<p>AWS Batch now supports Amazon ECS Managed Instances (ECS MI) as a new compute option, enabling you to run GPU-accelerated and compute-intensive batch workloads on AWS-managed infrastructure. With AWS Batch on ECS MI you can now access GPU-accelerated instances while AWS handles AMI updates, security patching, and instance lifecycle automatically, eliminating the operational overhead of customer-managed Amazon EC2 infrastructure.<br> <br> To get started, create an AWS Batch on ECS MI compute environment using the AWS Batch <i>CreateComputeEnvironment</i> API or the AWS Batch Management Console. You can specify your allowed instance types and networking configuration in the <i>managedInstancesProvider</i> block, associate the compute environment with a job queue, and submit jobs using On-Demand, Spot, or reserved capacity.<br> <br> AWS Batch on ECS Managed Instances is supported in all <a href="https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/">AWS Regions</a> where AWS Batch is available. For more information, see the <a href="https://docs.aws.amazon.com/batch/latest/userguide/ecs_managed_instances.html">AWS Batch User Guide</a>.</p>
AWS Batch now supports Amazon ECS Managed Instances
AWS Batch now supports Amazon ECS Managed Instances (ECS MI) as a new compute option, enabling you to run GPU-accelerated and compute-intensive batch workloads on AWS-managed infrastructure. With AWS Batch on ECS MI you can now access GPU-accelerated instances while AWS handles A

Pixabay (free commercial use)
Related stories

Anthropic pushes into physical world with new standard to help AI agents operate machines - CNBC
Anthropic News
Anthropic pushes into physical world with new standard to help AI agents operate machines CNBC
AWS Elastic Disaster Recovery introduces Recovery Plans for orchestrated application recovery
AWS What’s New
AWS Elastic Disaster Recovery (AWS DRS) now offers Recovery Plans, a capability that automates the sequential launch of multi-server applications during recovery and drills. Instead of launching servers one at a time and tracking dependencies manually, you define the recovery seq

Giga-Scale AI and the Ethernet Evolution: How Spectrum-X Ethernet Rewrites the Rules
NVIDIA Developer Blog
The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales to span hundreds of thousands of GPUs,... The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales

How AI Coding Agents Can Unlock Materials Simulation with NVIDIA ALCHEMI Toolkit
NVIDIA Developer Blog
Atomistic simulation requires three things: knowledge of the science, compute-efficient implementation of simulations, and accessible interfaces to the... Atomistic simulation requires three things: knowledge of the science, compute-efficient implementation of simulations, and ac

How we saved 100 terabytes of memory by optimizing 1.1.1.1’s DNS cache
Sebastiaan Neuteboom
Big Pineapple , the platform behind 1.1.1.1 , Gateway DNS , DNS Firewall , AS112 , and several other Cloudflare DNS services, stores over 250 billion DNS cache entries at any given time. At that scale, wasting a single byte per entry costs more than 250 gigabytes of memory across

Managed PostgreSQL vs. self-hosted PostgreSQL: Key benefits and trade-offs
Lauro Ojeda
Summary This post is for technical decision makers evaluating where to run production PostgreSQL workloads. It compares two valid operating models—self-managed PostgreSQL and a managed database service—through business and operational outcomes: control, engineering capacity, resi
