All modern software is cloud software, and it’s more than likely that it runs on Kubernetes. Developers are faced with the challenge of deploy applications composed of many microservices. And each microservice adds to the complexity of the deployment.
This article reviews the different methods for deploying applications on Azure Kubernetes Service (AKS).
History lesson time! In 2011, microservices debuted as an architectural style suited for the cloud. In 2013, Docker simplified building containers. Combining containers and microservices sparked a change in how applications were built and distributed in the cloud. As performance, scaling, and reliability became an increasing concern, container orchestration platforms became widely available. Kubernetes became the dominant container orchestration through community and corporate support, and some have suggested it was inevitable. Every major cloud service provider, including Azure, offers a version of Kubernetes.
Kubernetes streamlines container deployment and management, making applications scale and accessible. This article demonstrates configuring and deploying Kubernetes with Azure.
Static web applications are a popular way to publish websites. There are many reasons for adopting static web applications, including speed, security, version control, scalability, and reduced cost.
This article goes into depth about the two types of static web applications that Azure offers. The first uses Azure Blob Storage to serve static data. The second method is Azure Static Web Apps which follows the pattern of Jamstack applications that use a static website generator integrated with source control that publishes to a Content Delivery Network. We’ll take an in-depth look at both methods and consider the pros and cons of each.
The previous article was a deep dive into virtual machines. First, we used the Azure Portal to create and deploy a virtual machine; then, we repeated the process using infrastructure as code. We further demonstrated how to automate provisioning as part of cloud engineering’s build and deploy processes.
This article will explore the other end of the cloud infrastructure with serverless, which is an on-demand, fully-managed cloud architecture.
So you want to be an Azure dev and all-around infrastructure wizard? Let’s start with the basics, virtual machines! In the previous article, the common use case for virtual machines is migrating applications from dedicated hardware. You want full control of the machine to install required software for the application or configure storage and networking.
Azure provides many ways to create and configure virtual machines ranging from the Azure CLI to the Azure Portal. In this article, we’ll first create a virtual machine using the portal to understand the requirements and process; then, we’ll do it with code using Pulumi’s Azure Native provider, which is built directly from the Azure Resource Manager API.
The Azure cloud platform includes over 200 products and cloud services. Wherever you are in your Microsoft cloud engineering journey, you should be familiar with these top 5 cloud tasks that are essential building blocks commonly used to deploy applications and infrastructure to the Azure cloud.
In this series of articles, we’ll go in-depth on virtual machines, Azure Functions, static websites, building an Azure Kubernetes Service cluster and deploying applications on AKS, and DevOps with Azure App Service.
Last September, we announced the beta release of Pulumi Azure NextGen: a new Microsoft Azure provider for Pulumi that combines same-day access to the entire Azure API surface with the excellent Pulumi experience you know and love, including version-less resources, auto-naming, and auto-location.
Today, we’re excited to announce that this new provider is now the default way to manage Azure resources with Pulumi. We’re also excited to announce its final name: the native Azure provider for Pulumi, or “Azure-Native” for short. You can get started with the new provider using our newly-updated getting started guide.
Azure Synapse is an integrated analytics service that combines enterprise data warehousing of Azure SQL Data Warehouse and Big Data analytics of Apache Spark. Azure Synapse is a managed service well integrated with other Azure services for data ingestion and business analytics.
You could use the Azure portal to get started with Azure Synapse, but it can be hard to define sophisticated infrastructure for your analytics pipeline using the portal alone, and many users need to apply version control to their cloud configurations.
The alternative is to use an infrastructure as code tool to automate building and deploying cloud resources. This article demonstrates how to provision an Azure Synapse workspace using Pulumi and general-purpose programming languages like Python and C#.
This article demonstrates how to deploy and provision a virtual machine in Azure using the Pulumi Azure-Native provider. While there are numerous examples of using the Azure console, the Azure CLI, or ARM templates to deploy and provision virtual machines, we’ll use Python to implement a repeatable deployment.
We are excited to announce the beta release of a next generation Microsoft Azure provider for Pulumi. Azure has been a rapidly growing cloud platform among Pulumi users over the last year, and with the next generation Azure provider, we are doubling down on providing the best support possible for the Azure platform in Pulumi. We designed the new provider to expose the entire API surface of Azure to developers and operators, now and forever.
The new Azure provider for Pulumi (azure-nextgen) works directly with the Azure Resource Manager (ARM) platform instead of depending on a handwritten layer as with the previous provider. This approach ensures higher quality and higher fidelity with the Azure platform.