Tag: Sébastien Stormacq

Today we’re launching zonal autoshift, a new capability of Amazon Route 53 Application Recovery Controller that you can enable to automatically and safely shift your workload’s traffic away from an Availability Zone when AWS identifies a potential failure affecting that Availability Zone and shift it back once the failure is resolved. When deploying resilient applications, you typically deploy your resources across multiple Availability Zones in a Region. Availability Zones are distinct groups of physical data centers at a meaningful distance apart (typically miles) to make sure that they have diverse power, connectivity, network devices, and flood plains. To help you protect against an application’s errors, like a failed deployment, an error of configuration, or an operator error, we introduced last…

Today, Amazon Inspector adds three new capabilities to increase the realm of possibilities when scanning your workloads for software vulnerabilities: Amazon Inspector introduces a new set of open source plugins and an API allowing you to assess your container images for software vulnerabilities at build time directly from your continuous integration and continuous delivery (CI/CD) pipelines wherever they are running. Amazon Inspector can now continuously monitor your Amazon Elastic Compute Cloud (Amazon EC2) instances without installing an agent or additional software (in preview). Amazon Inspector uses generative artificial intelligence (AI) and automated reasoning to provide assisted code remediation for your AWS Lambda functions. Amazon Inspector is a vulnerability management service that continually scans your AWS workloads for known software vulnerabilities…

Amazon Redshift puts artificial intelligence (AI) at your service to optimize efficiencies and make you more productive with two new capabilities that we are launching in preview today. First, Amazon Redshift Serverless becomes smarter. It scales capacity proactively and automatically along dimensions such as the complexity of your queries, their frequency, the size of the dataset, and so on to deliver tailored performance optimizations. This allows you to spend less time tuning your data warehouse instances and more time getting value from your data. Second, Amazon Q generative SQL in Amazon Redshift Query Editor generates SQL recommendations from natural language prompts. This helps you to be more productive in extracting insights from your data. Let’s start with Amazon Redshift Serverless…

I am happy to announce the general availability of Amazon Neptune Analytics, a new analytics database engine that makes it faster for data scientists and application developers to quickly analyze large amounts of graph data. With Neptune Analytics, you can now quickly load your dataset from Amazon Neptune or your data lake on Amazon Simple Storage Service (Amazon S3), run your analysis tasks in near real time, and optionally terminate your graph afterward. Graph data enables the representation and analysis of intricate relationships and connections within diverse data domains. Common applications include social networks, where it aids in identifying communities, recommending connections, and analyzing information diffusion. In supply chain management, graphs facilitate efficient route optimization and bottleneck identification. In cybersecurity,…