aws · kazisufiyan-k2 · Mar 19, 2026
diff --git a/README.md b/README.md
@@ -9,102 +9,149 @@
 
 ______________________________________________________________________
 
-## 🔥 What's New
-
-### 🚀 Release Highlights
-
-- **[2026/03/10]** Released v0.17.0 [vLLM DLCs](https://gallery.ecr.aws/deep-learning-containers/vllm)
-  - EC2/EKS/ECS: `public.ecr.aws/deep-learning-containers/vllm:0.17-gpu-py312-ec2`
-  - SageMaker: `public.ecr.aws/deep-learning-containers/vllm:0.17-gpu-py312`
-- **[2026/03/09]** Released v0.5.9 [SGLang DLCs](https://gallery.ecr.aws/deep-learning-containers/sglang)
-  - EC2/EKS/ECS: `public.ecr.aws/deep-learning-containers/sglang:0.5.9-gpu-py312-ec2`
-  - SageMaker: `public.ecr.aws/deep-learning-containers/sglang:0.5.9-gpu-py312`
-- **[2026/03/09]** Released v0.16.0 [vLLM DLCs](https://gallery.ecr.aws/deep-learning-containers/vllm)
-  - EC2/EKS/ECS: `public.ecr.aws/deep-learning-containers/vllm:0.16-gpu-py312-ec2`
-  - SageMaker: `public.ecr.aws/deep-learning-containers/vllm:0.16-gpu-py312`
-- **[2025/11/17]** Released first [SGLang DLCs](https://gallery.ecr.aws/deep-learning-containers/sglang)
-  - SageMaker: `public.ecr.aws/deep-learning-containers/sglang:0.5.5-gpu-py312`
-
-### 📢 Support Updates
-
-- **[2026/02/10]** Extended support for PyTorch 2.6 Inference containers until June 30, 2026
-  - PyTorch 2.6 Inference images will continue to receive security patches and updates through end of June 2026
-  - For complete framework support timelines, see our [Support Policy](https://aws.github.io/deep-learning-containers/reference/support_policy/)
-
-### 🎉 Hot Off the Press
-
-- 🌐
-  **[Master Distributed Training on Amazon EKS](https://aws.amazon.com/blogs/machine-learning/configure-and-verify-a-distributed-training-cluster-with-aws-deep-learning-containers-on-amazon-eks/)**
-  \- Set up and validate a distributed training environment on Amazon EKS for scalable ML model training across multiple nodes.
-- 🔄
-  **[Level Up with Amazon SageMaker AI & MLflow](https://aws.amazon.com/blogs/machine-learning/use-aws-deep-learning-containers-with-amazon-sagemaker-ai-managed-mlflow/)**
-  \- Integrate AWS DLCs with Amazon SageMaker AI's managed MLflow service for streamlined experiment tracking and model management.
-- 🚀
-  **[Deploy LLMs Like a Pro on Amazon EKS](https://aws.amazon.com/blogs/architecture/deploy-llms-on-amazon-eks-using-vllm-deep-learning-containers/)**
-  \- Deploy and serve Large Language Models efficiently on Amazon EKS using vLLM Deep Learning Containers.
-- 🎯
-  **[Web Automation with Meta Llama 3.2 Vision](https://aws.amazon.com/blogs/machine-learning/fine-tune-and-deploy-meta-llama-3-2-vision-for-generative-ai-powered-web-automation-using-aws-dlcs-amazon-eks-and-amazon-bedrock/)**
-  \- Fine-tune and deploy Meta's Llama 3.2 Vision model for AI-powered web automation.
-- ⚡
-  **[Supercharge Your DL Environment](https://aws.amazon.com/blogs/machine-learning/streamline-deep-learning-environments-with-amazon-q-developer-and-mcp/)**
-  \- Integrate AWS DLCs with Amazon Q Developer and Model Context Protocol (MCP).
-
-### 🎓 Hands-on Workshop
-
-- 🚀 **[LLM Deployment on Amazon EKS Workshop](https://catalog.us-east-1.prod.workshops.aws/workshops/c22b50fb-64b1-4e18-8d0f-ce990f87eed3/en-US)** -
-  Deploy and optimize LLMs on Amazon EKS using vLLM Deep Learning Containers. For more information, see
-  [Sample Code](https://github.com/aws-samples/sample-vllm-on-eks-with-dlc)
+🔥 What's New
+🚀 Release Highlights
 
-______________________________________________________________________
+```
+[2026/03/10] Released v0.17.0 vLLM DLCs  
+    EC2/EKS/ECS: public.ecr.aws/deep-learning-containers/vllm:0.17-gpu-py312-ec2  
+    SageMaker: public.ecr.aws/deep-learning-containers/vllm:0.17-gpu-py312  
 
-## About
+[2026/03/09] Released v0.5.9 SGLang DLCs  
+    EC2/EKS/ECS: public.ecr.aws/deep-learning-containers/sglang:0.5.9-gpu-py312-ec2  
+    SageMaker: public.ecr.aws/deep-learning-containers/sglang:0.5.9-gpu-py312  
 
-AWS Deep Learning Containers (DLCs) are a suite of Docker images that streamline the deployment of AI/ML workloads on Amazon SageMaker AI, Amazon EKS, and
-Amazon EC2.
+[2026/03/09] Released v0.16.0 vLLM DLCs  
+    EC2/EKS/ECS: public.ecr.aws/deep-learning-containers/vllm:0.16-gpu-py312-ec2  
+    SageMaker: public.ecr.aws/deep-learning-containers/vllm:0.16-gpu-py312  
 
