Data science has advanced because tools like Jupyter Notebook hide complexity by running high level code for the specific problem they are trying to solve. Increasing the level of abstraction lets a data scientist be more productive by reducing the effort to try multiple approaches to near zero, which encourages experimentation and better results.

Data scientists typically work locally, but they often store data for analyses and models in the cloud. There are clear advantages to using cloud resources for these tasks:

• Data scientists generally don’t want to manage their storage and databases.
• They need to be able to store large data sets cheaply.
• They need large capacity swings available on-demand.

SDKs like AWS’ Python library, boto3, can create resources, but they still require domain expertise to manage and properly architect a solution. The Pulumi Automation API improves on raw SDKs by providing high-level abstractions for creating and managing cloud services, letting data scientists concentrate on analyses and models without being well-versed in cloud APIs.

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Policies set the guardrails for your applications and infrastructure. They define many aspects of how your company manages its applications and infrastructure. Security, safe use of resources, and compliance with external standards are just a few examples of what a policy can define.

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Currently available in public preview, Pulumi’s Automation API enables you to provision your infrastructure programmatically using the Pulumi engine. Today, we are excited to announce C# support for Automation API, enabling .NET developers to automate infrastructure deployments, create complex orchestration workflows, build custom ops tooling, and build cloud frameworks. Read more about the Automation API here.

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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.

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Guest Article: Simen A. W. Olsen is a Software Architect and Manager at Bjerk, a software development agency based in Oslo, Norway. He joins Paul Stack to talk about the new GitHub Action powered by the Pulumi Automation API.

In this article, we’ll take a look at how our GitHub Action has been re-architected to be built on top of our Automation API.

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Guest Article: Andy Davies is a Senior Software Developer at Reaktor, a tech company based in Amsterdam, New York, and Finland, writing about using the Pulumi Automation API to add observability to infrastructure provisioning.

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In this article, I’ll show how Pulumi can be used with Aiven’s services to create infrastructure that can be migrated from cloud to cloud with no downtime.

This tutorial will use Python, Pulumi, Grafana, and an AWS Lambda function to simulate recording temperature data in an InfluxDB database.

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The Pulumi Service helps teams of all sizes deliver and manage cloud apps and infrastructure. In the console, everyone on the team can see the infrastructure the team is responsible for, when it was last deployed, how it’s configured, and more. They can see a full breakdown of the infrastructure as well, so they can understand how the team brings together individual cloud services to create their applications. When you bring your teams together on the Pulumi Service, you can provide a “single pane of glass” over all the infrastructure that you manage with Pulumi.

Most teams larger than a few people define their team members, and the groups they’re a part of, using an Identity Provider (IdP) like Okta, Microsoft’s Azure Active Directory, or Google Cloud Identity & Access Management. The Pulumi Service works seamlessly with these IdPs (and many more) by providing Single Sign-On with SAML and user and group synchronization via SCIM 2.0.

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An unauthorized user gaining access to your infrastructure can be catastrophic: data can be stolen or leaked, security holes can be exploited, and more. That risk makes it critical to keep the infrastructure secrets—the passwords, access tokens, keys, and so on—well-protected. This is particularly true in automated systems, like continuous integration and delivery and infrastructure-as-code systems.

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Whether you are working with Kubernetes or serverless, your application uses containers. If you use the Docker desktop client, images are pushed to Docker Hub by default. Pulling images from Docker Hub is convenient, but there are many reasons to store images in your own registry. For example, Docker Hub doesn’t guarantee to produce the same image on repeated pulls, i.e., your base image might have changed. It’s also possible to inadvertently expose secrets in an intermediate image used to build the image stored on Docker Hub. There is also the possibility of vulnerabilities in even official images. This article shows how to create a repository and how to build and push images to that repository

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