Posts Tagged azure

Denis Willett is a software engineer at the North Carolina Institute of Climate Studies who works on the NOAA Open Data Dissemination Program. His work focuses on leveraging cloud technologies for the development of data processing and machine learning pipelines. Denis did his PhD in Entomology and Nematology at University of Florida and his undergraduate and masters work in Earth Systems at Stanford University. You can read his full bio here.

NOAA Open Data Dissemination (NODD) makes environmental data freely and publicly accessible across Amazon Web Services (AWS), Microsoft Azure (Azure), and Google Cloud Platform (GCP). These data include near real-time satellite imagery, weather models, radar feeds, drought information, ocean databases, and a suite of climate data records among many others. This program supports more than 220 datasets and over 24PB of open data. Since its inception, the program has been growing rapidly, almost doubling in size over the past year.

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Deploying a static website often involves provisioning a number of pieces of infrastructure and stitching those pieces together in a way to make the site accessible to your users. A static website typically consists of HTML, CSS, and JavaScript files along with any other static assets the site might need to render such as PNG and SVG files for example. These files are then uploaded to a storage bucket where they can be served from.

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At PulumiUP 2022, Tomas Jansson, software architect at Elkjøp Nordic, gave a presentation on how to enable developers to self-service infrastructure by using Pulumi’s Automation API. Elkjøp Nordic is the leading consumer electronics retailer in the Nordics. The company sells consumer electronics, mobile phones, computers, white goods, domestic appliances, and services linked to these products both directly to consumers and to businesses. It is an omnichannel retailer and serves customers both online and through more than 400 stores.

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Today, Microsoft announced a new general-purpose serverless container platform: Azure Container Apps. Container Apps is a fully managed platform for microservice applications that runs on top of Kubernetes and open-source technologies like KEDA, Envoy, and Dapr.

Container Apps are designed to abstract infrastructure management with flexible serverless containers. Developers can run containers at scale without the burden of standing up and managing a Kubernetes cluster manually.

We are happy to announce same-day support for Azure Container Apps in the Pulumi Azure Native Provider, which covers 100% of the Azure Resource Manager APIs and gives you highest fidelity integration with Azure’s resources.

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Containers have emerged as one of the de facto standards for running software. When adopted with the right mindset, they can drastically improve the development lifecycle and help to close the loop between local development and running your applications in the cloud.

If you’re at the stage of trying to run your application in Microsoft Azure, the choices can be overwhelming. The Azure Container product page lists 7 different products on their landing page, and for new users it can often be difficult to decide which of the myriad products is right for their use case. What can make it even more confusing is that often these container services can be interoperable, meaning you can use one container product from another!

In this post, we’re going to examine each of the main container services offered in Azure and then examine what they’re good for and what they might not be so good for. Let’s take a look!

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What comes to mind when you hear DevOps? Frequently, DevOps is described as a cultural practice that enables an organization to deliver high-quality applications quickly. The DevOps model emphasizes the “breaking down of silos” and combining development and operations into a single team. Developing, deploying, and maintaining an application is the responsibility of both developers and operators across the application lifecycle.

DevOps processes rely on tooling to automate delivering and maintaining applications. This article demonstrates how to implement Azure Pipelines to build and deploy applications.

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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).

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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.

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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.

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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.

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