Deploy vLLM on AWS in under 10 Minutes! скачать в хорошем качестве

Deploy vLLM on AWS in under 10 Minutes!

You’ve heard all the buzz around vLLM and want to try it but between GPUs, dependencies, AWS setup, and driver installs, it’s hard to know where to start. This video takes care of all of that for you. First, I'll break down what vLLM actually is and why it’s such a game changer for inference performance. Then I show you the exact automation you need to run to get up and running in under 10 minutes. These two playbooks is all you need. Playbook 1: aws_helper walks you through a quick set of prompts and auto-generates your entire AWS config vars file (region, GPU instance, VPC, subnet, key pair, disk size, etc.), so there’s no manual cloud setup or guessing involved. Playbook 2: vllm_installer takes that vars file input and handles everything else. It provisions the instance, installs all required drivers, Docker, and pulls the vLLM container so you don’t need to know a single dependency. By the end, you’ll have a fully running vLLM server with a curl-ready endpoint, without touching a single driver or configuration file yourself. If you want to start using vLLM, this is your shortcut! 👉 Get the playbooks here: https://github.com/ansible-tmm/ansibl... Timestamps 0:00 Why vLLM and why it’s so fast 1:22 How vLLM optimizes memory & inference performance 3:29 AWS service quota requirement for GPU instances 4:18 Best AWS instance to use for just getting started 5:03 Ansible + collection prerequisites 6:04 AWS CLI and credential setup 7:11 Creating a Hugging Face access token 7:58 Playbook 1 – aws_helper walkthrough 9:56 Reviewing the generated vars file 9:59 Playbook 2 – vllm_installer deployment 10:40 Instance provisioning & dependency installation 11:45 vLLM server is live 12:03 Testing with curl