AWS DevOps & Developer Productivity Blog

Tag: AI/ML

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Boosting Unit Test Automation at Audible with Amazon Q Developer

Audible, an Amazon company, is a leading producer and provider of audio storytelling. With a vast library of over 1,000,000 titles including audiobooks, podcasts, and Audible Originals with specific curated offerings available in each marketplace, Audible makes it easy to transform everyday moments into extraordinary opportunities for learning, imagination, and entertainment through immersive audio experiences. […]

Multi Agent Collaboration with Strands

Multi Agent Collaboration with Strands

In the evolving landscape of autonomous systems, multi-agent collaboration is becoming not only feasible but necessary. As agents gain more capabilities, like advanced reasoning, adaptation, and tool use, the challenge shifts from individual performance to effective coordination. The question is no longer “can an agent solve a task?” but “how do we organize execution across […]

Streamline DevOps troubleshooting: Integrate CloudWatch investigations with Slack

Infrastructure alerts pose a challenge for DevOps teams, particularly when they occur outside of regular business hours. The complexity isn’t merely in receiving notifications, it lies in rapidly assessing their severity and determining the root cause. This challenge is compounded when upstream service disruptions cascade into multiple downstream alerts, creating a confusion of notifications that […]

Amazon introduces SWE-PolyBench, a multilingual benchmark for AI Coding Agents

Coding agents powered by large language models have shown impressive capabilities in software engineering tasks, but evaluating their performance across diverse programming languages and real-world scenarios remains challenging. This led to a recent explosion in benchmark creation to assess the coding effectiveness of said systems in controlled environments. In particular, SWE-Bench which measures the performance […]

Leverage powerful generative-AI capabilities for Java development in the Eclipse IDE public preview

Today marks an exciting milestone for Eclipse developers everywhere: we’re thrilled to announce the public preview of Amazon Q Developer in the Eclipse IDE. This integration brings the power of AI-driven development directly into one of the most popular development environments. In this blog post, we’ll explore some of its game-changing features, and show you […]

Analyzing your AWS Cost Explorer data with Amazon Q Developer: Now Generally Available

We are excited to announce the general availability of the cost analysis capability in Amazon Q Developer. This powerful feature integrates Q Developer’s natural language processing capabilities with AWS Cost Explorer, revolutionizing how you analyze and understand your AWS costs. Initially launched in preview on April 30, 2024, the Amazon Q cost analysis capability now offers enhanced […]

Expanded resource awareness in Amazon Q Developer

Expanded resource awareness in Amazon Q Developer

Recently, Amazon Q Developer announced expanded support for account resource awareness with Amazon Q in the AWS Management Console  and the AWS Mobile Application. This is coupled with the general availability of Amazon Q Developer in AWS Chatbot, enabling you to ask questions from Microsoft Teams or Slack. Additionally, Amazon Q will now provide context-aware assistance for […]

Introducing the next-level of AI-powered workflows with Amazon Q Developer inline chat

Earlier today, Amazon Q Developer announced support for inline chat. Inline chat combines the benefits of in-IDE chat with the ability to directly update code, allowing developers to describe issues or ideas directly in the code editor, and receive AI-generated responses that are seamlessly integrated into their codebase. In this post, I will introduce the […]

Directing ML-powered Operational Insights from Amazon DevOps Guru to your Datadog event stream

Amazon DevOps Guru is a fully managed AIOps service that uses machine learning (ML) to quickly identify when applications are behaving outside of their normal operating patterns and generates insights from its findings. These insights generated by DevOps Guru can be used to alert on-call teams to react to anomalies for business mission critical workloads. […]