Category: Artificial Intelligence

Observability in a container-centric environment presents new challenges for operators due to the increasing number of abstractions and supporting infrastructure. In many cases, organizations can have hundreds of clusters and thousands of services/tasks/pods running concurrently. This post will demonstrate new features in Amazon DevOps Guru to help simplify and expand the capabilities of the operator. […]

Applying various transformations to images at scale is an easily parallelized and scaled task. As a Computer Vision research team at Amazon, we occasionally find that the amount of image data we are dealing with can’t be effectively computed on a single machine, but also isn’t large enough to justify running a large and potentially […]

Critical business applications are monitored in order to prevent anomalies from negatively impacting their operational performance and availability. Amazon DevOps Guru is a Machine Learning (ML) powered solution that aids operations by detecting anomalous behavior and providing insights and recommendations for how to address the root cause before it impacts the customer. This post demonstrates how Amazon […]

with Aaron Friedman (Principal PM-T for xGuru services) Amazon CodeGuru is a developer tool that uses machine learning and automated reasoning to catch hard to find defects and security vulnerabilities in application code. The purpose of this blog is to show how new CodeGuru Reviewer features help improve the security posture of your Python applications […]

InnerSource is the term for the emerging practice of organizations adopting the open source methodology, albeit to develop proprietary software. This blog discusses the building of a model InnerSource ecosystem that leverages multiple AWS services, such as CodeBuild, CodeCommit, CodePipeline, CodeArtifact, and CodeGuru, along with other AWS services and open source tools.

Gridium creates software that lets people run commercial buildings at a lower cost and with less energy. Currently, half of the world lives in cities. Soon, nearly 70% will, while buildings utilize 40% of the world’s electricity. In the U.S. alone, commercial real estate value tops one trillion dollars. Furthermore, much of this asset class […]

Here we are introducing the inconsistency detector for Java in Amazon CodeGuru Reviewer. CodeGuru Reviewer automatically analyzes pull requests (created in supported repositories such as AWS CodeCommit, GitHub, GitHub Enterprise, and Bitbucket) and generates recommendations for improving code quality. The Inconsistency Principle Software is repetitive, so it’s possible to mine usage specifications from the mining […]

Amazon CodeGuru Profiler recently began providing recommendations for applications written in Python. Additionally, the new automated onboarding process for Lambda functions makes it even easier to use CodeGuru Profiler with serverless applications built on Lambda. This post highlights these new features by explaining how to set up and utilize Codeguru Profiler on an AWS Lambda function written in Python.

This post shows you how to configure CodeGuru Profiler to collect multiple applications’ profiling data into a central account and review the applications’ performance data on one dashboard.

This post announces the availability of new self-paced where you learn how to use CodeGuru Reviewer to automatically scan your code base, identify hard-to-find bugs and vulnerabilities, and get recommendations for fixing the bugs and security issues.