AWS Graviton2 processors are custom-designed by AWS to enable the best price performance in Amazon EC2. Thousands of customers are realizing significant price performance benefits for a wide variety of workloads with Graviton2-based instances. Today, we are announcing the general availability of Amazon EC2 G5g instances that extend Graviton2 price-performance benefits to GPU-based workloads including graphics applications and machine learning inference. In addition to Graviton2 processors, G5g instances feature NVIDIA T4G Tensor Core GPUs to provide the best price performance for Android game streaming, with up to 25 Gbps of networking bandwidth and 19 Gbps of EBS bandwidth. These instances provide up to 30 percent lower cost per stream per hour for Android game streaming than x86-based GPU instances. G5g…
New for AWS Compute Optimizer – Resource Efficiency Metrics to Estimate Savings Opportunities and Performance Risks
By applying the knowledge drawn from Amazon’s experience running diverse workloads in the cloud, AWS Compute Optimizer identifies workload patterns and recommends optimal AWS resources. Today, I am happy to share that AWS Compute Optimizer now delivers resource efficiency metrics alongside its recommendations to help you assess how efficiently you are using AWS resources: A dashboard shows you savings and performance improvement opportunities at the account level. You can dive into resource types and individual resources from the dashboard. The Estimated monthly savings (On-Demand) and Savings opportunity (%) columns estimate the possible savings for over-provisioned resources. You can sort your recommendations using these two columns to quickly find the resources on which to focus your optimization efforts. The Current performance risk…
New for AWS Compute Optimizer – Enhanced Infrastructure Metrics to Extend the Look-Back Period to Three Months
By using machine learning to analyze historical utilization metrics, AWS Compute Optimizer recommends optimal AWS resources for your workloads to reduce costs and improve performance. Over-provisioning resources can lead to unnecessary infrastructure costs, and under-provisioning resources can lead to poor application performance. Compute Optimizer helps you choose optimal configurations for three types of AWS resources: Amazon Elastic Compute Cloud (Amazon EC2) instances, Amazon Elastic Block Store (EBS) volumes, and AWS Lambda functions, based on your utilization data. Today, I am happy to share that AWS Compute Optimizer now supports recommendation preferences where you can opt in or out of features that enhance resource-specific recommendations. For EC2 instances, AWS Compute Optimizer analyzes Amazon CloudWatch metrics from the past 14 days to…
New – AWS Migration Hub Refactor Spaces Helps to Incrementally Refactor Your Applications
I am excited to announce the preview of AWS Migration Hub Refactor Spaces, a new capability of AWS Migration Hub to let you refactor existing applications into distributed applications, typically based on microservices. There are multiple reasons why you want to refactor existing applications. You might want to make your code more modular, use more modern frameworks, use different data storage, etc. In general, when refactoring, your objective is to make your application easier to maintain and evolve over time. Other benefits might include handling larger workloads, increasing resiliency, or lowering costs. But let’s face it, refactoring is hard. I usually compare refactoring to changing the engines, cabin seats, and entertainment system of a plane while keeping the plane in…