Pulumi allows you to use the best features of programming languages to build your infrastructure while ensuring compatibility with your current development environments. To this end Pulumi provides a seamless experience when authoring TypeScript programs, managing the compilation of your program for you. With the latest release of our Node.js SDK, we’ve made this even more flexible by making it easier than ever to choose the version of TypeScript you want to use.

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As always, we have been actively rolling out new features in response to the invaluable feedback from our ever-growing community. We’ve shipped several security and usability features to Pulumi ESC in response to feedback from our growing user base. Moreover, we’ve also added new enhancements to our core Platform CLI and Providers. In addition to the release notes, stay up-to-date with all things Pulumi by following the new features blogs and the pulumi/pulumi repo changelog. With so much to explore, let’s dive into the major updates across Pulumi from the past two months!

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The Pulumi Kubernetes provider makes it easy to deploy Kubernetes resources to your cluster, giving you options based on how your application or workload is packaged. The options include strongly-typed resources for standard Kubernetes types, Helm charts, Kustomizations, and Kubernetes manifests. In v4.10, we leveled up the support for working with Kubernetes manifests with the introduction of the yaml/v2 package. The package provides new implementations of the ConfigGroup and ConfigFile resources, expanding support to the Pulumi Java SDK and to Pulumi YAML.

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In the introductory blog post, we learned to Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS. However, we made a few concessions in the application logic to illustrate the broader picture of what we were able to achieve combining these three technologies. Now that we have a solid foundation for deploying our Slack bot and querying our data, lets begin moving from proof-of-concept to production-ready, iteratively.

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Welcome to the final post in our series of articles focused on infrastructure as code (IaC) recommended practices. In this post, we’ll wrap up our recommendations for IaC with Pulumi, summarizing the recommendations from previous posts as well as highlighting some areas of potential future growth for the team at Zephyr Archaeotech Emporium—the fictional company at the center of the story throughout this series.

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At Pulumi, the stability of our CLI and SDK releases is critically important. A lot of infrastructure is built and deployed using Pulumi, and any bugs in how that infrastructure is deployed can cause outages. While we put a lot of emphasis on unit and integration testing, we are also constantly investing in new ways to provide additional safeguards to ensure we always deliver stable releases. To that end, we are introducing new dev releases of our CLI and SDKs, which will enable users who want to work with the very latest bits to try them out before they are deployed widely to the entire Pulumi user base. This blog post will walk you through how we are using them internally, and how you can too!

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Today, we are thrilled to add integration support for 1Password in preview within Pulumi Environments, Secrets, and Configuration (ESC). Since its launch, numerous organizations have leveraged Pulumi ESC to manage secrets and simplify configurations using composable environments. Leveraging Pulumi ESC’s comprehensive set of providers, users have obtained dynamic cloud provider credentials and retrieved secrets from other secrets management platforms, including HashiCorp Vault.

The addition of 1Password, known for its developer-centric approach to secrets management, to our roster of integrations has been a top request among our community. As users of 1Password ourselves, this collaboration represents more than just a feature release; it embodies our commitment to enriching the developer experience and fostering secure, efficient development workflows.

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One of Pulumi’s core goals is to provide cloud engineers with access to the very best software engineering tooling available. Using traditional programming languages like Node.js, Python, Go, .NET and Java means the latest and greatest software engineering tools from each of these ecosystems is available to bring to bear on managing cloud infrastructure, natively integrated with your existing development environments.

In the Node.js ecosystem, we’ve seen an explosion of great tooling over the last couple of years around support for monorepos - larger repositories built out of many smaller projects, and sharing code and dependencies smartly across all the various projects. We’ve seen many of our Pulumi Node.js users adopting these tools and repo structures, including tools like Yarn Workspaces, pnpm, Turborepo, and especially Nx.

While it has always been possible to apply these tools to Pulumi Node.js projects in TypeScript or JavaScript just like any other Node.js project, we’ve recently made a number of enhancements and fixes to make sure that Pulumi works truly seamlessly with these tools.

In this post, we’ll show how you can build a seamless development workflow by integrating Pulumi code level abstractions, such as Component Resources, with a monorepo-based build system like Nx.

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We’re excited to announce the launch of the Pulumi Environments, Secrets, and Configurations (ESC) Key-Value Table Editor. At Pulumi, we’re committed to providing flexible solutions that cater to diverse development needs and practices. This latest addition underscores our dedication to this principle by offering a user-friendly interface for managing complex configurations and secrets.

Pulumi ESC simplifies the management of secrets and configurations by reducing duplication and drift, empowering development teams to focus on building and deploying. The existing YAML-based code editor offers a native way for developers to author and manage configurations.

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The integration of artificial intelligence (AI) to improve user experiences is gaining popularity in today’s world. One fascinating application of AI is the creation of chatbots, which can engage users in conversation and provide helpful information or services. In this blog post, we’ll explore the process of building an AI-powered Slack bot using Embedchain, a Retrieval-Augmented Generation (RAG) framework powered by LangChain. Additionally, we’ll deploy our bot on AWS using Pulumi, a modern infrastructure as code (IaC) platform.

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