-### 🎯 What We Offer
+[2025/11/17] Released first SGLang DLCs  
+    SageMaker: public.ecr.aws/deep-learning-containers/sglang:0.5.5-gpu-py312  
+```
 
-- **Pre-optimized Environments** - Production-ready containers with optimized deep learning frameworks
-- **Latest AI/ML Tools** - Quick access to cutting-edge frameworks like vLLM, SGLang, and PyTorch
-- **Multi-Platform Support** - Run seamlessly on Amazon SageMaker AI, Amazon EKS, or Amazon EC2
-- **Enterprise-Ready** - Built with security, performance, and scalability in mind
+📢 Support Updates
 
-### 💪 Key Benefits
+```
+[2026/02/10] Extended support for PyTorch 2.6 Inference containers until June 30, 2026  
+PyTorch 2.6 Inference images will continue to receive security patches and updates through end of June 2026  
+```
 
-- **Rapid Deployment** - Get started in minutes with pre-configured environments
-- **Framework Flexibility** - Support for popular frameworks like PyTorch, TensorFlow, and more
-- **Performance Optimized** - Containers tuned for AWS infrastructure
-- **Regular Updates** - Quick access to latest framework releases and security patches
-- **AWS Integration** - Seamless compatibility with AWS AI/ML services
+🎉 Hot Off the Press
 
-### 🎮 Perfect For
+```
+🌐 Master Distributed Training on Amazon EKS  
+🔄 Level Up with Amazon SageMaker AI & MLflow  
+🚀 Deploy LLMs Like a Pro on Amazon EKS  
+🎯 Web Automation with Meta Llama 3.2 Vision  
+⚡ Supercharge Your DL Environment  
+```
 
-- Data Scientists building and training models
-- ML Engineers deploying production workloads
-- DevOps teams managing ML infrastructure
-- Researchers exploring cutting-edge AI capabilities
+🎓 Hands-on Workshop
 
-### 🔒 Security & Compliance
+```
+🚀 LLM Deployment on Amazon EKS Workshop  
+```
 
-Our containers undergo rigorous security scanning and are regularly updated to address vulnerabilities, ensuring your ML workloads run on a secure
-foundation.
+---
 
-For more information on our security policy, see [Security](https://aws.github.io/deep-learning-containers/security/).
+## 📦 About
 
-______________________________________________________________________
+AWS Deep Learning Containers (DLCs) are a suite of Docker images that streamline the deployment of AI/ML workloads on Amazon SageMaker AI, Amazon EKS, and Amazon EC2.
+
+---
+
+## 🎯 What We Offer
+
+* Pre-optimized Environments
+* Latest AI/ML Tools (vLLM, SGLang, PyTorch)
+* Multi-Platform Support
+* Enterprise-Ready Infrastructure
+
+---
+
+## 💪 Key Benefits
+
+* Rapid Deployment
+* Framework Flexibility
+* Performance Optimized
+* Regular Updates
+* Seamless AWS Integration
+
+---
+
+## 🎮 Perfect For
+
+* Data Scientists
+* ML Engineers
+* DevOps Teams
+* AI Researchers
+
+---
+
+## 🔒 Security & Compliance
+
+Our containers undergo rigorous security scanning and are regularly updated to address vulnerabilities.
+
+---
+
+## 📊 Training Data
+
+AWS Deep Learning Containers (DLCs) do not include or provide training datasets.
+They are infrastructure tools used to run machine learning frameworks like PyTorch, TensorFlow, vLLM, and SGLang.
 
-## Quick Links
+Users must provide and manage their own datasets.
 
-- [Getting Started](https://aws.github.io/deep-learning-containers/get_started/) - Get up and running in minutes
-- [Tutorials](https://aws.github.io/deep-learning-containers/tutorials/) - Step-by-step guides
-- [Available Images](https://aws.github.io/deep-learning-containers/reference/available_images/) - Browse all container images
-- [Support Policy](https://aws.github.io/deep-learning-containers/reference/support_policy/) - Framework versions and timelines
-- [Security](https://aws.github.io/deep-learning-containers/security/) - Security policy
+---
 
-## Getting Help
+## 📈 Evaluation / Benchmarks
 
-- [GitHub Issues](https://github.com/aws/deep-learning-containers/issues) - Report bugs or request features
+Performance depends on:
 
-## License
+* Framework used
+* Model architecture
+* Hardware (GPU/CPU)
+* Dataset quality
+
+Results may vary based on configuration.
+
+---
+
+## ⚠️ Limitations / Risks
+
+* No built-in datasets
+* Requires AWS knowledge (EKS, EC2, SageMaker)
+* Cost depends on usage
+* Performance depends on setup
+
+---
+
+## 🔐 Responsible Usage
+
+Users should ensure:
+
+* Proper dataset licensing
+* Data privacy compliance
+* Ethical AI practices
+
+---
+
+## 🔗 Quick Links
+
+* Getting Started
+* Tutorials
+* Available Images
+* Support Policy
+* Security
+
+---
+
+## 🤝 Getting Help
+
+* GitHub Issues
+
+---
+
+## 📄 License
 
 This project is licensed under the Apache-2.0 License.
+