Posts Tagged ai

Future of the Cloud: 10 Trends Shaping 2025 and Beyond

Future of the Cloud: 10 Trends Shaping 2025 and Beyond

In 2025, several trends will dominate cloud computing, driving innovation, efficiency, and scalability. From Infrastructure as Code (IaC) to AI/ML, platform engineering to multi-cloud and hybrid strategies, and security practices, let’s explore the 10 biggest emerging trends.

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PulumiUP 2024: Dive Into the Future of Cloud, Platform Engineering, and AI/ML

PulumiUP 2024: Dive Into the Future of Cloud, Platform Engineering, and AI/ML

PulumiUP 2024 is just around the corner! It will be held on September 18th, starting at 8 AM PT | 15:00 UTC +0, and with over 5,500 engineers from all over the world already registered, this is shaping up to be the must-attend event for cloud professionals, platform engineers, and AI/ML enthusiasts alike. From entry-level engineers to tech executives, this event brings together professionals from companies of all sizes to explore the latest innovations and best practices in Cloud and IaC, Platform Engineering & DevOps, and AI/ML.

If you haven’t registered yet, now’s the time! Start building your schedule today, select the talks you want to watch live and on-demand and add them to your schedule.

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Why Switch to Pulumi for Infrastructure as Code?

Why Switch to Pulumi for Infrastructure as Code?

The cloud promised to revolutionize your business.

Faster innovation. Lower costs. Unlimited scalability.

But for many companies, that promise remains frustratingly out of reach. Instead of accelerating product development, infrastructure has become a bottleneck. You and your team (DevOps, platform, or infrastructure engineering teams) are bogged down by:

  • Clunky tools and manual processes
  • Provisioning a simple test environment takes days
  • Rolling out updates across regions takes weeks
  • The combinations of modern cloud architectures seems infinite

You know there has to be a better way. A way to truly harness the power of the cloud and turn it into your competitive advantage.

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Introducing Pulumi Copilot: Intelligent Cloud Management

Introducing Pulumi Copilot: Intelligent Cloud Management

AI is transforming how users interact with every category of technology today, and cloud infrastructure is no exception. Last year we launched Pulumi AI to combine generative AI with Pulumi’s knowledge of cloud infrastructure, helping users solve complex cloud development problems using Infrastructure-as-Code. Pulumi AI has seen rapid adoption and engagement, with tens of thousands of users leveraging Pulumi AI over the last year.

Today, we’re excited to introduce Pulumi Copilot, a huge leap forward in applying AI to cloud infrastructure management. Pulumi Copilot is a new conversational chat interface integrated throughout Pulumi Cloud, enabling Pulumi Cloud users to quickly accomplish a variety of cloud infrastructure management tasks by leveraging the power of large language models plus the rich capabilities of Pulumi Cloud.

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Uploading documents to your AI Slackbot in real-time using S3, SQS and Pulumi on AWS

Uploading documents to your AI Slackbot in real-time using S3, SQS and Pulumi on AWS

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.

arti-architecture.png

To follow along, clone the project, git clone https://github.com/catmeme/arti.git or view it on GitHub.

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Adding data to Pinecone using S3, Embedchain and Pulumi on AWS for an AI Slack bot

Adding data to Pinecone using S3, Embedchain and Pulumi on AWS for an AI Slack bot

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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Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS

Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS

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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Low-Code LLM Apps with LocalAI, Flowise, and Pulumi on AWS

Low-Code LLM Apps with LocalAI, Flowise, and Pulumi on AWS

In a previous blog post from me, we discussed how easy it is to build your 🦜️🔗 LangChain LLM application and use 🦜️🏓 LangServe and Pulumi to deploy it on an AWS Fargate cluster. We even went a step further and deployed a Pinecone index, all in a few lines of Pulumi code, to provide a vector store for our LLM application.

Let me walk you this time a different path on creating a LLM applications. This LLM-powered application is using Flowise, a low-code/node drag & drop tool to visualize and build our LLM application and LocalAI. LocalAI is a local inference engine that allows us to run LLMs locally or on-prem with consumer grade hardware. Everything will be deployed on an AWS EKS cluster using Pulumi and TypeScript.

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The Present and (Near) Future of AI and Infrastructure as Code

The Present and (Near) Future of AI and Infrastructure as Code

AI is impacting almost every industry today, and for good reason - we are seeing fundamentally new experiences being made possible across a wide variety of products, and a set of new AI capabilities that promise even more incredible change in the near future.

Software development is among the earliest and most prominent fields to realize the benefits of AI, evidenced by the rapid adoption of tools like Github Copilot which is now one of the most heavily adopted developer tools of all time. Developers are benefiting from an incredible increase in their productivity with better scale and faster time to market.

We’re seeing the impacts of AI in the cloud Infrastructure development space in two impactful and complimentary directions:

  • 🤖➜☁️: AI is transforming how we author, build and manage cloud infrastructure
  • ☁️➜🤖: Cloud infrastructure tooling is changing how we build and deliver AI-based applications

At Pulumi, we’ve already seen profound impacts from AI in both of these directions.

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Easy LangServe Apps with Pulumi on AWS

Easy LangServe Apps with Pulumi on AWS

We all know how easy it is to create, deploy, and manage any cloud infrastructure with Pulumi using your favorite programming language. With the rise of artificial intelligence (AI) more and more developers are working on LLM-powered applications and services. And with this, the need to have the same ease of use for creating, deploying, and managing the infrastructure for these applications is growing.

In this blog post, we will show you how to this can be achieved with combining Pulumi and LangServe.

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