Tag: Danilo Poccia

I find quantum computing fascinating! At its simplest level, it extends the concept of bits, that have 0 or 1 values, with quantum bits, or qubits, that can have a combination of two different (quantum) states. Two characteristics make qubits really interesting: When you look at the value of a qubit, you get only one of the two possible states with a probability that depends on how its own states are combined. Multiple qubits can be “connected” together (this is called quantum entanglement) so that by changing the state of one, even just by reading its value, you alter the states of the others. These characteristics come from low-level properties described by quantum mechanics, a fundamental theory in physics that…

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…

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…

In August, we introduced the general-purpose Amazon EC2 M6i instances powered by the latest generation Intel Xeon Scalable processors (code-named Ice Lake) with an all-core turbo frequency of 3.5 GHz. Compute-optimized EC2 C6i instances were also made available last month. Today, I am happy to share that we are expanding our sixth-generation x86-based offerings to include memory-optimized Amazon EC2 R6i instances. Here’s a quick recap of the advantages of the new R6i instances compared to R5 instances: A larger instance size (r6i.32xlarge) with 128 vCPUs and 1,024 GiB of memory that makes it easier and more cost-efficient to consolidate workloads and scale up applications Up to 15 percent improvement in compute price/performance Up to 20 percent higher memory bandwidth Up…