We are super excited to announce integration support for AWS Systems Manager - Parameter Store within Pulumi Environments, Secrets, and Configuration (ESC). Parameter Store is a popular managed service by AWS for storing and managing secrets and other configuration, and its integration with ESC has been highly requested among the community.
Pulumi is excited to be at AWS re:Invent this week, where we’re showcasing our broad and deep support for AWS across all our products. From automating infrastructure with Pulumi IaC to securing secrets with Pulumi ESC to managing cloud assets with Pulumi Insights, Pulumi makes AWS a competitive advantage. Whether you’re a developer, DevOps pro, or platform engineer, Pulumi delivers the tools you need to build and manage modern cloud applications with ease.
Stop by the Pulumi re:Invent booth #370 this week to chat with experts on the Pulumi team. If you can’t make it to re:Invent, join our workshop, Accelerating Platform Engineering with Pulumi on AWS, on December 11, 2024, to see how Pulumi can enhance your cloud operations on AWS.
AWS has introduced a new feature for Amazon Elastic Kubernetes Service (EKS): Amazon EKS Hybrid Nodes. This addition to the Amazon EKS Hybrid/Edge portfolio allows organizations to maintain their Kubernetes control plane in AWS while running workloads on-premises or at the edge. This hybrid approach offers the best of both worlds - AWS’s reliable and scalable control plane management combined with the flexibility to run workloads wherever they make the most sense for your business.
Building an EKS cluster requires choosing how your containers will actually run - either on EC2 instances you manage or through AWS Fargate’s pod-by-pod approach. The differences can be pretty dramatic in practice. I’m setting up a demo cluster right now using Pulumi, so let me show you what I mean.
Here is my Fargate cluster:
The latest major release of the Pulumi EKS Provider is available now!
This release delivers significant improvements in flexibility, security and introduces new features to enhance your Kubernetes experience on AWS. AWS recently announced the deprecation of two features used by default in Pulumi EKS: the aws-auth ConfigMap and the AL2 operating system. Pulumi EKS v3 addresses these deprecations, enhances the maintainability of the provider, and aligns it with EKS best practices.
We’re excited to announce the general availability of the new AWS Cloud Control Provider for Pulumi (previously “AWS Native”). AWS is one of the most-used cloud providers across the Pulumi ecosystem, and we are committed to providing the fastest possible access to new AWS capabilities to all Pulumi users. This provider delivers on that promise by providing native support for all resources in the AWS Cloud Control APIs. As part of this launch, we are also renaming the provider from “AWS Native” to “AWS Cloud Control Provider,” based on customer feedback during the preview phase, to provide users with a broader range of advanced cloud management tools exposed by the AWS Cloud Control API. This provider includes the following features and benefits,
In the introductory blog post, we learned to Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS, and continued with Adding data to Pinecone using S3, Embedchain, and Pulumi on AWS for an AI Slack bot.
For reference, here’s what our architecture looked like at the end of the second blog post.
To follow along, clone the project, git clone https://github.com/catmeme/arti.git or view it on GitHub.
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.
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.
Building low-code LLM applications just got easier! With Flowise, LocalAI, and Pulumi, you can quickly create, deploy, and manage AI-powered workflows on AWS EKS—without writing complex code.
In this guide, you’ll learn how to:
Flowise simplifies LLM orchestration with a drag-and-drop interface, while LocalAI enables local inference without requiring a GPU. Pulumi streamlines cloud infrastructure deployment with just a few lines of code.