-k8se-envoy | A front-end proxy layer for all data-plane requests. It routes the inbound traffic to the correct apps. |
| <extensionName>-k8se-activator | An alternative routing destination to help with apps that have scaled to zero while the system gets the first instance available. |
| <extensionName>-k8se-build-service | Supports deployment operations and serves the Advanced tool features. |
| <extensionName>-k8se-http-scaler | Monitors inbound request volume in order to provide scaling information to KEDA. |
| <extensionName>-k8se-img-cacher | Pulls placeholder and app images into a local cache on the node. |
| <extensionName>-k8se-log-processor | Gathers logs from apps and other components and sends them to Log Analytics. |
| placeholder-azure-functions-* | Used to speed up cold starts for Azure Functions. |
Advantages of Azure App services
Fully managed environment
App Service automatically maintains and patches the Operating system and language frameworks for you. This leads to get you more time to focus on designing, developing and maintaining your application and data.
Compliance
App Service is SOC (Service Organization Controls), ISO (International Organization for Standardization), and PCI (Payment Card Industry) compliant.
Security
We can authenticate users with Azure Active Directory or any of the external authentication providers like Google, Facebook, Twitter, or Microsoft.
Supports multiple programming languages and frameworks
App Service provides a wide variety of programming languages and frameworks such as .NET, .NET Core, Java, Ruby, Node.js, PHP, Python.
Scalability
App Service can scale your resources up and down or in and out, based on the demand for your application. We can do this either manually if you want to or automatically based on metrics like CPU utilization for example.





