This section lists and introduces the blogs you have translated:
This article explains how to link a local Visual Studio Code environment with Amazon SageMaker Unified Studio so you can optimize data and AI development workflows. It walks through personalizing the IDE, accessing AWS Analytics and AI/ML services inside one unified environment, and configuring the remote connection prerequisites to build end-to-end data and AI pipelines.
This post introduces the newly released Amazon EC2 M4 and M4 Pro Mac instances that are built on the Apple M4 Mac mini and the AWS Nitro System. It covers the hardware configuration (Apple silicon M4/M4 Pro chips, multi-core CPU, GPU, Neural Engine), the 15–20% build-performance improvement, the new 2-TB local storage, and how to launch the instances via the AWS Management Console or CLI while integrating with other AWS services to build automated CI/CD pipelines.
This blog provides detailed guidance on optimizing Amazon EC2 instances that use AMD EPYC processors. It shows how to choose the right instance type based on workload characteristics (compute-intensive, big data and analytics, databases, web servers, AI/ML), explains 3rd- and 4th-generation AMD EPYC features, and outlines practical tuning methods—CPU, memory, and system parameters—to deliver the best price-to-performance ratio.