AWS App Runner and Google Cloud Run are two serverless computing platforms that can help you deploy and run containerized applications without having to worry about servers. Both platforms are relatively new, but they have quickly become popular choices for developers. What are the similarities? Both platforms are serverless, meaning that you don’t have to provision or manage servers. The platforms will automatically scale your application up or down based on demand, so you only pay for the resources that you use.

Google Cloud Dataflow and Azure Stream Analytics are both cloud-based streaming data processing services. They offer similar features, but there are some key differences between the two platforms. Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. It is designed to scale automatically based on the data processing needs. Dataflow also offers various security features including IAM (Identity and Access Management), encryption, and audit logging.

Azure networking and GCP networking are both comprehensive cloud networking services that offer a wide range of features and capabilities. However, there are some key differences between the two platforms. Azure networking offers a more traditional networking model, with a focus on virtual networks (VNets), subnets, and network security groups (NSGs). VNets are isolated networks that can be used to group together resources, such as virtual machines (VMs), storage, and applications.

There are a few ways to monitor costs in Azure. One way is to use the Azure Cost Management + Billing portal. This portal provides a graphical interface that you can use to view your costs over time, track your spending against budgets, and identify areas where you can save money. Another way to monitor costs is to use the Azure Cost Management API. This API allows you to programmatically access your cost data and integrate it with other systems.

Here is a Terraform file that you can use to create a Kubernetes cluster in Azure: provider "azurerm" { version = "~> 3.70.0" subscription_id = var.azure_subscription_id client_id = var.azure_client_id client_secret = var.azure_client_secret tenant_id = var.azure_tenant_id } resource "azurerm_resource_group" "aks_cluster" { name = var.resource_group_name location = var.location } resource "azurerm_kubernetes_cluster" "aks_cluster" { name = var.aks_cluster_name location = azurerm_resource_group.aks_cluster.location resource_group_name = azurerm_resource_group.aks_cluster.name node_count = 3 vm_size = "Standard_D2s_v3" network_profile { kubernetes_network_interface_id = azurerm_network_interface.