AWS for Media & Entertainment (M&E) is a cloud-based initiative that provides purpose-built services, solutions, and a partner ecosystem to help media companies transform content creation, supply chains, broadcast, streaming, and data analytics. It differentiates itself by offering a comprehensive set of nine dedicated AWS services—including AWS Elemental MediaLive, MediaConvert, and MediaPackage—alongside over 400 AWS Partners and solutions like Amazon Nimble Studio for rapid creative studio setup. The initiative also establishes dedicated industry specialists and professional services teams to accelerate deployments, serving leading customers such as Netflix, Formula 1, Discovery, and Disney. This integrated approach enables M&E organizations to innovate faster, optimize workflows, and deliver breakthrough audience experiences.
AWS Elemental MediaConnect Router solved a key technical constraint that made the hybrid architecture possible.
I show you how to enable Elemental Inference on an AWS Elemental MediaLive channel and use the Smart Crop (vertical video) feature to automatically convert landscape broadcast content into vertical 9:16 format.
This post explains the framework and walks through an end-to-end example using LiveRamp identity enrichment.
We show how you can monetize your live streams using Amazon IVS SSAI.
Learn more about Captain, an agentic AI companion built by Bundesliga Media and embedded inside the official Bundesliga app.
Learn how 5, part of Paramount, migrated from a dual-pipeline packaging architecture to AWS Elemental MediaPackage v2—consolidating infrastructure, eliminating manual failover, and expanding to new platforms across a 12-month collaborative journey with AWS.
This post walks through what the feature does, how to enable it, and where it fits in a typical live streaming workflow.
Enable Elemental Inference on an AWS Elemental MediaLive channel.
AWS Lambda has launched a public preview for managed runtimes supporting Node.js 26 and Python 3.15. This initiative allows developers and third-party tool providers to test compatibility and provide feedback before the runtimes reach general availability.
AWS has launched the AWS Agent Registry in preview and contributed to the new Agentic Resource Discovery (ARD) open specification. These tools aim to provide a standardized, searchable catalog for AI agents and Model Context Protocol (MCP) servers to facilitate cross-environment resource discovery.
AWS has released the Agentic Data Operations Platform (ADOP), a reference architecture that utilizes Amazon Bedrock and Claude to automate data engineering tasks like ETL, quality checks, and semantic modeling. The platform is designed to accelerate data source onboarding by generating deterministic code artifacts while enforcing architectural and compliance guardrails.
Amazon EKS has introduced automated certificate authority (CA) rotation to help manage cluster security and prevent expiration for AWS-managed components. While AWS automates the lifecycle for managed nodes, customers remain responsible for updating worker nodes and external clients to maintain secure API connections.
AWS has introduced inbound prefix controls for its Direct Connect service, increasing the maximum route prefix limit from 100 to 1,000 for private and transit virtual interfaces. This update allows streaming infrastructure teams to manage prefix capacity more granularly across connection and gateway levels.
Amazon Web Services has expanded the regional availability of its Graviton4-powered EC2 C8gd, M8gd, and R8gd instances. These instances provide high-speed local NVMe storage and improved performance for compute-intensive streaming workloads such as video encoding and real-time analytics.
Amazon Redshift has introduced long-term system table retention by enabling automatic data replication to Amazon S3 Tables in Apache Iceberg format. This update allows engineers to bypass custom ETL pipelines for cross-warehouse observability and performance analysis.
Amazon has introduced a visual interface for Generative AI Inference Recommendations within its SageMaker AI Studio. The tool utilizes NVIDIA AIPerf to benchmark model configurations, helping engineering teams optimize production workloads for latency, throughput, and cost.
AWS has detailed its strategy for integrating vector search capabilities directly into six of its existing data services, including OpenSearch, S3, and DynamoDB. These native integrations aim to support agentic AI workflows, such as RAG and multimodal content discovery, without requiring customers to migrate data to specialized vector databases.
AWS has published architectural guidance for scaling agentic AI systems within enterprise environments using Amazon SageMaker and Amazon Bedrock. The framework focuses on separating control and execution planes to manage multi-model and multi-framework environments while avoiding vendor lock-in.
