In a previous blog post from me, we discussed how easy it is to build your π¦οΈπ LangChain LLM application and use π¦οΈπ 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.
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.
Hello, Pulumi Pinecone Provider! π The Pinecone integration with Pulumi offers a native way to manage Pinecone indexes, including the newly-announced serverless indexes. Utilize any of Pulumi’s supported languages to effortlessly create, update, and remove your Pinecone indexes. This integration facilitates the application of Infrastructure as Code principles, helping you to work even more efficiently. Furthermore, this gives you the benefit of tapping into Pulumi’s wide range of providers, offering you a diverse and powerful set of tools to enhance your development work.
Backstage is an open source framework for building developer portals, created at Spotify and donated to the CNCF. It allows engineers to create their own development portal internally. Backstage makes it easy for teams to create a unified portal for their infrastructure tooling, software templates, services, documentation and plugins for external tools.
