Posts Tagged azure

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#.

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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.

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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.

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Itay Podhajcer is Chief Architect at Velocity Career Labs and a highly experienced software development and technology professional, consultant, architect & project manager. He shared his article on building an Azure serverless cluster for deploying RabbitMQ with C#. The original article was published here.

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We are happy to announce the release of a new major version of the Pulumi Azure provider. Pulumi Azure 2.0 is based on the 2.0 release of the upstream provider and brings several improvements and breaking changes.

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Here at Pulumi, everyone on our engineering team is a Gopher. Go has quickly become the “language of the cloud,” and so when we chose to build our open-source pulumi/pulumi engine and SaaS backend, we chose Go. As such, we are very excited to welcome Go to the family of supported infrastructure as code languages as part of Pulumi 2.0.

What is Pulumi?

Go has become the lingua franca of cloud-native infrastructure development. From projects like Docker, to Kubernetes, the community has embraced Go. The result is an ecosystem rich in tooling and packages designed for systems and cloud engineering.

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In an earlier article, we introduced examples of Policy as Code to prevent two of the most common causes of data breaches. Policies are the guardrails of infrastructure. They control access, set limits, and manage how infrastructure operates. In many systems, policies are created by clicking on a GUI, making it difficult to replicate or version. Pulumi implements policy by writing it in Typescript, which ensures that you can write policies using software development practices such as automated testing, deployment, and version control.

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Running Kubernetes in production can be challenging. This past year, Pulumi has collected common patterns of usage informed by best practices for provisioning Kubernetes infrastructure and running containerized applications. We call this Pulumi Crosswalk for Kubernetes: a collection of playbooks and libraries to help you to successfully configure, deploy, and manage Kubernetes in a way that works for teams in production.

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Azure Functions is a managed service for serverless applications in the Azure cloud. More broadly, Azure Functions is a runtime with multiple hosting possibilities. KEDA (Kubernetes-based Event-Driven Autoscaling) is an emerging option to host this runtime in Kubernetes.

In the first part of this post, I compare KEDA with cloud-based scaling and outline the required components. In the second part, I define infrastructure as code to deploy a sample KEDA application to an Azure Kubernetes Service (AKS) cluster.

The result is a fully working example and a high-level idea of how it works. Kubernetes expertise is not required!

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In a previous blog post, I shared how easy it is to create a globally distributed, highly-available, low-latency application with Azure Functions, Azure Cosmos DB, and Pulumi.

Today, I want to show how the same approach can be generalized for any cloud compute service, including containers, virtual machines, and serverless functions.

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