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<h4><Badgecolor="blue">Improvement</Badge> [Updated Serverless endpoint creation flow](https://docs.runpod.io/serverless/endpoints/overview) </h4> The endpoint creation flow now offers six deployment paths — Hello World, Hugging Face LLM, Docker, GitHub, Flash, and Hub (which replaces the previous "Ready-to-Deploy Repos" option). Each path walks you through the right setup for your use case.
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New tutorial covering how to pull container images from private AWS ECR repositories into Runpod Pods using cross-account IAM delegation. Includes configuring ECR repository policies, adding ECR credentials in the Runpod console, and deploying a Pod with a private image, without managing credentials directly. [Read the tutorial](/tutorials/pods/use-private-ecr-images)
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<h4><Badgecolor="green">New Release</Badge> [Deploy Pods with private AWS ECR images - BETA](/tutorials/pods/use-private-ecr-images) </h4> New tutorial covering how to pull container images from private AWS ECR repositories into Runpod Pods using cross-account IAM delegation. Includes configuring ECR repository policies, adding ECR credentials in the Runpod
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console, and deploying a Pod with a private image, without managing credentials directly.
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@@ -44,15 +44,18 @@ Before creating an endpoint, ensure you have a [handler function](/serverless/wo
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1. Navigate to the [Serverless section](https://www.console.runpod.io/serverless) and click **New Endpoint**.
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2. Choose your deployment source:
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-**Import Git Repository**: See [Deploy from GitHub](/serverless/workers/github-integration)
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-**Import from Docker Registry**: See [Deploy from Docker Hub](/serverless/workers/deploy)
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-**Ready-to-Deploy Repos**: Select a preconfigured endpoint
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3. Configure your endpoint:
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-**Endpoint Name** and **Type** (Queue-based or Load balancer)
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-**GPU Configuration** and worker settings
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2. Choose your deployment path:
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-**Hello World**: Runpod forks a starter worker template into a new GitHub repo in your account. Choose Queue-based or Load balancing, then click **Deploy**.
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-**Hugging Face LLM**: Search for any text-generation model on Hugging Face (for example, type "Gemma" to find Gemma 4), select it, and click **Create Endpoint**. Runpod deploys a vLLM endpoint for you.
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-**Docker**: Deploy from a container image. Select a saved Serverless template to fill in the container configuration automatically, or skip the template and enter an image name manually. See [Deploy from Docker](/serverless/workers/deploy).
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-**GitHub**: Select a repository, filtering by code owner if needed. Runpod checks for a Dockerfile and runs a background check on your handler: queue-based endpoints check for handler files, and load balancing endpoints check for a `/ping` path. See [Deploy from GitHub](/serverless/workers/github-integration).
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-**Hub**: Opens the Hub browser, where you can browse and deploy prebuilt workers. This replaces the previous "Ready-to-Deploy Repos" option. See [Hub overview](/hub/overview).
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-**Flash**: A guided setup flow for [Flash](/flash/overview) that walks you through installing the SDK, initializing your project, and sending your first command. Steps complete automatically as you progress.
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3. For the GitHub, Docker, and Hello World paths, configure your endpoint before deploying:
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-**Endpoint name** and **type** ([Queue-based](/flash/create-endpoints#queue-based-endpoints) or [Load balancing](/flash/create-endpoints#load-balanced-endpoints))
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-**GPU** configuration and worker scaling
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-**Model** (optional): Enter a Hugging Face URL for [cached models](/serverless/endpoints/model-caching)
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-**Environment Variables**: See [environment variables](/serverless/development/environment-variables)
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-**Environment variables** and container configuration. See [environment variables](/serverless/development/environment-variables).
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